Strategies on Pricing, Greenness Degree, and ... - Hindawi
Transcript of Strategies on Pricing, Greenness Degree, and ... - Hindawi
Research ArticleStrategies on Pricing Greenness Degree and Carbon EmissionReduction in Supply Chains under Single and CrossDistributions of Green and Nongreen Products
Doo Ho Lee
Division of Software Media and Industrial Engineering Kangwon National University 346 Joongang-ro Samcheok-siGangwon-do 29513 Republic of Korea
Correspondence should be addressed to Doo Ho Lee enjdhleegmailcom
Received 7 October 2019 Accepted 7 March 2020 Published 10 April 2020
Academic Editor Francesco Lolli
Copyright copy 2020 DooHo Lee)is is an open access article distributed under the Creative Commons Attribution License whichpermits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Environmental sustainability has become a critical indicator in evaluations of the success and efficiency of supply chainmanagement In this study we consider a two-echelon supply chain composed of two competingmanufacturers two retailers andone third-party logistics firm )e first manufacturer produces a green product while the second manufacturer produces anongreen product Each of the two retailers can sell only a green product only a nongreen product or both green and nongreenproducts All products are initially stored by the third-party logistics firm and delivered to the retailers )is study investigatesproduct pricing the degree of greenness of the first manufacturerrsquos product and carbon emission reduction as carried out by thethird-party logistics firm Using a three-stage Stackelberg game framework we present the equilibrium strategy on pricing thedegree of greenness and carbon emission reduction for five different distribution channel structures One of our major findings isthat competition between the two manufacturers has a positive influence on the profitability of the supply chain We also find thatit is desirable for each manufacturer to choose a cross-distribution channel for its products considering the sustainability andprofitability of the supply chain
1 Introduction
During human history there has been no rapid globalwarming and environmental degradation comparable to thatoccurring today According to the Fourth Assessment Re-port of the Intergovernmental Panel on Climate Change [1]the Earthrsquos average temperature may increase from aminimum of 11sim29degC to a maximum of 24sim64degC duringthe twenty-first century In addition environmental deg-radation is one of the ten threats officially noted by theUnited Nations )e United Nations Office for Disaster RiskReduction defines environmental degradation as the re-duction of the capacity of the environment to meet socialand ecological objectives and needs [2] Rapid industriali-zation and economic growth have brought people materialabundance and greater convenience while also causingsocioenvironmental problems such as the rapid depletion of
resources unexpected natural disasters and environmentaldestruction For these reasons environmental issues haveattracted public and governmental attention around theworld [3] Environmental issues are also affecting consumerconsumption patterns Consumers are constantly changingtheir attitudes behaviors and approaches toward con-sumption [4] )ey have become more aware of environ-mental degradation and of how their consumption behaviorsaffect the level of pollution )us consumersrsquo purchasingpatterns are becoming more environmentally friendly andfor ecologically minded consumers protecting the envi-ronment has become the first priority when purchasingproducts [5]
Supply chain sustainability is a trending topic currentlyowing to growing consumer interest in global sustainabilityEnvironmental damage in supply chains includes toxicwaste water and air pollution biodiversity losses
HindawiMathematical Problems in EngineeringVolume 2020 Article ID 1246536 21 pageshttpsdoiorg10115520201246536
deforestation long-term damage to ecosystems andwasteful energy use Serious awareness of global environ-mental issues and the shift by consumers to environmentallyfriendly consumption patterns are demanding sustainablesupply chain management strategies for many firms insupply chains Accordingly more firms are willing to im-prove the degree of the greenness of supply chains through avariety of green innovation activities such as using cleanenergy during manufacturing processes remanufacturingend-of-life products developing new technologies to reducecarbon emissions and pollutants developing new green andsustainable products and developing new green retailingand marketing techniques One of the main aims whenimplementing these green innovation activities is to mini-mize the impact of environmental damage while enhancingoperational efficiency With consumers now leaning towardsustainable green and organic products as noted abovethey are searching for retail stores who operate using en-vironmentally friendly methods and on green principlesGreening practices are now being implemented in manyindustry fields such as clothing and apparel (EcocentrikApparel Natural Clothing Company and Element Eco-wear) furniture ()e Old Wood Eco Select Furniture andVermont Woods Studios) and household cleaning products(Wunder Budder) Due to the unprecedented popularity ofecofriendly products large traditional retailers such asWalmart and Costco are providing consumers with greenproducts alongside existing nongreen products With regardto supply chain management the logistics and trans-portation sector also requires green and sustainable oper-ations Logistics and transportation together reportedlyconstitute the secondmost prolific sources of greenhouse gasemission [6] )e main concern with respect to logistics isthe impact of pollution on the air roads andor waterVehicle emissions are generally associated with fossil fuelcombustion and particulate emissions from engines Inparticular considerable levels of greenhouse gas emissionsare caused by trucks running empty Because trucks areamong the main sources of pollution many studies of theenvironmental impact of logistics have been driven by theincrease in freight traffic In addition todayrsquos logistics ap-proaches tend to speed up transportation to reduce leadtimes which is also a major cause of the increased levels ofcarbon dioxide Greenhouse gases produced during thetransportation process are considered to be among the maincauses of global warming )erefore many logistics andtransportation companies are devising strategies to reducetheir use of fossil fuels and reduce their carbon emissions byfor instance the introduction of electric vehicles )e lit-erature shows that logistics will be a strategic lever for re-ducing carbon emissions
As such establishing greening strategies as part of asupply chain management plan is an important task for thesustainability and profitability of supply chain members)ekey research questions in this study are as follows
(i) How is competition in the market related to thedegree of greenness of the products and the strategyto reduce carbon emissions
(ii) How are the structures of distribution channels ofgreen and nongreen products related to the prof-itability of the supply chain
(iii) Are consumer preferences for green products re-lated to profits in the supply chain
(iv) Do efforts to reduce carbon emissions affect theprofitability of a supply chain
)e aim of this study is to find the answers to the abovequestions using a game-theoretical framework )e maincontributions of this research with respect to the literatureare threefold First we develop the various game modelsunder various distribution channel structures and suggestthe equilibrium strategy of each game model Second weinvestigate the effects of different parameters on the supplychainrsquos profitability and sustainability Finally through thenumerical experiments we support main findings
)e remainder of this paper is organized as follows InSection 2 we present a review of the relevant literature afterwhich we introduce the five different distribution channelstructures discussed in the paper In Section 3 we review thenotations used and the assumptions Section 4 deals with theequilibrium strategies for each of the five distributionchannel structures Parametric analyses and various nu-merical experiments are conducted and described in Sec-tions 5 and 6 to investigate the impacts of certain parameterson the equilibrium decisions )e last section provides asummary of the paper presents the conclusion and providessome directions for future research
2 Literature Review
In this section we review the relevant literature consideringthree different streams of research in this area green supplychains distribution channel strategies and third-partylogistics
21 Green Supply Chains )e supply chain is an importantbranch of operations management and it has a considerableimpact on the environment through emissions and pollu-tion which affect the health of a community Companies invarious industries are now attempting to minimize theirenvironmental effects by integrating environmental con-cerns into their supply chain operations Applying envi-ronmental issues to supply chain management is referred toas ldquogreen supply chain managementrdquo [7ndash11] Zhang and Liu[12] studied the coordination mechanism in a three-levelgreen supply chain in which product demand correlates withthe degree of greenness of the product Under various gamemodels profits reach their maximal level under cooperativedecision-making while the equilibrium results are far fromsatisfactory in a noncooperative game Zhang et al [13]considered cooperation and noncooperation games with agreen supply chain in which green and nongreen productscoexist and substitute for each other Zhang et al [13]revealed that profitability in the cooperation game is alwaysgreater than that in a noncooperation game Huang andWang [14] surveyed the coordination of a multilevel green
2 Mathematical Problems in Engineering
supply chain through pricing and remanufacturing decisionsand investigated the effects of power and distributionchannel structures on pricing remanufacturing decisionsand profits Madani and Rasti-Barzoki [15] extended thegreen supply chain to the context of government inter-vention In their model the role of a government is to drivesupply chains to produce green and sustainable products Anumerical experiment conducted by Madani and Rasti-Barzoki [15] showed that increases in governmental sub-sidies lead to increases in the demand for and the degree ofgreenness of a product as well as the profits of all supplychain members and the government and decreases in thepollution costs borne by the government Zhu and He [16]investigated green product design issues in supply chainsunder several competition scenarios and asserted that in-creasing greenness competition hurts the equilibriumgreenness of a product while increasing price competitioncan be the driving force to increase the greenness of aproduct Song and Gao [17] applied the concept of revenuesharing to a green supply chain to promote the cooperationof upstream and downstream firms and ultimately realizehigh performance of the green supply chain Song and Gao[17] proved that a revenue-sharing contract enhances thegreening levels of products Jamali and Rasti-Barzoki [18]explored the chain-to-chain competition of a dual-channelsupply chain in which green products are distributedthrough one chain and nongreen products are distributedthrough the other )ey asserted that in order to encourageconsumers to purchase more green products publicawareness of green products should be increased in themarket Heydari et al [19] studied three types (open-triadclosed-triad and transitional-triad) of decision problems inrelation to pricing and greening in a three-echelon dual-channel supply chain and suggested that both the total profitof the supply chain and the green level of the product in theclosed-triad decision structure are the highest among thesethree decision problems Rahmani and Yavari [20] examinedpricing and greening decisions for a dual-channel greensupply chain when the level of market demand is disrupted)ey found that an increased market scale caused by adisruption and lower greening costs are not only beneficialfor the entire supply chain but also increase the greeninglevel of green products Hong and Guo [21] examinedseveral cooperation contracts within a green supply chainand investigated their environmental performance out-comes showing that a two-part tariff contract results in thehighest greenness degree of products and the highest level ofcooperation among supply chain members
22 Distribution Channel Strategy A variety of distributionchannel structures are common in supply chains Manystudies have proven that the profitability of a supply chain isgenerally influenced by its distribution structure McGuireand Staelin [22] found that a decentralized channel can easemarket competition )ey also found that in a state ofequilibrium vertically integrated channels always arisewhereas decentralized channels only occur with highlysubstitutable products Choi [23] discussed a distribution
channel structure consisting of two independent manufac-turers and two common retailers and considered pricecompetition with differentiation of the products and storesfor various decentralized channel structures Choi [23]found that product differentiation helps manufacturerswhereas it hurts retailers Conversely while store differen-tiation helps retailers it hurts manufacturers Moner-Colonques et al [24] examined an asymmetric noncoop-erative game between two manufacturers who decide thenumber of retailers and suggested that when product dif-ferentiation is strong and brand asymmetry is moderate thetwo manufacturers prefer a cross-distribution channel inequilibrium Wu and Mallik [25] extended the work of Choi[23] assuming that channel configurations are determinedendogenously by the Nash equilibrium between the man-ufacturer and the retailers )ey found that manufacturersshould strategically use a cross-distribution channel tomaximize their profits Bian et al [26] dealt with equilibriumchannel strategies with a public firm competing with aprivate firm and found that the equilibrium strategy for thedistribution channel structure in question depends on themarket competition mode (Bertrand or Cournot competi-tion) the form of vertical contract and the degree of productsubstitutability Bian et al [27] studied manufacturersrsquodistribution channel strategies under environmental taxa-tion and suggested that a monopolistic manufacturer canbenefit from a decentralized distribution channel when itstechnology is sufficiently polluting and that two competingmanufacturers are more likely to decentralize the distri-bution channel when their technologies are more envi-ronmentally damaging Nie et al [28] investigated the effectsof a cross online-and-offline channel (OOC) on two com-peting retailersrsquo distribution channel strategies and showedthat such retailers may abandon the OOC strategy when thecross-channel effect is significantly negative Bian et al [29]analyzed the dynamic interactions between manufacturersrsquodistribution channel strategies and incentives for collusion)ey suggested that a single distribution channel does notalways facilitate collusion between manufacturers and heldthat the selection of the distribution channel mainly dependson the discount factor and on the degree of product dif-ferentiation )is paper is related to the literature on dis-tribution channel conflicts and coordination Readers mayrefer to Tsay and Agrawal [30] to review of this stream ofwork
23 ird-Party Logistics )ird-party logistics (3PL) inrelation to supply chain management refers to an organi-zationrsquos use of third-party businesses to outsource elementsof its distribution warehousing and fulfillment services Tofocus on core business development and operations largefirms delegate their logistical and transportation tasks tospecialized 3PL firms to drive operational efficiency Manystudies have proved that a transportation outsourcing ser-vice is beneficial to economies of scale leading to savings incapital investments and reductions of financial risk [31ndash36]However environmental problems become more serious inthe field of logistics management because logistics and
Mathematical Problems in Engineering 3
transportation are the second most common causes of theemission of greenhouse gases such as carbon monoxide andcarbon dioxide )us many researchers have examinedenvironmental problems and their links to 3PL Suzuki [37]developed a truck-scheduling solution which minimizes fuelconsumption and pollutant emissions showing that con-siderable savings in fuel consumption can be realized if thedistance a truck travels with heavy payloads can be mini-mized which can further increase energy efficiency andreduce pollutant emissions De Giovanni and Zaccour [38]studied a two-echelon closed-loop supply chain in which3PL is responsible for collecting used products )eyrevealed that unless 3PL performs better than the retailer themanufacturer never selects 3PL as a means by which tooutsource in reverse logistics Zhu et al [39] established amaximum-capacity model and developed a vehicle-routingprocedure that allows a particular vehicle to use the max-imum-capacity route with a set fuel consumption levelBazan et al [40] investigated different models of greenhousegas emissions from the production and transportation op-erations in a supply chain under amultilevel emission-taxingscheme )ey found that energy usage is the main costcomponent in their research models implying that reducingenergy usage should be prioritized Maiti and Giri [41]surveyed a closed-loop supply chain consisting of a retailer a3PL firm and a manufacturer who operates hybridmanufacturing and a remanufacturing system )eir nu-merical study showed that the 3PL-led decision game per-forms worst Li et al [42] addressed the transportationoutsourcing problems of a supply chain under variouscarbon tax policies and found that a strict carbon tax policyand increasing energy prices can force a manufacturer tooutsource more transportation services to a professional 3PLfirm Jamali and Rasti-Barzoki [43] investigated the effects ofreduced carbon emissions by a 3PL firm on the profitabilityof a three-echelon supply chain and asserted that in order toreduce greenhouse gas emissions 3PL firms should deliverproducts to retailers using green transportation meansConsequently the reduction in carbon emissions by the 3PLfirm increases the demand for green as well as nongreenproducts
24 Research Gaps As discussed above in-depth researchon green supply chains distribution channel structures andthird-party logistics has been conducted over the past fewdecades Moreover the distribution channel structure playsa very important role in determining the profitability of thesupply chain In addition a manufacturerrsquos interest in greenproducts and a 3PL firmrsquos carbon emission reduction effortsare important factors when evaluating the success and ef-ficiency of a supply chain for sustainable growth Howeverto the best of the authorrsquos knowledge no research has dealtwith all of these issues simultaneously Also to the best of theauthorrsquos knowledge the only paper dealing with thegreenness design of a product and 3PL firmsrsquo efforts toreduce carbon emissions is that by Jamali and Rasti-Barzoki[43] )erefore this study focuses on how the ecofriendli-ness of a manufacturer and efforts to reduce carbon
emissions by a 3PL firm affect the profits of supply chainmembers under various distribution channel structures
3 Model Description and Assumptions
31 Notations In this paper we use the notations presentedin Table 1
32 Investigated Supply Chain We consider a green supplychain composed of two manufacturers two retailers andone third-party logistics firm In this supply chain themanufacturers provide consumers with substitutableproducts )e first manufacturer (M1) produces a green(ecofriendly) product while the second manufacturer (M2)produces a nongreen product All products produced by thetwo manufacturers are delivered to and stored by the 3PLfirm When shipping the products to the 3PL firm eachmanufacturer pays tm per unit product)e two retailers (R1and R2) then receive the green and nongreen products fromthe 3PL firm For retailers the unit shipping cost is assumedto be equal to tr Each manufacturer can choose to distributetheir goods through either one retailer or both retailers
)ere is a three-stage game involved in the green supplychain In the first stage of the game M1 determines itswholesale price w1 and the greenness degree g of its greenproduct At the same time M2 sets its wholesale price w2 Byspecifying the values of w1 w2 and g in the second stage3PL determines its carbon emission reduction e Finallybased on all information of other members R1 and R2determine the selling quantities of the manufacturersrsquoproducts q1 and q2 In order to establish a game-theoreticalmodel the following basic assumptions are made
Assumption 1 Each manufacturer can distribute its prod-ucts through a single retailer or through both retailers If amanufacturer chooses to distribute through a single retailerthe channel structure is called a single distribution channelA cross-distribution channel represents the channel struc-ture by which amanufacturer distributes its product throughboth retailers )erefore the following four different dis-tribution channel structures can be defined the single-singlestructure (SS) cross-cross structure (CC) cross-singlestructure (CS) and single-cross structure (SC) One morepossible structure is the case where both retailers cooperatewith each other (CO) In this study we deal with these fivedifferent distribution channel structures (see Figure 1)
Assumption 2 )e demands for the green and nongreenproducts are sensitive to price the degree of greenness andthe amount of carbon emission reduction It is assumed thatthe green and nongreen products show no significant dif-ference in terms of function but vary in terms of price andenvironmental value )e greenness degree of the producthas a positive (negative) impact on M1rsquos (M2rsquos) demandbecause M1 only produces green products Hence the de-mand function of each manufacturer can be expressed asfollows
4 Mathematical Problems in Engineering
q1 α1 minus p1 + βp2 + λ1g + μe
q2 α2 minus p2 + βp1 minus λ2g + μe(1)
In equation (1) we assume that λ1 gt λ2 )e ratio ofpeople interested in buying the green (nongreen) product isλ1 (λ2) If the green products are not available in the marketconsumers are then willing to switch to buying the nongreenproducts )erefore the difference λ1 minus λ2 determines thenumber of consumers who give up buying the nongreenproduct A similar assumption can be found in earlierstudies [15 18 43]
Assumption 3 Cournot competition is an economic modelwhich describes an industry structure in which firmscompete on the selling quantity with decisions made in-dependently of each other and at the same time In thispaper we assume that the two manufacturers compete onselling quantity rather than wholesale price From equation(1) the following retail price functions are derived
p1 q1 q2( 1113857 α1 minus q1 + λ1g + β α2 minus q2 minus λ2g( 1113857 + μe(1 + β)
1 minus β2
p2 q2 q1( 1113857 α2 minus q2 minus λ2g + β α1 minus q1 + λ1g( 1113857 + μe(1 + β)
1 minus β2
(2)
Because each manufacturer can distribute its productthrough different retailers we have qi qii + qij andqi qii + qij where qij is manufacturer irsquos selling quantitydistributed through retailer j
Assumption 4 We assume that the investment in greeningthe product is an increasing and convex function of thegreenness degree of M1rsquos product Hence the greenness costcan be expressed as (cmg22) We also assume that theinvestment in reducing carbon emissions is an increasingand convex function of 3PLrsquos carbon emission reduction)us the carbon abatement investment cost can be given by
Table 1 Notations
Indicesi j Manufacturers and retailers (i j 1 2)
Decision variablese Carbon emission reduction by 3PLg Greenness degree of a productqi Manufacturer irsquos selling quantityqij Manufacturer irsquos selling quantity distributed through retailer j (qi qii + qij)
wi Manufacturer irsquos wholesale priceParametersc3 Cost coefficient of carbon emission reductioncm Cost coefficient of the greenness degreetr Retailerrsquos payment to 3PL per unit of transportationtm Manufacturerrsquos payment to 3PL per unit of transportationαi Potential market demand for manufacturer irsquos productβ Impact of a competitive price on the selling quantity (0lt βlt 1)
λi Impact of the greenness degree of a product on the selling quantityμ Impact of carbon emission reduction by 3PL on the selling quantityFunctionspi Retail price of manufacturer irsquos productπmi Manufacturer irsquos profitπri Retailer irsquos profitπrt Retailersrsquo total profit (πrt πr1 + πr2)
π3 3PLrsquos profitπgsc Supply chain profit (πgsc πm1 + πm2 + πr1 + πr2 + π3)
q1 q2
q2
M1 M2
3PL
q2
R1 R2
(a)
q1
q11 q12
q2
q22q21
M1 M2
3PL
R1 R2
(b)
q11 q12
q1 q2
q2
M1 M2
3PL
R1 R2
(c)
q1
q1
q2
q22q21
M1 M2
3PL
R1 R2
(d)
q1 q2
M1 M2
3PL
R1 R2
(e)
Figure 1 Five distribution channel structures (a) SS structure (b) CC structure (c) CS structure (d) SC structure (e) CO structure
Mathematical Problems in Engineering 5
(c3e22) Similar assumptions were made in earlier studies
[44ndash46]
Assumption 5 To focus on the effect of distribution channelthe two manufacturersrsquo production costs are assumed to beconstant and normalized to zero Similarly the retailersrsquooperational costs are also normalized to zero Allowingnonzero production and operational costs will not quali-tatively change our results We also assume that consumersin the market must visit the traditional brick-and-mortarretailers to purchase the product therefore the shippingcosts between consumers and retailers are ignored here
4 Analysis
In this section we analyze each possible distribution channelstructure and then present the equilibrium results on theselling quantity the greenness degree and the carbonemission reduction
41 SS Structure Both M1 and M2 Adopt Single DistributionChannel First we discuss the SS structure in which M1rsquos(M2rsquos) product is exclusively distributed through R1 (R2)(Figure 1(a)) )e profit function of each member in thegreen supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q1
πr2 p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(3)
Proposition 1 Let qSSi eSS gSS and wSSi denote the selling
quantity of product i the carbon emission reduction thegreenness degree and the wholesale price of product i in the SSdistribution channel structure respectively If the condition4cm(1 minus β2)(4 minus β2)gtA2
3 is met the optimal decisions are canbe determined as follows
qSS1
A1 + gSSA3 + 1 minus β21113872 1113873 βwSS2 minus 2wSS
1( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4a)
qSS2
A2 + gSSA4 + 1 minus β21113872 1113873 βwSS1 minus 2wSS
2( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4b)
eSS
2μ(1 + β) tm + tr( 1113857
c3(2 + β) (4c)
gSS
A3 1 minus β21113872 1113873 4A5 + βA6 minus tm 16 minus β21113872 11138731113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857 (4d)
wSS1 tm +
cmgSS 4 minus β21113872 1113873
A3 (4e)
wSS2
14
βwSS1 +
gSSA4
1 minus β2+ A61113888 1113889 (4f)
e values of A1 to A7 are given in Appendix
Proof )e decision sequence in the case of the SS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq1
πr1
maxq2
πr2 (5)
To solve the decision problem in equation (5) we usebackward induction Given the values of other membersrsquodecision variables we initially maximize the retailersrsquoprofits From the fact that (z2πrizq2i ) minus (2(1 minus β2))lt 0for i 1 2 the profit function of each retailer is strictlyconcave with respect to (wrt) its own selling quantity)us solving the first-order conditions (FOCs) of theretailers yields equations (4a) and (4b) Substituting theminto the 3PLrsquos profit function the second-order condition(SOC) of the 3PLrsquos problem is given by(z2π3ze2) minus c3 lt 0 From the 3PLrsquos FOC we haveequation (4c) Integrating equations (4a)ndash(4c) into theprofit functions of the manufacturers we can obtain M1rsquosHessian matrix as follows
HSSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 1 minus β21113872 1113873
4 minus β2A3
4 minus β2
A3
4 minus β2minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(6)
We define ΔSSk as the leading principal minor of order k
in HSSm1 We then find that ΔSS1 lt 0 If we assume that
4cm(1 minus β2)(4 minus β2)gtA23 Δ
SS2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because(z2πm2zw2
2) minus 4((1 minus β2)(4 minus β2))lt 0 By solving theFOCs of manufacturersrsquo problem all members in the greensupply chain can find their own equilibrium strategies inequations (4a)ndash(4f) )is completes the proof
42 CC Structure Both M1 andM2 Adopt Cross-DistributionChannel Next we analyze the CC structure in which eachmanufacturer distributes via both retailers (Figure 1(b))Recall that in the case of the CC structure qi qii + qij fori 1 2 and because each manufacturer can distribute itsproduct through different retailers )us the profit functionof each member in the green supply chain is given as
6 Mathematical Problems in Engineering
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q11 + p2 minus w2 minus tr( 1113857q21
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q11 + q12 + q21 + q22( 1113857 minusc3e
2
2
(7)
Proposition 2 Let qCCij eCC gCC and wCCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and thewholesale price of product i in the CC distribution channelstructure If the condition 3cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qCC11 q
CC12
B1 + λ1gCC minus wCC1 + βwCC
2 + μeCC
3 (8a)
qCC21 q
CC22
B2 minus λ2gCC + βwCC1 minus wCC
2 + μeCC
3 (8b)
eCC
4μ tm + tr( 1113857
3c3 (8c)
gCC
2λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCC( 1113857( 1113857
3cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857 (8d)
wCC1 tm +
3cmgCC
2λ1 (8e)
wCC2
βwCC1 minus λ2gCC + μeCC + tm + B2
2 (8f)
e values of B1 and B2 are given in Appendix
Proof )e decision sequence in the case of the CC structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11 q21
πr1
maxq12 q22
πr2 (9)
Given the values of other membersrsquo decision variablesfirst we maximize retailersrsquo profits Let HCC
ri denote theHessian matrix of retailer irsquos profit maximization problem)en we have
HCCri
z2πri
zq2ii
z2πri
zqiizqji
z2πri
zqjizqii
z2πri
zqji2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(10)
We define ΞCCk as the leading principal minor of order k
in HCCri We then find that ΞCC1 lt 0 and ΞCC2 (4
(1 minus β2))gt 0 )us the profit function of retailer i is strictlyconcave wrt its own selling quantities Accordingly solvingthe FOCs of the retailersrsquo problems yields equations (8a) and(8b) Substituting them into the 3PLrsquos profit function theSOC of the 3PLrsquos problem is determined by (z2π3ze2)
minus c3 lt 0 From the 3PLrsquos FOC we have (8c) Integratingequations (8a) to (8c) into the profit functions of the man-ufacturers we can obtain M1rsquos Hessian matrix as follows
HCCm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus43
2λ13
2λ13
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(11)
We define ΔCCk as the leading principal minor of order k
in HCCm1 We then find that ΔCC1 lt 0 Assuming that 3cm gt λ
21
we haveΔCC2 gt 0 implying thatM1rsquos profit function is strictlyconcave wrt w1 and g M2rsquos profit function is also strictlyconcave wrt w2 because the SOC of M2rsquos problem is givenby (z2πm2zw2
2) minus (43)lt 0 By solving the FOCs of themanufacturersrsquo problem all members in the green supplychain can find their own equilibrium strategies via equations(8a)ndash(8f) )is completes the proof
Note that from equations (7) (8a) and (8b) we haveπr1 πr2 in the CC structure
43 CS Structure M1 Adopts Cross-Distribution Channelwhile M2 Adopts Single Distribution Channel In the case ofthe CS structure M1 distributes its green products throughboth R1 and R2 while M2 distributes its nongreen productsonly through R2 (Figure 1(c)) Because green products aredistributed through both retailers we have q1 q11 + q12)us the profit function of each member in the green supplychain is given as
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q11
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q11 + q12 + q2( 1113857 minusc3e
2
2
(12)
Proposition 3 Let qCSij eCS gCS and wCSi denote corre-
spondingly the selling quantity of product i via retailer jthe carbon emission reduction the greenness degree andthe wholesale price of product i in the CS distributionchannel structure If the condition 12cm(4 minus β2)gt(4λ1 minus βλ2)
2 is met the optimal decisions are can be de-termined as follows
Mathematical Problems in Engineering 7
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
deforestation long-term damage to ecosystems andwasteful energy use Serious awareness of global environ-mental issues and the shift by consumers to environmentallyfriendly consumption patterns are demanding sustainablesupply chain management strategies for many firms insupply chains Accordingly more firms are willing to im-prove the degree of the greenness of supply chains through avariety of green innovation activities such as using cleanenergy during manufacturing processes remanufacturingend-of-life products developing new technologies to reducecarbon emissions and pollutants developing new green andsustainable products and developing new green retailingand marketing techniques One of the main aims whenimplementing these green innovation activities is to mini-mize the impact of environmental damage while enhancingoperational efficiency With consumers now leaning towardsustainable green and organic products as noted abovethey are searching for retail stores who operate using en-vironmentally friendly methods and on green principlesGreening practices are now being implemented in manyindustry fields such as clothing and apparel (EcocentrikApparel Natural Clothing Company and Element Eco-wear) furniture ()e Old Wood Eco Select Furniture andVermont Woods Studios) and household cleaning products(Wunder Budder) Due to the unprecedented popularity ofecofriendly products large traditional retailers such asWalmart and Costco are providing consumers with greenproducts alongside existing nongreen products With regardto supply chain management the logistics and trans-portation sector also requires green and sustainable oper-ations Logistics and transportation together reportedlyconstitute the secondmost prolific sources of greenhouse gasemission [6] )e main concern with respect to logistics isthe impact of pollution on the air roads andor waterVehicle emissions are generally associated with fossil fuelcombustion and particulate emissions from engines Inparticular considerable levels of greenhouse gas emissionsare caused by trucks running empty Because trucks areamong the main sources of pollution many studies of theenvironmental impact of logistics have been driven by theincrease in freight traffic In addition todayrsquos logistics ap-proaches tend to speed up transportation to reduce leadtimes which is also a major cause of the increased levels ofcarbon dioxide Greenhouse gases produced during thetransportation process are considered to be among the maincauses of global warming )erefore many logistics andtransportation companies are devising strategies to reducetheir use of fossil fuels and reduce their carbon emissions byfor instance the introduction of electric vehicles )e lit-erature shows that logistics will be a strategic lever for re-ducing carbon emissions
As such establishing greening strategies as part of asupply chain management plan is an important task for thesustainability and profitability of supply chain members)ekey research questions in this study are as follows
(i) How is competition in the market related to thedegree of greenness of the products and the strategyto reduce carbon emissions
(ii) How are the structures of distribution channels ofgreen and nongreen products related to the prof-itability of the supply chain
(iii) Are consumer preferences for green products re-lated to profits in the supply chain
(iv) Do efforts to reduce carbon emissions affect theprofitability of a supply chain
)e aim of this study is to find the answers to the abovequestions using a game-theoretical framework )e maincontributions of this research with respect to the literatureare threefold First we develop the various game modelsunder various distribution channel structures and suggestthe equilibrium strategy of each game model Second weinvestigate the effects of different parameters on the supplychainrsquos profitability and sustainability Finally through thenumerical experiments we support main findings
)e remainder of this paper is organized as follows InSection 2 we present a review of the relevant literature afterwhich we introduce the five different distribution channelstructures discussed in the paper In Section 3 we review thenotations used and the assumptions Section 4 deals with theequilibrium strategies for each of the five distributionchannel structures Parametric analyses and various nu-merical experiments are conducted and described in Sec-tions 5 and 6 to investigate the impacts of certain parameterson the equilibrium decisions )e last section provides asummary of the paper presents the conclusion and providessome directions for future research
2 Literature Review
In this section we review the relevant literature consideringthree different streams of research in this area green supplychains distribution channel strategies and third-partylogistics
21 Green Supply Chains )e supply chain is an importantbranch of operations management and it has a considerableimpact on the environment through emissions and pollu-tion which affect the health of a community Companies invarious industries are now attempting to minimize theirenvironmental effects by integrating environmental con-cerns into their supply chain operations Applying envi-ronmental issues to supply chain management is referred toas ldquogreen supply chain managementrdquo [7ndash11] Zhang and Liu[12] studied the coordination mechanism in a three-levelgreen supply chain in which product demand correlates withthe degree of greenness of the product Under various gamemodels profits reach their maximal level under cooperativedecision-making while the equilibrium results are far fromsatisfactory in a noncooperative game Zhang et al [13]considered cooperation and noncooperation games with agreen supply chain in which green and nongreen productscoexist and substitute for each other Zhang et al [13]revealed that profitability in the cooperation game is alwaysgreater than that in a noncooperation game Huang andWang [14] surveyed the coordination of a multilevel green
2 Mathematical Problems in Engineering
supply chain through pricing and remanufacturing decisionsand investigated the effects of power and distributionchannel structures on pricing remanufacturing decisionsand profits Madani and Rasti-Barzoki [15] extended thegreen supply chain to the context of government inter-vention In their model the role of a government is to drivesupply chains to produce green and sustainable products Anumerical experiment conducted by Madani and Rasti-Barzoki [15] showed that increases in governmental sub-sidies lead to increases in the demand for and the degree ofgreenness of a product as well as the profits of all supplychain members and the government and decreases in thepollution costs borne by the government Zhu and He [16]investigated green product design issues in supply chainsunder several competition scenarios and asserted that in-creasing greenness competition hurts the equilibriumgreenness of a product while increasing price competitioncan be the driving force to increase the greenness of aproduct Song and Gao [17] applied the concept of revenuesharing to a green supply chain to promote the cooperationof upstream and downstream firms and ultimately realizehigh performance of the green supply chain Song and Gao[17] proved that a revenue-sharing contract enhances thegreening levels of products Jamali and Rasti-Barzoki [18]explored the chain-to-chain competition of a dual-channelsupply chain in which green products are distributedthrough one chain and nongreen products are distributedthrough the other )ey asserted that in order to encourageconsumers to purchase more green products publicawareness of green products should be increased in themarket Heydari et al [19] studied three types (open-triadclosed-triad and transitional-triad) of decision problems inrelation to pricing and greening in a three-echelon dual-channel supply chain and suggested that both the total profitof the supply chain and the green level of the product in theclosed-triad decision structure are the highest among thesethree decision problems Rahmani and Yavari [20] examinedpricing and greening decisions for a dual-channel greensupply chain when the level of market demand is disrupted)ey found that an increased market scale caused by adisruption and lower greening costs are not only beneficialfor the entire supply chain but also increase the greeninglevel of green products Hong and Guo [21] examinedseveral cooperation contracts within a green supply chainand investigated their environmental performance out-comes showing that a two-part tariff contract results in thehighest greenness degree of products and the highest level ofcooperation among supply chain members
22 Distribution Channel Strategy A variety of distributionchannel structures are common in supply chains Manystudies have proven that the profitability of a supply chain isgenerally influenced by its distribution structure McGuireand Staelin [22] found that a decentralized channel can easemarket competition )ey also found that in a state ofequilibrium vertically integrated channels always arisewhereas decentralized channels only occur with highlysubstitutable products Choi [23] discussed a distribution
channel structure consisting of two independent manufac-turers and two common retailers and considered pricecompetition with differentiation of the products and storesfor various decentralized channel structures Choi [23]found that product differentiation helps manufacturerswhereas it hurts retailers Conversely while store differen-tiation helps retailers it hurts manufacturers Moner-Colonques et al [24] examined an asymmetric noncoop-erative game between two manufacturers who decide thenumber of retailers and suggested that when product dif-ferentiation is strong and brand asymmetry is moderate thetwo manufacturers prefer a cross-distribution channel inequilibrium Wu and Mallik [25] extended the work of Choi[23] assuming that channel configurations are determinedendogenously by the Nash equilibrium between the man-ufacturer and the retailers )ey found that manufacturersshould strategically use a cross-distribution channel tomaximize their profits Bian et al [26] dealt with equilibriumchannel strategies with a public firm competing with aprivate firm and found that the equilibrium strategy for thedistribution channel structure in question depends on themarket competition mode (Bertrand or Cournot competi-tion) the form of vertical contract and the degree of productsubstitutability Bian et al [27] studied manufacturersrsquodistribution channel strategies under environmental taxa-tion and suggested that a monopolistic manufacturer canbenefit from a decentralized distribution channel when itstechnology is sufficiently polluting and that two competingmanufacturers are more likely to decentralize the distri-bution channel when their technologies are more envi-ronmentally damaging Nie et al [28] investigated the effectsof a cross online-and-offline channel (OOC) on two com-peting retailersrsquo distribution channel strategies and showedthat such retailers may abandon the OOC strategy when thecross-channel effect is significantly negative Bian et al [29]analyzed the dynamic interactions between manufacturersrsquodistribution channel strategies and incentives for collusion)ey suggested that a single distribution channel does notalways facilitate collusion between manufacturers and heldthat the selection of the distribution channel mainly dependson the discount factor and on the degree of product dif-ferentiation )is paper is related to the literature on dis-tribution channel conflicts and coordination Readers mayrefer to Tsay and Agrawal [30] to review of this stream ofwork
23 ird-Party Logistics )ird-party logistics (3PL) inrelation to supply chain management refers to an organi-zationrsquos use of third-party businesses to outsource elementsof its distribution warehousing and fulfillment services Tofocus on core business development and operations largefirms delegate their logistical and transportation tasks tospecialized 3PL firms to drive operational efficiency Manystudies have proved that a transportation outsourcing ser-vice is beneficial to economies of scale leading to savings incapital investments and reductions of financial risk [31ndash36]However environmental problems become more serious inthe field of logistics management because logistics and
Mathematical Problems in Engineering 3
transportation are the second most common causes of theemission of greenhouse gases such as carbon monoxide andcarbon dioxide )us many researchers have examinedenvironmental problems and their links to 3PL Suzuki [37]developed a truck-scheduling solution which minimizes fuelconsumption and pollutant emissions showing that con-siderable savings in fuel consumption can be realized if thedistance a truck travels with heavy payloads can be mini-mized which can further increase energy efficiency andreduce pollutant emissions De Giovanni and Zaccour [38]studied a two-echelon closed-loop supply chain in which3PL is responsible for collecting used products )eyrevealed that unless 3PL performs better than the retailer themanufacturer never selects 3PL as a means by which tooutsource in reverse logistics Zhu et al [39] established amaximum-capacity model and developed a vehicle-routingprocedure that allows a particular vehicle to use the max-imum-capacity route with a set fuel consumption levelBazan et al [40] investigated different models of greenhousegas emissions from the production and transportation op-erations in a supply chain under amultilevel emission-taxingscheme )ey found that energy usage is the main costcomponent in their research models implying that reducingenergy usage should be prioritized Maiti and Giri [41]surveyed a closed-loop supply chain consisting of a retailer a3PL firm and a manufacturer who operates hybridmanufacturing and a remanufacturing system )eir nu-merical study showed that the 3PL-led decision game per-forms worst Li et al [42] addressed the transportationoutsourcing problems of a supply chain under variouscarbon tax policies and found that a strict carbon tax policyand increasing energy prices can force a manufacturer tooutsource more transportation services to a professional 3PLfirm Jamali and Rasti-Barzoki [43] investigated the effects ofreduced carbon emissions by a 3PL firm on the profitabilityof a three-echelon supply chain and asserted that in order toreduce greenhouse gas emissions 3PL firms should deliverproducts to retailers using green transportation meansConsequently the reduction in carbon emissions by the 3PLfirm increases the demand for green as well as nongreenproducts
24 Research Gaps As discussed above in-depth researchon green supply chains distribution channel structures andthird-party logistics has been conducted over the past fewdecades Moreover the distribution channel structure playsa very important role in determining the profitability of thesupply chain In addition a manufacturerrsquos interest in greenproducts and a 3PL firmrsquos carbon emission reduction effortsare important factors when evaluating the success and ef-ficiency of a supply chain for sustainable growth Howeverto the best of the authorrsquos knowledge no research has dealtwith all of these issues simultaneously Also to the best of theauthorrsquos knowledge the only paper dealing with thegreenness design of a product and 3PL firmsrsquo efforts toreduce carbon emissions is that by Jamali and Rasti-Barzoki[43] )erefore this study focuses on how the ecofriendli-ness of a manufacturer and efforts to reduce carbon
emissions by a 3PL firm affect the profits of supply chainmembers under various distribution channel structures
3 Model Description and Assumptions
31 Notations In this paper we use the notations presentedin Table 1
32 Investigated Supply Chain We consider a green supplychain composed of two manufacturers two retailers andone third-party logistics firm In this supply chain themanufacturers provide consumers with substitutableproducts )e first manufacturer (M1) produces a green(ecofriendly) product while the second manufacturer (M2)produces a nongreen product All products produced by thetwo manufacturers are delivered to and stored by the 3PLfirm When shipping the products to the 3PL firm eachmanufacturer pays tm per unit product)e two retailers (R1and R2) then receive the green and nongreen products fromthe 3PL firm For retailers the unit shipping cost is assumedto be equal to tr Each manufacturer can choose to distributetheir goods through either one retailer or both retailers
)ere is a three-stage game involved in the green supplychain In the first stage of the game M1 determines itswholesale price w1 and the greenness degree g of its greenproduct At the same time M2 sets its wholesale price w2 Byspecifying the values of w1 w2 and g in the second stage3PL determines its carbon emission reduction e Finallybased on all information of other members R1 and R2determine the selling quantities of the manufacturersrsquoproducts q1 and q2 In order to establish a game-theoreticalmodel the following basic assumptions are made
Assumption 1 Each manufacturer can distribute its prod-ucts through a single retailer or through both retailers If amanufacturer chooses to distribute through a single retailerthe channel structure is called a single distribution channelA cross-distribution channel represents the channel struc-ture by which amanufacturer distributes its product throughboth retailers )erefore the following four different dis-tribution channel structures can be defined the single-singlestructure (SS) cross-cross structure (CC) cross-singlestructure (CS) and single-cross structure (SC) One morepossible structure is the case where both retailers cooperatewith each other (CO) In this study we deal with these fivedifferent distribution channel structures (see Figure 1)
Assumption 2 )e demands for the green and nongreenproducts are sensitive to price the degree of greenness andthe amount of carbon emission reduction It is assumed thatthe green and nongreen products show no significant dif-ference in terms of function but vary in terms of price andenvironmental value )e greenness degree of the producthas a positive (negative) impact on M1rsquos (M2rsquos) demandbecause M1 only produces green products Hence the de-mand function of each manufacturer can be expressed asfollows
4 Mathematical Problems in Engineering
q1 α1 minus p1 + βp2 + λ1g + μe
q2 α2 minus p2 + βp1 minus λ2g + μe(1)
In equation (1) we assume that λ1 gt λ2 )e ratio ofpeople interested in buying the green (nongreen) product isλ1 (λ2) If the green products are not available in the marketconsumers are then willing to switch to buying the nongreenproducts )erefore the difference λ1 minus λ2 determines thenumber of consumers who give up buying the nongreenproduct A similar assumption can be found in earlierstudies [15 18 43]
Assumption 3 Cournot competition is an economic modelwhich describes an industry structure in which firmscompete on the selling quantity with decisions made in-dependently of each other and at the same time In thispaper we assume that the two manufacturers compete onselling quantity rather than wholesale price From equation(1) the following retail price functions are derived
p1 q1 q2( 1113857 α1 minus q1 + λ1g + β α2 minus q2 minus λ2g( 1113857 + μe(1 + β)
1 minus β2
p2 q2 q1( 1113857 α2 minus q2 minus λ2g + β α1 minus q1 + λ1g( 1113857 + μe(1 + β)
1 minus β2
(2)
Because each manufacturer can distribute its productthrough different retailers we have qi qii + qij andqi qii + qij where qij is manufacturer irsquos selling quantitydistributed through retailer j
Assumption 4 We assume that the investment in greeningthe product is an increasing and convex function of thegreenness degree of M1rsquos product Hence the greenness costcan be expressed as (cmg22) We also assume that theinvestment in reducing carbon emissions is an increasingand convex function of 3PLrsquos carbon emission reduction)us the carbon abatement investment cost can be given by
Table 1 Notations
Indicesi j Manufacturers and retailers (i j 1 2)
Decision variablese Carbon emission reduction by 3PLg Greenness degree of a productqi Manufacturer irsquos selling quantityqij Manufacturer irsquos selling quantity distributed through retailer j (qi qii + qij)
wi Manufacturer irsquos wholesale priceParametersc3 Cost coefficient of carbon emission reductioncm Cost coefficient of the greenness degreetr Retailerrsquos payment to 3PL per unit of transportationtm Manufacturerrsquos payment to 3PL per unit of transportationαi Potential market demand for manufacturer irsquos productβ Impact of a competitive price on the selling quantity (0lt βlt 1)
λi Impact of the greenness degree of a product on the selling quantityμ Impact of carbon emission reduction by 3PL on the selling quantityFunctionspi Retail price of manufacturer irsquos productπmi Manufacturer irsquos profitπri Retailer irsquos profitπrt Retailersrsquo total profit (πrt πr1 + πr2)
π3 3PLrsquos profitπgsc Supply chain profit (πgsc πm1 + πm2 + πr1 + πr2 + π3)
q1 q2
q2
M1 M2
3PL
q2
R1 R2
(a)
q1
q11 q12
q2
q22q21
M1 M2
3PL
R1 R2
(b)
q11 q12
q1 q2
q2
M1 M2
3PL
R1 R2
(c)
q1
q1
q2
q22q21
M1 M2
3PL
R1 R2
(d)
q1 q2
M1 M2
3PL
R1 R2
(e)
Figure 1 Five distribution channel structures (a) SS structure (b) CC structure (c) CS structure (d) SC structure (e) CO structure
Mathematical Problems in Engineering 5
(c3e22) Similar assumptions were made in earlier studies
[44ndash46]
Assumption 5 To focus on the effect of distribution channelthe two manufacturersrsquo production costs are assumed to beconstant and normalized to zero Similarly the retailersrsquooperational costs are also normalized to zero Allowingnonzero production and operational costs will not quali-tatively change our results We also assume that consumersin the market must visit the traditional brick-and-mortarretailers to purchase the product therefore the shippingcosts between consumers and retailers are ignored here
4 Analysis
In this section we analyze each possible distribution channelstructure and then present the equilibrium results on theselling quantity the greenness degree and the carbonemission reduction
41 SS Structure Both M1 and M2 Adopt Single DistributionChannel First we discuss the SS structure in which M1rsquos(M2rsquos) product is exclusively distributed through R1 (R2)(Figure 1(a)) )e profit function of each member in thegreen supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q1
πr2 p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(3)
Proposition 1 Let qSSi eSS gSS and wSSi denote the selling
quantity of product i the carbon emission reduction thegreenness degree and the wholesale price of product i in the SSdistribution channel structure respectively If the condition4cm(1 minus β2)(4 minus β2)gtA2
3 is met the optimal decisions are canbe determined as follows
qSS1
A1 + gSSA3 + 1 minus β21113872 1113873 βwSS2 minus 2wSS
1( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4a)
qSS2
A2 + gSSA4 + 1 minus β21113872 1113873 βwSS1 minus 2wSS
2( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4b)
eSS
2μ(1 + β) tm + tr( 1113857
c3(2 + β) (4c)
gSS
A3 1 minus β21113872 1113873 4A5 + βA6 minus tm 16 minus β21113872 11138731113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857 (4d)
wSS1 tm +
cmgSS 4 minus β21113872 1113873
A3 (4e)
wSS2
14
βwSS1 +
gSSA4
1 minus β2+ A61113888 1113889 (4f)
e values of A1 to A7 are given in Appendix
Proof )e decision sequence in the case of the SS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq1
πr1
maxq2
πr2 (5)
To solve the decision problem in equation (5) we usebackward induction Given the values of other membersrsquodecision variables we initially maximize the retailersrsquoprofits From the fact that (z2πrizq2i ) minus (2(1 minus β2))lt 0for i 1 2 the profit function of each retailer is strictlyconcave with respect to (wrt) its own selling quantity)us solving the first-order conditions (FOCs) of theretailers yields equations (4a) and (4b) Substituting theminto the 3PLrsquos profit function the second-order condition(SOC) of the 3PLrsquos problem is given by(z2π3ze2) minus c3 lt 0 From the 3PLrsquos FOC we haveequation (4c) Integrating equations (4a)ndash(4c) into theprofit functions of the manufacturers we can obtain M1rsquosHessian matrix as follows
HSSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 1 minus β21113872 1113873
4 minus β2A3
4 minus β2
A3
4 minus β2minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(6)
We define ΔSSk as the leading principal minor of order k
in HSSm1 We then find that ΔSS1 lt 0 If we assume that
4cm(1 minus β2)(4 minus β2)gtA23 Δ
SS2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because(z2πm2zw2
2) minus 4((1 minus β2)(4 minus β2))lt 0 By solving theFOCs of manufacturersrsquo problem all members in the greensupply chain can find their own equilibrium strategies inequations (4a)ndash(4f) )is completes the proof
42 CC Structure Both M1 andM2 Adopt Cross-DistributionChannel Next we analyze the CC structure in which eachmanufacturer distributes via both retailers (Figure 1(b))Recall that in the case of the CC structure qi qii + qij fori 1 2 and because each manufacturer can distribute itsproduct through different retailers )us the profit functionof each member in the green supply chain is given as
6 Mathematical Problems in Engineering
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q11 + p2 minus w2 minus tr( 1113857q21
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q11 + q12 + q21 + q22( 1113857 minusc3e
2
2
(7)
Proposition 2 Let qCCij eCC gCC and wCCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and thewholesale price of product i in the CC distribution channelstructure If the condition 3cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qCC11 q
CC12
B1 + λ1gCC minus wCC1 + βwCC
2 + μeCC
3 (8a)
qCC21 q
CC22
B2 minus λ2gCC + βwCC1 minus wCC
2 + μeCC
3 (8b)
eCC
4μ tm + tr( 1113857
3c3 (8c)
gCC
2λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCC( 1113857( 1113857
3cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857 (8d)
wCC1 tm +
3cmgCC
2λ1 (8e)
wCC2
βwCC1 minus λ2gCC + μeCC + tm + B2
2 (8f)
e values of B1 and B2 are given in Appendix
Proof )e decision sequence in the case of the CC structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11 q21
πr1
maxq12 q22
πr2 (9)
Given the values of other membersrsquo decision variablesfirst we maximize retailersrsquo profits Let HCC
ri denote theHessian matrix of retailer irsquos profit maximization problem)en we have
HCCri
z2πri
zq2ii
z2πri
zqiizqji
z2πri
zqjizqii
z2πri
zqji2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(10)
We define ΞCCk as the leading principal minor of order k
in HCCri We then find that ΞCC1 lt 0 and ΞCC2 (4
(1 minus β2))gt 0 )us the profit function of retailer i is strictlyconcave wrt its own selling quantities Accordingly solvingthe FOCs of the retailersrsquo problems yields equations (8a) and(8b) Substituting them into the 3PLrsquos profit function theSOC of the 3PLrsquos problem is determined by (z2π3ze2)
minus c3 lt 0 From the 3PLrsquos FOC we have (8c) Integratingequations (8a) to (8c) into the profit functions of the man-ufacturers we can obtain M1rsquos Hessian matrix as follows
HCCm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus43
2λ13
2λ13
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(11)
We define ΔCCk as the leading principal minor of order k
in HCCm1 We then find that ΔCC1 lt 0 Assuming that 3cm gt λ
21
we haveΔCC2 gt 0 implying thatM1rsquos profit function is strictlyconcave wrt w1 and g M2rsquos profit function is also strictlyconcave wrt w2 because the SOC of M2rsquos problem is givenby (z2πm2zw2
2) minus (43)lt 0 By solving the FOCs of themanufacturersrsquo problem all members in the green supplychain can find their own equilibrium strategies via equations(8a)ndash(8f) )is completes the proof
Note that from equations (7) (8a) and (8b) we haveπr1 πr2 in the CC structure
43 CS Structure M1 Adopts Cross-Distribution Channelwhile M2 Adopts Single Distribution Channel In the case ofthe CS structure M1 distributes its green products throughboth R1 and R2 while M2 distributes its nongreen productsonly through R2 (Figure 1(c)) Because green products aredistributed through both retailers we have q1 q11 + q12)us the profit function of each member in the green supplychain is given as
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q11
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q11 + q12 + q2( 1113857 minusc3e
2
2
(12)
Proposition 3 Let qCSij eCS gCS and wCSi denote corre-
spondingly the selling quantity of product i via retailer jthe carbon emission reduction the greenness degree andthe wholesale price of product i in the CS distributionchannel structure If the condition 12cm(4 minus β2)gt(4λ1 minus βλ2)
2 is met the optimal decisions are can be de-termined as follows
Mathematical Problems in Engineering 7
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
supply chain through pricing and remanufacturing decisionsand investigated the effects of power and distributionchannel structures on pricing remanufacturing decisionsand profits Madani and Rasti-Barzoki [15] extended thegreen supply chain to the context of government inter-vention In their model the role of a government is to drivesupply chains to produce green and sustainable products Anumerical experiment conducted by Madani and Rasti-Barzoki [15] showed that increases in governmental sub-sidies lead to increases in the demand for and the degree ofgreenness of a product as well as the profits of all supplychain members and the government and decreases in thepollution costs borne by the government Zhu and He [16]investigated green product design issues in supply chainsunder several competition scenarios and asserted that in-creasing greenness competition hurts the equilibriumgreenness of a product while increasing price competitioncan be the driving force to increase the greenness of aproduct Song and Gao [17] applied the concept of revenuesharing to a green supply chain to promote the cooperationof upstream and downstream firms and ultimately realizehigh performance of the green supply chain Song and Gao[17] proved that a revenue-sharing contract enhances thegreening levels of products Jamali and Rasti-Barzoki [18]explored the chain-to-chain competition of a dual-channelsupply chain in which green products are distributedthrough one chain and nongreen products are distributedthrough the other )ey asserted that in order to encourageconsumers to purchase more green products publicawareness of green products should be increased in themarket Heydari et al [19] studied three types (open-triadclosed-triad and transitional-triad) of decision problems inrelation to pricing and greening in a three-echelon dual-channel supply chain and suggested that both the total profitof the supply chain and the green level of the product in theclosed-triad decision structure are the highest among thesethree decision problems Rahmani and Yavari [20] examinedpricing and greening decisions for a dual-channel greensupply chain when the level of market demand is disrupted)ey found that an increased market scale caused by adisruption and lower greening costs are not only beneficialfor the entire supply chain but also increase the greeninglevel of green products Hong and Guo [21] examinedseveral cooperation contracts within a green supply chainand investigated their environmental performance out-comes showing that a two-part tariff contract results in thehighest greenness degree of products and the highest level ofcooperation among supply chain members
22 Distribution Channel Strategy A variety of distributionchannel structures are common in supply chains Manystudies have proven that the profitability of a supply chain isgenerally influenced by its distribution structure McGuireand Staelin [22] found that a decentralized channel can easemarket competition )ey also found that in a state ofequilibrium vertically integrated channels always arisewhereas decentralized channels only occur with highlysubstitutable products Choi [23] discussed a distribution
channel structure consisting of two independent manufac-turers and two common retailers and considered pricecompetition with differentiation of the products and storesfor various decentralized channel structures Choi [23]found that product differentiation helps manufacturerswhereas it hurts retailers Conversely while store differen-tiation helps retailers it hurts manufacturers Moner-Colonques et al [24] examined an asymmetric noncoop-erative game between two manufacturers who decide thenumber of retailers and suggested that when product dif-ferentiation is strong and brand asymmetry is moderate thetwo manufacturers prefer a cross-distribution channel inequilibrium Wu and Mallik [25] extended the work of Choi[23] assuming that channel configurations are determinedendogenously by the Nash equilibrium between the man-ufacturer and the retailers )ey found that manufacturersshould strategically use a cross-distribution channel tomaximize their profits Bian et al [26] dealt with equilibriumchannel strategies with a public firm competing with aprivate firm and found that the equilibrium strategy for thedistribution channel structure in question depends on themarket competition mode (Bertrand or Cournot competi-tion) the form of vertical contract and the degree of productsubstitutability Bian et al [27] studied manufacturersrsquodistribution channel strategies under environmental taxa-tion and suggested that a monopolistic manufacturer canbenefit from a decentralized distribution channel when itstechnology is sufficiently polluting and that two competingmanufacturers are more likely to decentralize the distri-bution channel when their technologies are more envi-ronmentally damaging Nie et al [28] investigated the effectsof a cross online-and-offline channel (OOC) on two com-peting retailersrsquo distribution channel strategies and showedthat such retailers may abandon the OOC strategy when thecross-channel effect is significantly negative Bian et al [29]analyzed the dynamic interactions between manufacturersrsquodistribution channel strategies and incentives for collusion)ey suggested that a single distribution channel does notalways facilitate collusion between manufacturers and heldthat the selection of the distribution channel mainly dependson the discount factor and on the degree of product dif-ferentiation )is paper is related to the literature on dis-tribution channel conflicts and coordination Readers mayrefer to Tsay and Agrawal [30] to review of this stream ofwork
23 ird-Party Logistics )ird-party logistics (3PL) inrelation to supply chain management refers to an organi-zationrsquos use of third-party businesses to outsource elementsof its distribution warehousing and fulfillment services Tofocus on core business development and operations largefirms delegate their logistical and transportation tasks tospecialized 3PL firms to drive operational efficiency Manystudies have proved that a transportation outsourcing ser-vice is beneficial to economies of scale leading to savings incapital investments and reductions of financial risk [31ndash36]However environmental problems become more serious inthe field of logistics management because logistics and
Mathematical Problems in Engineering 3
transportation are the second most common causes of theemission of greenhouse gases such as carbon monoxide andcarbon dioxide )us many researchers have examinedenvironmental problems and their links to 3PL Suzuki [37]developed a truck-scheduling solution which minimizes fuelconsumption and pollutant emissions showing that con-siderable savings in fuel consumption can be realized if thedistance a truck travels with heavy payloads can be mini-mized which can further increase energy efficiency andreduce pollutant emissions De Giovanni and Zaccour [38]studied a two-echelon closed-loop supply chain in which3PL is responsible for collecting used products )eyrevealed that unless 3PL performs better than the retailer themanufacturer never selects 3PL as a means by which tooutsource in reverse logistics Zhu et al [39] established amaximum-capacity model and developed a vehicle-routingprocedure that allows a particular vehicle to use the max-imum-capacity route with a set fuel consumption levelBazan et al [40] investigated different models of greenhousegas emissions from the production and transportation op-erations in a supply chain under amultilevel emission-taxingscheme )ey found that energy usage is the main costcomponent in their research models implying that reducingenergy usage should be prioritized Maiti and Giri [41]surveyed a closed-loop supply chain consisting of a retailer a3PL firm and a manufacturer who operates hybridmanufacturing and a remanufacturing system )eir nu-merical study showed that the 3PL-led decision game per-forms worst Li et al [42] addressed the transportationoutsourcing problems of a supply chain under variouscarbon tax policies and found that a strict carbon tax policyand increasing energy prices can force a manufacturer tooutsource more transportation services to a professional 3PLfirm Jamali and Rasti-Barzoki [43] investigated the effects ofreduced carbon emissions by a 3PL firm on the profitabilityof a three-echelon supply chain and asserted that in order toreduce greenhouse gas emissions 3PL firms should deliverproducts to retailers using green transportation meansConsequently the reduction in carbon emissions by the 3PLfirm increases the demand for green as well as nongreenproducts
24 Research Gaps As discussed above in-depth researchon green supply chains distribution channel structures andthird-party logistics has been conducted over the past fewdecades Moreover the distribution channel structure playsa very important role in determining the profitability of thesupply chain In addition a manufacturerrsquos interest in greenproducts and a 3PL firmrsquos carbon emission reduction effortsare important factors when evaluating the success and ef-ficiency of a supply chain for sustainable growth Howeverto the best of the authorrsquos knowledge no research has dealtwith all of these issues simultaneously Also to the best of theauthorrsquos knowledge the only paper dealing with thegreenness design of a product and 3PL firmsrsquo efforts toreduce carbon emissions is that by Jamali and Rasti-Barzoki[43] )erefore this study focuses on how the ecofriendli-ness of a manufacturer and efforts to reduce carbon
emissions by a 3PL firm affect the profits of supply chainmembers under various distribution channel structures
3 Model Description and Assumptions
31 Notations In this paper we use the notations presentedin Table 1
32 Investigated Supply Chain We consider a green supplychain composed of two manufacturers two retailers andone third-party logistics firm In this supply chain themanufacturers provide consumers with substitutableproducts )e first manufacturer (M1) produces a green(ecofriendly) product while the second manufacturer (M2)produces a nongreen product All products produced by thetwo manufacturers are delivered to and stored by the 3PLfirm When shipping the products to the 3PL firm eachmanufacturer pays tm per unit product)e two retailers (R1and R2) then receive the green and nongreen products fromthe 3PL firm For retailers the unit shipping cost is assumedto be equal to tr Each manufacturer can choose to distributetheir goods through either one retailer or both retailers
)ere is a three-stage game involved in the green supplychain In the first stage of the game M1 determines itswholesale price w1 and the greenness degree g of its greenproduct At the same time M2 sets its wholesale price w2 Byspecifying the values of w1 w2 and g in the second stage3PL determines its carbon emission reduction e Finallybased on all information of other members R1 and R2determine the selling quantities of the manufacturersrsquoproducts q1 and q2 In order to establish a game-theoreticalmodel the following basic assumptions are made
Assumption 1 Each manufacturer can distribute its prod-ucts through a single retailer or through both retailers If amanufacturer chooses to distribute through a single retailerthe channel structure is called a single distribution channelA cross-distribution channel represents the channel struc-ture by which amanufacturer distributes its product throughboth retailers )erefore the following four different dis-tribution channel structures can be defined the single-singlestructure (SS) cross-cross structure (CC) cross-singlestructure (CS) and single-cross structure (SC) One morepossible structure is the case where both retailers cooperatewith each other (CO) In this study we deal with these fivedifferent distribution channel structures (see Figure 1)
Assumption 2 )e demands for the green and nongreenproducts are sensitive to price the degree of greenness andthe amount of carbon emission reduction It is assumed thatthe green and nongreen products show no significant dif-ference in terms of function but vary in terms of price andenvironmental value )e greenness degree of the producthas a positive (negative) impact on M1rsquos (M2rsquos) demandbecause M1 only produces green products Hence the de-mand function of each manufacturer can be expressed asfollows
4 Mathematical Problems in Engineering
q1 α1 minus p1 + βp2 + λ1g + μe
q2 α2 minus p2 + βp1 minus λ2g + μe(1)
In equation (1) we assume that λ1 gt λ2 )e ratio ofpeople interested in buying the green (nongreen) product isλ1 (λ2) If the green products are not available in the marketconsumers are then willing to switch to buying the nongreenproducts )erefore the difference λ1 minus λ2 determines thenumber of consumers who give up buying the nongreenproduct A similar assumption can be found in earlierstudies [15 18 43]
Assumption 3 Cournot competition is an economic modelwhich describes an industry structure in which firmscompete on the selling quantity with decisions made in-dependently of each other and at the same time In thispaper we assume that the two manufacturers compete onselling quantity rather than wholesale price From equation(1) the following retail price functions are derived
p1 q1 q2( 1113857 α1 minus q1 + λ1g + β α2 minus q2 minus λ2g( 1113857 + μe(1 + β)
1 minus β2
p2 q2 q1( 1113857 α2 minus q2 minus λ2g + β α1 minus q1 + λ1g( 1113857 + μe(1 + β)
1 minus β2
(2)
Because each manufacturer can distribute its productthrough different retailers we have qi qii + qij andqi qii + qij where qij is manufacturer irsquos selling quantitydistributed through retailer j
Assumption 4 We assume that the investment in greeningthe product is an increasing and convex function of thegreenness degree of M1rsquos product Hence the greenness costcan be expressed as (cmg22) We also assume that theinvestment in reducing carbon emissions is an increasingand convex function of 3PLrsquos carbon emission reduction)us the carbon abatement investment cost can be given by
Table 1 Notations
Indicesi j Manufacturers and retailers (i j 1 2)
Decision variablese Carbon emission reduction by 3PLg Greenness degree of a productqi Manufacturer irsquos selling quantityqij Manufacturer irsquos selling quantity distributed through retailer j (qi qii + qij)
wi Manufacturer irsquos wholesale priceParametersc3 Cost coefficient of carbon emission reductioncm Cost coefficient of the greenness degreetr Retailerrsquos payment to 3PL per unit of transportationtm Manufacturerrsquos payment to 3PL per unit of transportationαi Potential market demand for manufacturer irsquos productβ Impact of a competitive price on the selling quantity (0lt βlt 1)
λi Impact of the greenness degree of a product on the selling quantityμ Impact of carbon emission reduction by 3PL on the selling quantityFunctionspi Retail price of manufacturer irsquos productπmi Manufacturer irsquos profitπri Retailer irsquos profitπrt Retailersrsquo total profit (πrt πr1 + πr2)
π3 3PLrsquos profitπgsc Supply chain profit (πgsc πm1 + πm2 + πr1 + πr2 + π3)
q1 q2
q2
M1 M2
3PL
q2
R1 R2
(a)
q1
q11 q12
q2
q22q21
M1 M2
3PL
R1 R2
(b)
q11 q12
q1 q2
q2
M1 M2
3PL
R1 R2
(c)
q1
q1
q2
q22q21
M1 M2
3PL
R1 R2
(d)
q1 q2
M1 M2
3PL
R1 R2
(e)
Figure 1 Five distribution channel structures (a) SS structure (b) CC structure (c) CS structure (d) SC structure (e) CO structure
Mathematical Problems in Engineering 5
(c3e22) Similar assumptions were made in earlier studies
[44ndash46]
Assumption 5 To focus on the effect of distribution channelthe two manufacturersrsquo production costs are assumed to beconstant and normalized to zero Similarly the retailersrsquooperational costs are also normalized to zero Allowingnonzero production and operational costs will not quali-tatively change our results We also assume that consumersin the market must visit the traditional brick-and-mortarretailers to purchase the product therefore the shippingcosts between consumers and retailers are ignored here
4 Analysis
In this section we analyze each possible distribution channelstructure and then present the equilibrium results on theselling quantity the greenness degree and the carbonemission reduction
41 SS Structure Both M1 and M2 Adopt Single DistributionChannel First we discuss the SS structure in which M1rsquos(M2rsquos) product is exclusively distributed through R1 (R2)(Figure 1(a)) )e profit function of each member in thegreen supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q1
πr2 p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(3)
Proposition 1 Let qSSi eSS gSS and wSSi denote the selling
quantity of product i the carbon emission reduction thegreenness degree and the wholesale price of product i in the SSdistribution channel structure respectively If the condition4cm(1 minus β2)(4 minus β2)gtA2
3 is met the optimal decisions are canbe determined as follows
qSS1
A1 + gSSA3 + 1 minus β21113872 1113873 βwSS2 minus 2wSS
1( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4a)
qSS2
A2 + gSSA4 + 1 minus β21113872 1113873 βwSS1 minus 2wSS
2( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4b)
eSS
2μ(1 + β) tm + tr( 1113857
c3(2 + β) (4c)
gSS
A3 1 minus β21113872 1113873 4A5 + βA6 minus tm 16 minus β21113872 11138731113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857 (4d)
wSS1 tm +
cmgSS 4 minus β21113872 1113873
A3 (4e)
wSS2
14
βwSS1 +
gSSA4
1 minus β2+ A61113888 1113889 (4f)
e values of A1 to A7 are given in Appendix
Proof )e decision sequence in the case of the SS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq1
πr1
maxq2
πr2 (5)
To solve the decision problem in equation (5) we usebackward induction Given the values of other membersrsquodecision variables we initially maximize the retailersrsquoprofits From the fact that (z2πrizq2i ) minus (2(1 minus β2))lt 0for i 1 2 the profit function of each retailer is strictlyconcave with respect to (wrt) its own selling quantity)us solving the first-order conditions (FOCs) of theretailers yields equations (4a) and (4b) Substituting theminto the 3PLrsquos profit function the second-order condition(SOC) of the 3PLrsquos problem is given by(z2π3ze2) minus c3 lt 0 From the 3PLrsquos FOC we haveequation (4c) Integrating equations (4a)ndash(4c) into theprofit functions of the manufacturers we can obtain M1rsquosHessian matrix as follows
HSSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 1 minus β21113872 1113873
4 minus β2A3
4 minus β2
A3
4 minus β2minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(6)
We define ΔSSk as the leading principal minor of order k
in HSSm1 We then find that ΔSS1 lt 0 If we assume that
4cm(1 minus β2)(4 minus β2)gtA23 Δ
SS2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because(z2πm2zw2
2) minus 4((1 minus β2)(4 minus β2))lt 0 By solving theFOCs of manufacturersrsquo problem all members in the greensupply chain can find their own equilibrium strategies inequations (4a)ndash(4f) )is completes the proof
42 CC Structure Both M1 andM2 Adopt Cross-DistributionChannel Next we analyze the CC structure in which eachmanufacturer distributes via both retailers (Figure 1(b))Recall that in the case of the CC structure qi qii + qij fori 1 2 and because each manufacturer can distribute itsproduct through different retailers )us the profit functionof each member in the green supply chain is given as
6 Mathematical Problems in Engineering
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q11 + p2 minus w2 minus tr( 1113857q21
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q11 + q12 + q21 + q22( 1113857 minusc3e
2
2
(7)
Proposition 2 Let qCCij eCC gCC and wCCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and thewholesale price of product i in the CC distribution channelstructure If the condition 3cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qCC11 q
CC12
B1 + λ1gCC minus wCC1 + βwCC
2 + μeCC
3 (8a)
qCC21 q
CC22
B2 minus λ2gCC + βwCC1 minus wCC
2 + μeCC
3 (8b)
eCC
4μ tm + tr( 1113857
3c3 (8c)
gCC
2λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCC( 1113857( 1113857
3cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857 (8d)
wCC1 tm +
3cmgCC
2λ1 (8e)
wCC2
βwCC1 minus λ2gCC + μeCC + tm + B2
2 (8f)
e values of B1 and B2 are given in Appendix
Proof )e decision sequence in the case of the CC structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11 q21
πr1
maxq12 q22
πr2 (9)
Given the values of other membersrsquo decision variablesfirst we maximize retailersrsquo profits Let HCC
ri denote theHessian matrix of retailer irsquos profit maximization problem)en we have
HCCri
z2πri
zq2ii
z2πri
zqiizqji
z2πri
zqjizqii
z2πri
zqji2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(10)
We define ΞCCk as the leading principal minor of order k
in HCCri We then find that ΞCC1 lt 0 and ΞCC2 (4
(1 minus β2))gt 0 )us the profit function of retailer i is strictlyconcave wrt its own selling quantities Accordingly solvingthe FOCs of the retailersrsquo problems yields equations (8a) and(8b) Substituting them into the 3PLrsquos profit function theSOC of the 3PLrsquos problem is determined by (z2π3ze2)
minus c3 lt 0 From the 3PLrsquos FOC we have (8c) Integratingequations (8a) to (8c) into the profit functions of the man-ufacturers we can obtain M1rsquos Hessian matrix as follows
HCCm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus43
2λ13
2λ13
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(11)
We define ΔCCk as the leading principal minor of order k
in HCCm1 We then find that ΔCC1 lt 0 Assuming that 3cm gt λ
21
we haveΔCC2 gt 0 implying thatM1rsquos profit function is strictlyconcave wrt w1 and g M2rsquos profit function is also strictlyconcave wrt w2 because the SOC of M2rsquos problem is givenby (z2πm2zw2
2) minus (43)lt 0 By solving the FOCs of themanufacturersrsquo problem all members in the green supplychain can find their own equilibrium strategies via equations(8a)ndash(8f) )is completes the proof
Note that from equations (7) (8a) and (8b) we haveπr1 πr2 in the CC structure
43 CS Structure M1 Adopts Cross-Distribution Channelwhile M2 Adopts Single Distribution Channel In the case ofthe CS structure M1 distributes its green products throughboth R1 and R2 while M2 distributes its nongreen productsonly through R2 (Figure 1(c)) Because green products aredistributed through both retailers we have q1 q11 + q12)us the profit function of each member in the green supplychain is given as
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q11
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q11 + q12 + q2( 1113857 minusc3e
2
2
(12)
Proposition 3 Let qCSij eCS gCS and wCSi denote corre-
spondingly the selling quantity of product i via retailer jthe carbon emission reduction the greenness degree andthe wholesale price of product i in the CS distributionchannel structure If the condition 12cm(4 minus β2)gt(4λ1 minus βλ2)
2 is met the optimal decisions are can be de-termined as follows
Mathematical Problems in Engineering 7
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
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[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
transportation are the second most common causes of theemission of greenhouse gases such as carbon monoxide andcarbon dioxide )us many researchers have examinedenvironmental problems and their links to 3PL Suzuki [37]developed a truck-scheduling solution which minimizes fuelconsumption and pollutant emissions showing that con-siderable savings in fuel consumption can be realized if thedistance a truck travels with heavy payloads can be mini-mized which can further increase energy efficiency andreduce pollutant emissions De Giovanni and Zaccour [38]studied a two-echelon closed-loop supply chain in which3PL is responsible for collecting used products )eyrevealed that unless 3PL performs better than the retailer themanufacturer never selects 3PL as a means by which tooutsource in reverse logistics Zhu et al [39] established amaximum-capacity model and developed a vehicle-routingprocedure that allows a particular vehicle to use the max-imum-capacity route with a set fuel consumption levelBazan et al [40] investigated different models of greenhousegas emissions from the production and transportation op-erations in a supply chain under amultilevel emission-taxingscheme )ey found that energy usage is the main costcomponent in their research models implying that reducingenergy usage should be prioritized Maiti and Giri [41]surveyed a closed-loop supply chain consisting of a retailer a3PL firm and a manufacturer who operates hybridmanufacturing and a remanufacturing system )eir nu-merical study showed that the 3PL-led decision game per-forms worst Li et al [42] addressed the transportationoutsourcing problems of a supply chain under variouscarbon tax policies and found that a strict carbon tax policyand increasing energy prices can force a manufacturer tooutsource more transportation services to a professional 3PLfirm Jamali and Rasti-Barzoki [43] investigated the effects ofreduced carbon emissions by a 3PL firm on the profitabilityof a three-echelon supply chain and asserted that in order toreduce greenhouse gas emissions 3PL firms should deliverproducts to retailers using green transportation meansConsequently the reduction in carbon emissions by the 3PLfirm increases the demand for green as well as nongreenproducts
24 Research Gaps As discussed above in-depth researchon green supply chains distribution channel structures andthird-party logistics has been conducted over the past fewdecades Moreover the distribution channel structure playsa very important role in determining the profitability of thesupply chain In addition a manufacturerrsquos interest in greenproducts and a 3PL firmrsquos carbon emission reduction effortsare important factors when evaluating the success and ef-ficiency of a supply chain for sustainable growth Howeverto the best of the authorrsquos knowledge no research has dealtwith all of these issues simultaneously Also to the best of theauthorrsquos knowledge the only paper dealing with thegreenness design of a product and 3PL firmsrsquo efforts toreduce carbon emissions is that by Jamali and Rasti-Barzoki[43] )erefore this study focuses on how the ecofriendli-ness of a manufacturer and efforts to reduce carbon
emissions by a 3PL firm affect the profits of supply chainmembers under various distribution channel structures
3 Model Description and Assumptions
31 Notations In this paper we use the notations presentedin Table 1
32 Investigated Supply Chain We consider a green supplychain composed of two manufacturers two retailers andone third-party logistics firm In this supply chain themanufacturers provide consumers with substitutableproducts )e first manufacturer (M1) produces a green(ecofriendly) product while the second manufacturer (M2)produces a nongreen product All products produced by thetwo manufacturers are delivered to and stored by the 3PLfirm When shipping the products to the 3PL firm eachmanufacturer pays tm per unit product)e two retailers (R1and R2) then receive the green and nongreen products fromthe 3PL firm For retailers the unit shipping cost is assumedto be equal to tr Each manufacturer can choose to distributetheir goods through either one retailer or both retailers
)ere is a three-stage game involved in the green supplychain In the first stage of the game M1 determines itswholesale price w1 and the greenness degree g of its greenproduct At the same time M2 sets its wholesale price w2 Byspecifying the values of w1 w2 and g in the second stage3PL determines its carbon emission reduction e Finallybased on all information of other members R1 and R2determine the selling quantities of the manufacturersrsquoproducts q1 and q2 In order to establish a game-theoreticalmodel the following basic assumptions are made
Assumption 1 Each manufacturer can distribute its prod-ucts through a single retailer or through both retailers If amanufacturer chooses to distribute through a single retailerthe channel structure is called a single distribution channelA cross-distribution channel represents the channel struc-ture by which amanufacturer distributes its product throughboth retailers )erefore the following four different dis-tribution channel structures can be defined the single-singlestructure (SS) cross-cross structure (CC) cross-singlestructure (CS) and single-cross structure (SC) One morepossible structure is the case where both retailers cooperatewith each other (CO) In this study we deal with these fivedifferent distribution channel structures (see Figure 1)
Assumption 2 )e demands for the green and nongreenproducts are sensitive to price the degree of greenness andthe amount of carbon emission reduction It is assumed thatthe green and nongreen products show no significant dif-ference in terms of function but vary in terms of price andenvironmental value )e greenness degree of the producthas a positive (negative) impact on M1rsquos (M2rsquos) demandbecause M1 only produces green products Hence the de-mand function of each manufacturer can be expressed asfollows
4 Mathematical Problems in Engineering
q1 α1 minus p1 + βp2 + λ1g + μe
q2 α2 minus p2 + βp1 minus λ2g + μe(1)
In equation (1) we assume that λ1 gt λ2 )e ratio ofpeople interested in buying the green (nongreen) product isλ1 (λ2) If the green products are not available in the marketconsumers are then willing to switch to buying the nongreenproducts )erefore the difference λ1 minus λ2 determines thenumber of consumers who give up buying the nongreenproduct A similar assumption can be found in earlierstudies [15 18 43]
Assumption 3 Cournot competition is an economic modelwhich describes an industry structure in which firmscompete on the selling quantity with decisions made in-dependently of each other and at the same time In thispaper we assume that the two manufacturers compete onselling quantity rather than wholesale price From equation(1) the following retail price functions are derived
p1 q1 q2( 1113857 α1 minus q1 + λ1g + β α2 minus q2 minus λ2g( 1113857 + μe(1 + β)
1 minus β2
p2 q2 q1( 1113857 α2 minus q2 minus λ2g + β α1 minus q1 + λ1g( 1113857 + μe(1 + β)
1 minus β2
(2)
Because each manufacturer can distribute its productthrough different retailers we have qi qii + qij andqi qii + qij where qij is manufacturer irsquos selling quantitydistributed through retailer j
Assumption 4 We assume that the investment in greeningthe product is an increasing and convex function of thegreenness degree of M1rsquos product Hence the greenness costcan be expressed as (cmg22) We also assume that theinvestment in reducing carbon emissions is an increasingand convex function of 3PLrsquos carbon emission reduction)us the carbon abatement investment cost can be given by
Table 1 Notations
Indicesi j Manufacturers and retailers (i j 1 2)
Decision variablese Carbon emission reduction by 3PLg Greenness degree of a productqi Manufacturer irsquos selling quantityqij Manufacturer irsquos selling quantity distributed through retailer j (qi qii + qij)
wi Manufacturer irsquos wholesale priceParametersc3 Cost coefficient of carbon emission reductioncm Cost coefficient of the greenness degreetr Retailerrsquos payment to 3PL per unit of transportationtm Manufacturerrsquos payment to 3PL per unit of transportationαi Potential market demand for manufacturer irsquos productβ Impact of a competitive price on the selling quantity (0lt βlt 1)
λi Impact of the greenness degree of a product on the selling quantityμ Impact of carbon emission reduction by 3PL on the selling quantityFunctionspi Retail price of manufacturer irsquos productπmi Manufacturer irsquos profitπri Retailer irsquos profitπrt Retailersrsquo total profit (πrt πr1 + πr2)
π3 3PLrsquos profitπgsc Supply chain profit (πgsc πm1 + πm2 + πr1 + πr2 + π3)
q1 q2
q2
M1 M2
3PL
q2
R1 R2
(a)
q1
q11 q12
q2
q22q21
M1 M2
3PL
R1 R2
(b)
q11 q12
q1 q2
q2
M1 M2
3PL
R1 R2
(c)
q1
q1
q2
q22q21
M1 M2
3PL
R1 R2
(d)
q1 q2
M1 M2
3PL
R1 R2
(e)
Figure 1 Five distribution channel structures (a) SS structure (b) CC structure (c) CS structure (d) SC structure (e) CO structure
Mathematical Problems in Engineering 5
(c3e22) Similar assumptions were made in earlier studies
[44ndash46]
Assumption 5 To focus on the effect of distribution channelthe two manufacturersrsquo production costs are assumed to beconstant and normalized to zero Similarly the retailersrsquooperational costs are also normalized to zero Allowingnonzero production and operational costs will not quali-tatively change our results We also assume that consumersin the market must visit the traditional brick-and-mortarretailers to purchase the product therefore the shippingcosts between consumers and retailers are ignored here
4 Analysis
In this section we analyze each possible distribution channelstructure and then present the equilibrium results on theselling quantity the greenness degree and the carbonemission reduction
41 SS Structure Both M1 and M2 Adopt Single DistributionChannel First we discuss the SS structure in which M1rsquos(M2rsquos) product is exclusively distributed through R1 (R2)(Figure 1(a)) )e profit function of each member in thegreen supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q1
πr2 p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(3)
Proposition 1 Let qSSi eSS gSS and wSSi denote the selling
quantity of product i the carbon emission reduction thegreenness degree and the wholesale price of product i in the SSdistribution channel structure respectively If the condition4cm(1 minus β2)(4 minus β2)gtA2
3 is met the optimal decisions are canbe determined as follows
qSS1
A1 + gSSA3 + 1 minus β21113872 1113873 βwSS2 minus 2wSS
1( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4a)
qSS2
A2 + gSSA4 + 1 minus β21113872 1113873 βwSS1 minus 2wSS
2( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4b)
eSS
2μ(1 + β) tm + tr( 1113857
c3(2 + β) (4c)
gSS
A3 1 minus β21113872 1113873 4A5 + βA6 minus tm 16 minus β21113872 11138731113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857 (4d)
wSS1 tm +
cmgSS 4 minus β21113872 1113873
A3 (4e)
wSS2
14
βwSS1 +
gSSA4
1 minus β2+ A61113888 1113889 (4f)
e values of A1 to A7 are given in Appendix
Proof )e decision sequence in the case of the SS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq1
πr1
maxq2
πr2 (5)
To solve the decision problem in equation (5) we usebackward induction Given the values of other membersrsquodecision variables we initially maximize the retailersrsquoprofits From the fact that (z2πrizq2i ) minus (2(1 minus β2))lt 0for i 1 2 the profit function of each retailer is strictlyconcave with respect to (wrt) its own selling quantity)us solving the first-order conditions (FOCs) of theretailers yields equations (4a) and (4b) Substituting theminto the 3PLrsquos profit function the second-order condition(SOC) of the 3PLrsquos problem is given by(z2π3ze2) minus c3 lt 0 From the 3PLrsquos FOC we haveequation (4c) Integrating equations (4a)ndash(4c) into theprofit functions of the manufacturers we can obtain M1rsquosHessian matrix as follows
HSSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 1 minus β21113872 1113873
4 minus β2A3
4 minus β2
A3
4 minus β2minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(6)
We define ΔSSk as the leading principal minor of order k
in HSSm1 We then find that ΔSS1 lt 0 If we assume that
4cm(1 minus β2)(4 minus β2)gtA23 Δ
SS2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because(z2πm2zw2
2) minus 4((1 minus β2)(4 minus β2))lt 0 By solving theFOCs of manufacturersrsquo problem all members in the greensupply chain can find their own equilibrium strategies inequations (4a)ndash(4f) )is completes the proof
42 CC Structure Both M1 andM2 Adopt Cross-DistributionChannel Next we analyze the CC structure in which eachmanufacturer distributes via both retailers (Figure 1(b))Recall that in the case of the CC structure qi qii + qij fori 1 2 and because each manufacturer can distribute itsproduct through different retailers )us the profit functionof each member in the green supply chain is given as
6 Mathematical Problems in Engineering
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q11 + p2 minus w2 minus tr( 1113857q21
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q11 + q12 + q21 + q22( 1113857 minusc3e
2
2
(7)
Proposition 2 Let qCCij eCC gCC and wCCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and thewholesale price of product i in the CC distribution channelstructure If the condition 3cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qCC11 q
CC12
B1 + λ1gCC minus wCC1 + βwCC
2 + μeCC
3 (8a)
qCC21 q
CC22
B2 minus λ2gCC + βwCC1 minus wCC
2 + μeCC
3 (8b)
eCC
4μ tm + tr( 1113857
3c3 (8c)
gCC
2λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCC( 1113857( 1113857
3cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857 (8d)
wCC1 tm +
3cmgCC
2λ1 (8e)
wCC2
βwCC1 minus λ2gCC + μeCC + tm + B2
2 (8f)
e values of B1 and B2 are given in Appendix
Proof )e decision sequence in the case of the CC structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11 q21
πr1
maxq12 q22
πr2 (9)
Given the values of other membersrsquo decision variablesfirst we maximize retailersrsquo profits Let HCC
ri denote theHessian matrix of retailer irsquos profit maximization problem)en we have
HCCri
z2πri
zq2ii
z2πri
zqiizqji
z2πri
zqjizqii
z2πri
zqji2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(10)
We define ΞCCk as the leading principal minor of order k
in HCCri We then find that ΞCC1 lt 0 and ΞCC2 (4
(1 minus β2))gt 0 )us the profit function of retailer i is strictlyconcave wrt its own selling quantities Accordingly solvingthe FOCs of the retailersrsquo problems yields equations (8a) and(8b) Substituting them into the 3PLrsquos profit function theSOC of the 3PLrsquos problem is determined by (z2π3ze2)
minus c3 lt 0 From the 3PLrsquos FOC we have (8c) Integratingequations (8a) to (8c) into the profit functions of the man-ufacturers we can obtain M1rsquos Hessian matrix as follows
HCCm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus43
2λ13
2λ13
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(11)
We define ΔCCk as the leading principal minor of order k
in HCCm1 We then find that ΔCC1 lt 0 Assuming that 3cm gt λ
21
we haveΔCC2 gt 0 implying thatM1rsquos profit function is strictlyconcave wrt w1 and g M2rsquos profit function is also strictlyconcave wrt w2 because the SOC of M2rsquos problem is givenby (z2πm2zw2
2) minus (43)lt 0 By solving the FOCs of themanufacturersrsquo problem all members in the green supplychain can find their own equilibrium strategies via equations(8a)ndash(8f) )is completes the proof
Note that from equations (7) (8a) and (8b) we haveπr1 πr2 in the CC structure
43 CS Structure M1 Adopts Cross-Distribution Channelwhile M2 Adopts Single Distribution Channel In the case ofthe CS structure M1 distributes its green products throughboth R1 and R2 while M2 distributes its nongreen productsonly through R2 (Figure 1(c)) Because green products aredistributed through both retailers we have q1 q11 + q12)us the profit function of each member in the green supplychain is given as
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q11
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q11 + q12 + q2( 1113857 minusc3e
2
2
(12)
Proposition 3 Let qCSij eCS gCS and wCSi denote corre-
spondingly the selling quantity of product i via retailer jthe carbon emission reduction the greenness degree andthe wholesale price of product i in the CS distributionchannel structure If the condition 12cm(4 minus β2)gt(4λ1 minus βλ2)
2 is met the optimal decisions are can be de-termined as follows
Mathematical Problems in Engineering 7
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
q1 α1 minus p1 + βp2 + λ1g + μe
q2 α2 minus p2 + βp1 minus λ2g + μe(1)
In equation (1) we assume that λ1 gt λ2 )e ratio ofpeople interested in buying the green (nongreen) product isλ1 (λ2) If the green products are not available in the marketconsumers are then willing to switch to buying the nongreenproducts )erefore the difference λ1 minus λ2 determines thenumber of consumers who give up buying the nongreenproduct A similar assumption can be found in earlierstudies [15 18 43]
Assumption 3 Cournot competition is an economic modelwhich describes an industry structure in which firmscompete on the selling quantity with decisions made in-dependently of each other and at the same time In thispaper we assume that the two manufacturers compete onselling quantity rather than wholesale price From equation(1) the following retail price functions are derived
p1 q1 q2( 1113857 α1 minus q1 + λ1g + β α2 minus q2 minus λ2g( 1113857 + μe(1 + β)
1 minus β2
p2 q2 q1( 1113857 α2 minus q2 minus λ2g + β α1 minus q1 + λ1g( 1113857 + μe(1 + β)
1 minus β2
(2)
Because each manufacturer can distribute its productthrough different retailers we have qi qii + qij andqi qii + qij where qij is manufacturer irsquos selling quantitydistributed through retailer j
Assumption 4 We assume that the investment in greeningthe product is an increasing and convex function of thegreenness degree of M1rsquos product Hence the greenness costcan be expressed as (cmg22) We also assume that theinvestment in reducing carbon emissions is an increasingand convex function of 3PLrsquos carbon emission reduction)us the carbon abatement investment cost can be given by
Table 1 Notations
Indicesi j Manufacturers and retailers (i j 1 2)
Decision variablese Carbon emission reduction by 3PLg Greenness degree of a productqi Manufacturer irsquos selling quantityqij Manufacturer irsquos selling quantity distributed through retailer j (qi qii + qij)
wi Manufacturer irsquos wholesale priceParametersc3 Cost coefficient of carbon emission reductioncm Cost coefficient of the greenness degreetr Retailerrsquos payment to 3PL per unit of transportationtm Manufacturerrsquos payment to 3PL per unit of transportationαi Potential market demand for manufacturer irsquos productβ Impact of a competitive price on the selling quantity (0lt βlt 1)
λi Impact of the greenness degree of a product on the selling quantityμ Impact of carbon emission reduction by 3PL on the selling quantityFunctionspi Retail price of manufacturer irsquos productπmi Manufacturer irsquos profitπri Retailer irsquos profitπrt Retailersrsquo total profit (πrt πr1 + πr2)
π3 3PLrsquos profitπgsc Supply chain profit (πgsc πm1 + πm2 + πr1 + πr2 + π3)
q1 q2
q2
M1 M2
3PL
q2
R1 R2
(a)
q1
q11 q12
q2
q22q21
M1 M2
3PL
R1 R2
(b)
q11 q12
q1 q2
q2
M1 M2
3PL
R1 R2
(c)
q1
q1
q2
q22q21
M1 M2
3PL
R1 R2
(d)
q1 q2
M1 M2
3PL
R1 R2
(e)
Figure 1 Five distribution channel structures (a) SS structure (b) CC structure (c) CS structure (d) SC structure (e) CO structure
Mathematical Problems in Engineering 5
(c3e22) Similar assumptions were made in earlier studies
[44ndash46]
Assumption 5 To focus on the effect of distribution channelthe two manufacturersrsquo production costs are assumed to beconstant and normalized to zero Similarly the retailersrsquooperational costs are also normalized to zero Allowingnonzero production and operational costs will not quali-tatively change our results We also assume that consumersin the market must visit the traditional brick-and-mortarretailers to purchase the product therefore the shippingcosts between consumers and retailers are ignored here
4 Analysis
In this section we analyze each possible distribution channelstructure and then present the equilibrium results on theselling quantity the greenness degree and the carbonemission reduction
41 SS Structure Both M1 and M2 Adopt Single DistributionChannel First we discuss the SS structure in which M1rsquos(M2rsquos) product is exclusively distributed through R1 (R2)(Figure 1(a)) )e profit function of each member in thegreen supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q1
πr2 p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(3)
Proposition 1 Let qSSi eSS gSS and wSSi denote the selling
quantity of product i the carbon emission reduction thegreenness degree and the wholesale price of product i in the SSdistribution channel structure respectively If the condition4cm(1 minus β2)(4 minus β2)gtA2
3 is met the optimal decisions are canbe determined as follows
qSS1
A1 + gSSA3 + 1 minus β21113872 1113873 βwSS2 minus 2wSS
1( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4a)
qSS2
A2 + gSSA4 + 1 minus β21113872 1113873 βwSS1 minus 2wSS
2( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4b)
eSS
2μ(1 + β) tm + tr( 1113857
c3(2 + β) (4c)
gSS
A3 1 minus β21113872 1113873 4A5 + βA6 minus tm 16 minus β21113872 11138731113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857 (4d)
wSS1 tm +
cmgSS 4 minus β21113872 1113873
A3 (4e)
wSS2
14
βwSS1 +
gSSA4
1 minus β2+ A61113888 1113889 (4f)
e values of A1 to A7 are given in Appendix
Proof )e decision sequence in the case of the SS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq1
πr1
maxq2
πr2 (5)
To solve the decision problem in equation (5) we usebackward induction Given the values of other membersrsquodecision variables we initially maximize the retailersrsquoprofits From the fact that (z2πrizq2i ) minus (2(1 minus β2))lt 0for i 1 2 the profit function of each retailer is strictlyconcave with respect to (wrt) its own selling quantity)us solving the first-order conditions (FOCs) of theretailers yields equations (4a) and (4b) Substituting theminto the 3PLrsquos profit function the second-order condition(SOC) of the 3PLrsquos problem is given by(z2π3ze2) minus c3 lt 0 From the 3PLrsquos FOC we haveequation (4c) Integrating equations (4a)ndash(4c) into theprofit functions of the manufacturers we can obtain M1rsquosHessian matrix as follows
HSSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 1 minus β21113872 1113873
4 minus β2A3
4 minus β2
A3
4 minus β2minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(6)
We define ΔSSk as the leading principal minor of order k
in HSSm1 We then find that ΔSS1 lt 0 If we assume that
4cm(1 minus β2)(4 minus β2)gtA23 Δ
SS2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because(z2πm2zw2
2) minus 4((1 minus β2)(4 minus β2))lt 0 By solving theFOCs of manufacturersrsquo problem all members in the greensupply chain can find their own equilibrium strategies inequations (4a)ndash(4f) )is completes the proof
42 CC Structure Both M1 andM2 Adopt Cross-DistributionChannel Next we analyze the CC structure in which eachmanufacturer distributes via both retailers (Figure 1(b))Recall that in the case of the CC structure qi qii + qij fori 1 2 and because each manufacturer can distribute itsproduct through different retailers )us the profit functionof each member in the green supply chain is given as
6 Mathematical Problems in Engineering
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q11 + p2 minus w2 minus tr( 1113857q21
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q11 + q12 + q21 + q22( 1113857 minusc3e
2
2
(7)
Proposition 2 Let qCCij eCC gCC and wCCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and thewholesale price of product i in the CC distribution channelstructure If the condition 3cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qCC11 q
CC12
B1 + λ1gCC minus wCC1 + βwCC
2 + μeCC
3 (8a)
qCC21 q
CC22
B2 minus λ2gCC + βwCC1 minus wCC
2 + μeCC
3 (8b)
eCC
4μ tm + tr( 1113857
3c3 (8c)
gCC
2λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCC( 1113857( 1113857
3cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857 (8d)
wCC1 tm +
3cmgCC
2λ1 (8e)
wCC2
βwCC1 minus λ2gCC + μeCC + tm + B2
2 (8f)
e values of B1 and B2 are given in Appendix
Proof )e decision sequence in the case of the CC structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11 q21
πr1
maxq12 q22
πr2 (9)
Given the values of other membersrsquo decision variablesfirst we maximize retailersrsquo profits Let HCC
ri denote theHessian matrix of retailer irsquos profit maximization problem)en we have
HCCri
z2πri
zq2ii
z2πri
zqiizqji
z2πri
zqjizqii
z2πri
zqji2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(10)
We define ΞCCk as the leading principal minor of order k
in HCCri We then find that ΞCC1 lt 0 and ΞCC2 (4
(1 minus β2))gt 0 )us the profit function of retailer i is strictlyconcave wrt its own selling quantities Accordingly solvingthe FOCs of the retailersrsquo problems yields equations (8a) and(8b) Substituting them into the 3PLrsquos profit function theSOC of the 3PLrsquos problem is determined by (z2π3ze2)
minus c3 lt 0 From the 3PLrsquos FOC we have (8c) Integratingequations (8a) to (8c) into the profit functions of the man-ufacturers we can obtain M1rsquos Hessian matrix as follows
HCCm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus43
2λ13
2λ13
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(11)
We define ΔCCk as the leading principal minor of order k
in HCCm1 We then find that ΔCC1 lt 0 Assuming that 3cm gt λ
21
we haveΔCC2 gt 0 implying thatM1rsquos profit function is strictlyconcave wrt w1 and g M2rsquos profit function is also strictlyconcave wrt w2 because the SOC of M2rsquos problem is givenby (z2πm2zw2
2) minus (43)lt 0 By solving the FOCs of themanufacturersrsquo problem all members in the green supplychain can find their own equilibrium strategies via equations(8a)ndash(8f) )is completes the proof
Note that from equations (7) (8a) and (8b) we haveπr1 πr2 in the CC structure
43 CS Structure M1 Adopts Cross-Distribution Channelwhile M2 Adopts Single Distribution Channel In the case ofthe CS structure M1 distributes its green products throughboth R1 and R2 while M2 distributes its nongreen productsonly through R2 (Figure 1(c)) Because green products aredistributed through both retailers we have q1 q11 + q12)us the profit function of each member in the green supplychain is given as
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q11
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q11 + q12 + q2( 1113857 minusc3e
2
2
(12)
Proposition 3 Let qCSij eCS gCS and wCSi denote corre-
spondingly the selling quantity of product i via retailer jthe carbon emission reduction the greenness degree andthe wholesale price of product i in the CS distributionchannel structure If the condition 12cm(4 minus β2)gt(4λ1 minus βλ2)
2 is met the optimal decisions are can be de-termined as follows
Mathematical Problems in Engineering 7
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
(c3e22) Similar assumptions were made in earlier studies
[44ndash46]
Assumption 5 To focus on the effect of distribution channelthe two manufacturersrsquo production costs are assumed to beconstant and normalized to zero Similarly the retailersrsquooperational costs are also normalized to zero Allowingnonzero production and operational costs will not quali-tatively change our results We also assume that consumersin the market must visit the traditional brick-and-mortarretailers to purchase the product therefore the shippingcosts between consumers and retailers are ignored here
4 Analysis
In this section we analyze each possible distribution channelstructure and then present the equilibrium results on theselling quantity the greenness degree and the carbonemission reduction
41 SS Structure Both M1 and M2 Adopt Single DistributionChannel First we discuss the SS structure in which M1rsquos(M2rsquos) product is exclusively distributed through R1 (R2)(Figure 1(a)) )e profit function of each member in thegreen supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q1
πr2 p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(3)
Proposition 1 Let qSSi eSS gSS and wSSi denote the selling
quantity of product i the carbon emission reduction thegreenness degree and the wholesale price of product i in the SSdistribution channel structure respectively If the condition4cm(1 minus β2)(4 minus β2)gtA2
3 is met the optimal decisions are canbe determined as follows
qSS1
A1 + gSSA3 + 1 minus β21113872 1113873 βwSS2 minus 2wSS
1( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4a)
qSS2
A2 + gSSA4 + 1 minus β21113872 1113873 βwSS1 minus 2wSS
2( 1113857 + μeSS 2 + β minus β21113872 1113873
4 minus β2
(4b)
eSS
2μ(1 + β) tm + tr( 1113857
c3(2 + β) (4c)
gSS
A3 1 minus β21113872 1113873 4A5 + βA6 minus tm 16 minus β21113872 11138731113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857 (4d)
wSS1 tm +
cmgSS 4 minus β21113872 1113873
A3 (4e)
wSS2
14
βwSS1 +
gSSA4
1 minus β2+ A61113888 1113889 (4f)
e values of A1 to A7 are given in Appendix
Proof )e decision sequence in the case of the SS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq1
πr1
maxq2
πr2 (5)
To solve the decision problem in equation (5) we usebackward induction Given the values of other membersrsquodecision variables we initially maximize the retailersrsquoprofits From the fact that (z2πrizq2i ) minus (2(1 minus β2))lt 0for i 1 2 the profit function of each retailer is strictlyconcave with respect to (wrt) its own selling quantity)us solving the first-order conditions (FOCs) of theretailers yields equations (4a) and (4b) Substituting theminto the 3PLrsquos profit function the second-order condition(SOC) of the 3PLrsquos problem is given by(z2π3ze2) minus c3 lt 0 From the 3PLrsquos FOC we haveequation (4c) Integrating equations (4a)ndash(4c) into theprofit functions of the manufacturers we can obtain M1rsquosHessian matrix as follows
HSSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 1 minus β21113872 1113873
4 minus β2A3
4 minus β2
A3
4 minus β2minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(6)
We define ΔSSk as the leading principal minor of order k
in HSSm1 We then find that ΔSS1 lt 0 If we assume that
4cm(1 minus β2)(4 minus β2)gtA23 Δ
SS2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because(z2πm2zw2
2) minus 4((1 minus β2)(4 minus β2))lt 0 By solving theFOCs of manufacturersrsquo problem all members in the greensupply chain can find their own equilibrium strategies inequations (4a)ndash(4f) )is completes the proof
42 CC Structure Both M1 andM2 Adopt Cross-DistributionChannel Next we analyze the CC structure in which eachmanufacturer distributes via both retailers (Figure 1(b))Recall that in the case of the CC structure qi qii + qij fori 1 2 and because each manufacturer can distribute itsproduct through different retailers )us the profit functionof each member in the green supply chain is given as
6 Mathematical Problems in Engineering
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q11 + p2 minus w2 minus tr( 1113857q21
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q11 + q12 + q21 + q22( 1113857 minusc3e
2
2
(7)
Proposition 2 Let qCCij eCC gCC and wCCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and thewholesale price of product i in the CC distribution channelstructure If the condition 3cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qCC11 q
CC12
B1 + λ1gCC minus wCC1 + βwCC
2 + μeCC
3 (8a)
qCC21 q
CC22
B2 minus λ2gCC + βwCC1 minus wCC
2 + μeCC
3 (8b)
eCC
4μ tm + tr( 1113857
3c3 (8c)
gCC
2λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCC( 1113857( 1113857
3cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857 (8d)
wCC1 tm +
3cmgCC
2λ1 (8e)
wCC2
βwCC1 minus λ2gCC + μeCC + tm + B2
2 (8f)
e values of B1 and B2 are given in Appendix
Proof )e decision sequence in the case of the CC structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11 q21
πr1
maxq12 q22
πr2 (9)
Given the values of other membersrsquo decision variablesfirst we maximize retailersrsquo profits Let HCC
ri denote theHessian matrix of retailer irsquos profit maximization problem)en we have
HCCri
z2πri
zq2ii
z2πri
zqiizqji
z2πri
zqjizqii
z2πri
zqji2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(10)
We define ΞCCk as the leading principal minor of order k
in HCCri We then find that ΞCC1 lt 0 and ΞCC2 (4
(1 minus β2))gt 0 )us the profit function of retailer i is strictlyconcave wrt its own selling quantities Accordingly solvingthe FOCs of the retailersrsquo problems yields equations (8a) and(8b) Substituting them into the 3PLrsquos profit function theSOC of the 3PLrsquos problem is determined by (z2π3ze2)
minus c3 lt 0 From the 3PLrsquos FOC we have (8c) Integratingequations (8a) to (8c) into the profit functions of the man-ufacturers we can obtain M1rsquos Hessian matrix as follows
HCCm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus43
2λ13
2λ13
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(11)
We define ΔCCk as the leading principal minor of order k
in HCCm1 We then find that ΔCC1 lt 0 Assuming that 3cm gt λ
21
we haveΔCC2 gt 0 implying thatM1rsquos profit function is strictlyconcave wrt w1 and g M2rsquos profit function is also strictlyconcave wrt w2 because the SOC of M2rsquos problem is givenby (z2πm2zw2
2) minus (43)lt 0 By solving the FOCs of themanufacturersrsquo problem all members in the green supplychain can find their own equilibrium strategies via equations(8a)ndash(8f) )is completes the proof
Note that from equations (7) (8a) and (8b) we haveπr1 πr2 in the CC structure
43 CS Structure M1 Adopts Cross-Distribution Channelwhile M2 Adopts Single Distribution Channel In the case ofthe CS structure M1 distributes its green products throughboth R1 and R2 while M2 distributes its nongreen productsonly through R2 (Figure 1(c)) Because green products aredistributed through both retailers we have q1 q11 + q12)us the profit function of each member in the green supplychain is given as
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q11
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q11 + q12 + q2( 1113857 minusc3e
2
2
(12)
Proposition 3 Let qCSij eCS gCS and wCSi denote corre-
spondingly the selling quantity of product i via retailer jthe carbon emission reduction the greenness degree andthe wholesale price of product i in the CS distributionchannel structure If the condition 12cm(4 minus β2)gt(4λ1 minus βλ2)
2 is met the optimal decisions are can be de-termined as follows
Mathematical Problems in Engineering 7
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q11 + p2 minus w2 minus tr( 1113857q21
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q11 + q12 + q21 + q22( 1113857 minusc3e
2
2
(7)
Proposition 2 Let qCCij eCC gCC and wCCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and thewholesale price of product i in the CC distribution channelstructure If the condition 3cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qCC11 q
CC12
B1 + λ1gCC minus wCC1 + βwCC
2 + μeCC
3 (8a)
qCC21 q
CC22
B2 minus λ2gCC + βwCC1 minus wCC
2 + μeCC
3 (8b)
eCC
4μ tm + tr( 1113857
3c3 (8c)
gCC
2λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCC( 1113857( 1113857
3cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857 (8d)
wCC1 tm +
3cmgCC
2λ1 (8e)
wCC2
βwCC1 minus λ2gCC + μeCC + tm + B2
2 (8f)
e values of B1 and B2 are given in Appendix
Proof )e decision sequence in the case of the CC structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11 q21
πr1
maxq12 q22
πr2 (9)
Given the values of other membersrsquo decision variablesfirst we maximize retailersrsquo profits Let HCC
ri denote theHessian matrix of retailer irsquos profit maximization problem)en we have
HCCri
z2πri
zq2ii
z2πri
zqiizqji
z2πri
zqjizqii
z2πri
zqji2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(10)
We define ΞCCk as the leading principal minor of order k
in HCCri We then find that ΞCC1 lt 0 and ΞCC2 (4
(1 minus β2))gt 0 )us the profit function of retailer i is strictlyconcave wrt its own selling quantities Accordingly solvingthe FOCs of the retailersrsquo problems yields equations (8a) and(8b) Substituting them into the 3PLrsquos profit function theSOC of the 3PLrsquos problem is determined by (z2π3ze2)
minus c3 lt 0 From the 3PLrsquos FOC we have (8c) Integratingequations (8a) to (8c) into the profit functions of the man-ufacturers we can obtain M1rsquos Hessian matrix as follows
HCCm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus43
2λ13
2λ13
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(11)
We define ΔCCk as the leading principal minor of order k
in HCCm1 We then find that ΔCC1 lt 0 Assuming that 3cm gt λ
21
we haveΔCC2 gt 0 implying thatM1rsquos profit function is strictlyconcave wrt w1 and g M2rsquos profit function is also strictlyconcave wrt w2 because the SOC of M2rsquos problem is givenby (z2πm2zw2
2) minus (43)lt 0 By solving the FOCs of themanufacturersrsquo problem all members in the green supplychain can find their own equilibrium strategies via equations(8a)ndash(8f) )is completes the proof
Note that from equations (7) (8a) and (8b) we haveπr1 πr2 in the CC structure
43 CS Structure M1 Adopts Cross-Distribution Channelwhile M2 Adopts Single Distribution Channel In the case ofthe CS structure M1 distributes its green products throughboth R1 and R2 while M2 distributes its nongreen productsonly through R2 (Figure 1(c)) Because green products aredistributed through both retailers we have q1 q11 + q12)us the profit function of each member in the green supplychain is given as
πm1 w1 minus tm( 1113857 q11 + q12( 1113857 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πr1 p1 minus w1 minus tr( 1113857q11
πr2 p1 minus w1 minus tr( 1113857q12 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q11 + q12 + q2( 1113857 minusc3e
2
2
(12)
Proposition 3 Let qCSij eCS gCS and wCSi denote corre-
spondingly the selling quantity of product i via retailer jthe carbon emission reduction the greenness degree andthe wholesale price of product i in the CS distributionchannel structure If the condition 12cm(4 minus β2)gt(4λ1 minus βλ2)
2 is met the optimal decisions are can be de-termined as follows
Mathematical Problems in Engineering 7
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
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[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
qCS11
C1 minus wCS1 1 minus β21113872 1113873 + gCS λ1 minus βλ2( 1113857 + μeCS(1 + β)
3 (13a)
qCS12
C2 minus wCS1 2 + β21113872 1113873 + 3βwCS
2 + gCS 2λ1 + βλ2( 1113857 + μeCS(2 minus β)
6 (13b)
qCS2
B2 minus λ2gCS + βwCS1 minus wCS
2 + μeCS
2 (13c)
eCS
μ(7 + β) tm + tr( 1113857
6c3 (13d)
gCS
4λ1 minus βλ2( 1113857 4C1 + 2C2 + 3βB2 minus (8 + 5β) tm(1 minus β) minus μeCS( 1113857( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857 (13e)
wCS1 tm +
6cmgCS
4λ1 minus βλ2(13f)
wCS2
βwCS1 minus λ2gCS + μeCS + tm + B2
2 (13g)
e values of C1 and C2 are given in Appendix
Proof )e decision sequence in the case of the CS structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶
maxq11
πr1
maxq12 q2
πr2 (14)
Given the values of other membersrsquo decision variables wemaximize the retailersrsquo profits first )e SOC of retailer 1rsquosproblem is expressed as (z2πr1zq211) minus (2(1 minus β2))lt 0therefore the profit function of retailer 1 is strictly concave wrtits own selling quantity Let HCS
r2 denote the Hessian matrix ofretailer 2rsquos profit maximization problem )en we have
HCSr2
z2πr2
zq212
z2πr2
zq12zq2
z2πr2
zq2zq12
z2πr2
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(15)
Because HCSr2 HCC
ri the profit function of retailer 2 isstrictly concave wrt its own selling quantities Accordinglysolving the FOCs of the retailersrsquo problems yields equations(13a) to (13c) Substituting them into the 3PLrsquos profit functionthe SOC of the 3PLrsquos problem is given by (z2π3ze2) minus c3 lt 0From the 3PLrsquos FOC we have (13d) Integrating equations(13a)ndash(13d) into the profit functions of the manufacturers wecan obtain M1rsquos Hessian matrix as follows
HCSm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus4 minus β2
34λ1 minus βλ2
6
4λ1 minus βλ26
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(16)
We define ΔCSk as the leading principal minor of order k
in HCSm1 We then find that ΔCS1 lt 0 Assuming that
12cm(4 minus β2)gt (4λ1 minus βλ2)2 we have ΔCS2 gt 0 implying that
M1rsquos profit function is strictly concave wrt w1 and g M2rsquosprofit function is also strictly concave wrt w2 because theSOC of M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies using equations (13a)ndash(13g) )iscompletes the proof
44 SC Structure M1 Adopts Single Distribution Channelwhile M2 Adopts Cross-Distribution Channel In the SCstructure as opposed to the CS structure M1 distributes itsgreen products only through R1 while M2 distributes itsnongreen products through both R1 and R2 (Figure 1(d))Because nongreen products are distributed through bothretailers we have q2 q21 + q22 )us the profit function ofeach member in the green supply chain is given as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857 q21 + q22( 1113857
πr1 p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q21
πr2 p2 minus w2 minus tr( 1113857q22
π3 tm + tr( 1113857 q1 + q21 + q22( 1113857 minusc3e
2
2
(17)
Proposition 4 Let qSCij eSC gSC and wSCi correspondingly
denote the selling quantity of product i via retailer j thecarbon emission reduction the greenness degree and the
8 Mathematical Problems in Engineering
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
wholesale price of product i in the SC distribution channelstructure If the condition 4cm gt λ
21 is met the optimal de-
cisions are can be determined as follows
qSC1
B1 + λ1gSC minus wSC1 + βwSC
2 + μeSC
2 (18a)
qSC21
D1 + 3βwSC1 minus wSC
2 2 + β21113872 1113873 minus gSC βλ1 + 2λ2( 1113857 + μeSC(2 minus β)
6 (18b)
qSC22
D2 minus wSC2 1 minus β21113872 1113873 + gSC βλ1 minus λ2( 1113857 + μeSC(1 + β)
3 (18c)
eSC
μ(7 + β) tm + tr( 1113857
6c3 (18d)
gSC
λ1 2B1 4 minus β21113872 1113873 + β D1 + 2D2( 1113857 minus 8 + 4β minus β21113872 1113873 tm(1 minus β) minus μeSC( 11138571113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 λ1 8 minus β21113872 1113873 minus 4βλ21113872 1113873 (18e)
wSC1 tm +
2cmgSC
λ1 (18f)
wSC2
12
tm +3βwSC
1 + gSC βλ1 minus 4λ2( 1113857 + μeSC(4 + β) + D1 + 2D2
4 minus β21113888 1113889 (18g)
e values of D1 and D2 are given in Appendix
Proof )e proof of Proposition 4 is quite similar to that ofProposition 3 hence we omit the proof here
45 CO Structure R1 and R2 Cooperate When Determiningeir SellingQuantities In the case of the CO structure R1and R2 cooperate with each other to set the sellingquantities More specifically the cooperation behavior issimilar to the case in which the two retailers recognizetheir interdependence and agree to act in union in order tomaximize their total profit (Figure 1(e)) )us the profitfunction of each member in the green supply chain isgiven as
πm1 w1 minus tm( 1113857q1 minuscmg2
2
πm2 w2 minus tm( 1113857q2
πrt p1 minus w1 minus tr( 1113857q1 + p2 minus w2 minus tr( 1113857q2
π3 tm + tr( 1113857 q1 + q2( 1113857 minusc3e
2
2
(19)
Proposition 5 Let qCOi eCO gCO and wCOi correspondingly
denote the selling quantity of product i the carbon emissionreduction the greenness degree and the wholesale price ofproduct i in the CO distribution channel structure If the
condition 4cm gt λ21 is met the optimal decisions are can be
determined as follows
qCO1
B1 + λ1gCO minus wCO1 + βwCO
2 + μeCO
2 (20a)
qCO2
B2 minus λ2gCO + βwCO1 minus wCO
2 + μeCO
2 (20b)
eCO
μ tm + tr( 1113857
c3 (20c)
gCO
λ1 2B1 + βB2 minus (2 + β) tm(1 minus β) minus μeCO( 1113857( 1113857
2cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857 (20d)
wCO1 tm +
2cmgCO
λ1 (20e)
wCO2
βwCO1 minus λ2gCO + μeCO + tm + B2
2 (20f)
Proof )e decision sequence in the case of the CO structureis as follows
maxw1 g
πm1
maxw2
πm2⟶ max
eπ3⟶ max
q1 q2πrt (21)
Mathematical Problems in Engineering 9
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
Given the values of other membersrsquo decision variableswe initially maximize the retailersrsquo total profit Let HCO
rt
denote the Hessian matrix of the retailersrsquo profit maximi-zation problem )en we have
HCOrt
z2πrt
zq21
z2πrt
zq1zq2
z2πrt
zq2zq1
z2πrt
zq22
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus2
1 minus β2minus
2β1 minus β2
minus2β
1 minus β2minus
21 minus β2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
(22)
Since HCOrt HCC
ri the profit function of retailersrsquoproblem is strictly concave wrt its own selling quantitiesAccordingly solving the FOCs of the retailersrsquo problemsyields equations (20a) and (20b) Substituting them into the3PLrsquos profit function the SOC of the 3PLrsquos problem is givenby z2π3ze2 minus c3 lt 0 From the 3PLrsquos FOC we haveequation (20c) Integrating equations (20a) to (20c) into theprofit functions of manufacturers we can obtain M1rsquosHessian matrix as follows
HCOm1
z2πm1
zw21
z2πm1
zw1zg
z2πm1
zg zw1
z2πm1
zg2
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦
minus 1λ12
λ12
minus cm
⎡⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎣
⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎦ (23)
We define ΔCOk as the leading principal minor of orderk in HCO
m1 We then find that ΔCO1 lt 0 Assuming that4cm gt λ
21 we have ΔCO2 gt 0 implying that M1rsquos profit
function is strictly concave wrt w1 and g M2rsquos profitfunction is also strictly concave wrt w2 because the SOCof M2rsquos problem is given by (z2πm2zw2
2) minus 1lt 0 Bysolving the FOCs of the manufacturersrsquo problem allmembers in the green supply chain can find their ownequilibrium strategies via equations (20a)ndash(20f ) )iscompletes the proof
5 Discussion
)is section provides some parametric analyses First weinvestigate the impact of the potential market demand on thegreenness degree ofM1rsquos product Second the analysis of thestrategies by the 3PL to reduce their carbon emissions isconducted
51 Effects of α1 and α2 on M1rsquos Greenness Strategy )eparameter αi in the demand function qi indicates thepotential market demand for manufacturer irsquos product Toinvestigate the impact of αi on the greenness degree ofM1rsquos green product the first derivatives of g wrt α1 ineach of the distribution channel structures are obtained asfollows
dgSS
dα1
A3 8 minus 3β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα1
4λ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα1
8 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα1
λ1 8 minus β21113872 1113873
2cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα1
2λ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(24)
)e first derivatives of g wrt α2 in each of the distri-bution channel structures are obtained as follows
dgSS
dα2
βA3 6 minus β21113872 1113873
cmA7 minus A3 4A3 + βA4( 1113857
dgCC
dα2
2βλ13cm 4 minus β21113872 1113873 minus 2λ1 2λ1 minus βλ2( 1113857
dgCS
dα2
5β 4λ1 minus βλ2( 1113857
6cm 16 minus 7β21113872 1113873 minus 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dα2
4βλ12cm 16 minus 7β21113872 1113873 minus λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dα2
βλ12cm 4 minus β21113872 1113873 minus λ1 2λ1 minus βλ2( 1113857
(25)
From equations (24) and (25) we find that the nu-merator in each equation is positive So if the denominatorin each equation is positive then the potential market de-mand affects the greenness degree positively )at is fori 1 2 the following relationship can be established
dgSS
dαi
gt 0 if cmA7 gtA3 4A3 + βA4( 1113857
dgCC
dαi
gt 0 if 3cm 4 minus β21113872 1113873gt 2λ1 2λ1 minus βλ2( 1113857
dgCS
dαi
gt 0 if 6cm 16 minus 7β21113872 1113873gt 8λ1 minus 5βλ2( 1113857 4λ1 minus βλ2( 1113857
dgSC
dαi
gt 0 if 2cm 16 minus 7β21113872 1113873gt λ1 8 minus β21113872 1113873λ1 minus 4βλ21113872 1113873
dgCO
dαi
gt 0 if 2cm 4 minus β21113872 1113873gt λ1 2λ1 minus βλ2( 1113857
(26)
10 Mathematical Problems in Engineering
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
From equations (1) and (26) we can infer the followingAs the market size grows more consumers are likely toprefer to purchase green products which in turn promotethe demand for green products )is therefore implies thatmanufacturers will be more devoted to developing greenproducts as the market size increases
52 Effect of β on 3PLrsquos Carbon Emission Reduction )eparameter β in the demand function qi indicates the com-petition intensity between M1 and M2 To investigate theimpact of β on the 3PLrsquos carbon emission reduction the firstderivatives of e wrt β in each of the distribution channelstructures are obtained as follows
deSS
dβ2μ tm + tr( 1113857
c3(2 + β)2gt 0
deCS
dβdeSC
dβμ tm + tr( 1113857
6c3gt 0
deCC
dβdeCO
dβ 0
(27)
As shown in equation (27) 3PLrsquos effort to reduce theircarbon emissions is positively influenced by the manufac-turersrsquo competition for the SS CS and SC structures Inother words if at least one of the manufacturers chooses asingle distribution channel the greater the competitionbetween manufacturers becomes the more carbon emis-sions the 3PLmust reduce It should be noted that in the caseof the CC and CO structures the 3PLrsquos carbon emissionreduction is not affected by the competition between themanufacturers because its first derivatives are equal to zeroGiven this fact if each manufacturerrsquos product is distributedthrough both retailers the competition between manufac-turers does not affect the 3PLrsquos carbon emission reductionstrategy
It is also interesting to compare the 3PLrsquos carbonemission reduction strategies for the five distributionchannel structures After some mathematics we have thefollowing relationship
eCO lt e
SS lt eCS
eSC lt e
CC (28)
It follows from equation (28) that retailersrsquo cooperationin the green supply chain leads to the least effort by the 3PLto reduce their carbon emissions We also find that moremanufacturers adopting cross-distribution channels willforce the 3PL to exert more effort to reduce their carbonemissions
6 Numerical Experiments andManagerial Insights
)is section numerically investigates the effects of certainparameters on the equilibrium quantities In the numericalexperiments conducted here we assume the followingmarket situations First although environmental awarenessby consumers is higher than ever the market size for green
products is smaller than that for nongreen products (ieα1 lt α2) Second according to Assumption 1 the number ofconsumers who give up buying the nongreen product mustbe positive (ie λ1 gt λ2) )ird M1rsquos unit greening cost ishigher than the 3PLrsquos unit carbon reduction cost (iecm gt c3) Fourth given that the manufacturers outsourcestorage as well as shipping to the 3PL the unit transportationcost borne by the manufacturers is greater than that paid bythe retailers (ie tm gt tr) Finally the values of β and μmustbe determined to satisfy the SOC of each problem Con-sidering these assumptions the main dataset used for theanalysis is given as follows α1 100 α2 150 β 05λ1 3 λ2 15 μ 2 cm 15 c3 5 tm 10 and tr 8For this dataset we obtain the equilibrium decision of eachmember in the green supply chain in the next sections
61 Effect of β on the EquilibriumQuantities Once again theparameter β in the demand function qi indicates the com-petition intensity between two manufacturers We are in-terested in an investigation of the effects of the competitionintensity on equilibrium decisions To do this we considerthe main dataset and vary β from 03 to 07 )e equilibriumquantities of the decision variables and the obtained profitsfor different values of β are plotted in Figure 2 As the valueof β increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities increasefor both manufacturersWith the CC and CO structures the 3PLrsquos efforts toreduce their carbon emissions remain constant On theother hand with the SS CS and SC structures the3PLrsquos efforts to reduce their carbon emissions increase)e profits of all members in the green supply chainincrease Subsequently the total profit of the greensupply chain also increases
From the facts observed above we suggest the followingmanagerial insight
611 Insight 1 )e intense competition between themanufacturers in the supply chain encourages M1rsquos productto be greener When M1rsquos product becomes more envi-ronmentally friendly M1rsquos selling quantity increasesBenefiting from M1rsquos increased sales M2rsquos selling quantityalso increases Due to the increased manufacturesrsquo sellingquantities the retailersrsquo and the 3PLrsquos profit also increasesimplying that the total profit of the supply chain increasesSummarizing these facts competition between manufac-turers has a positive impact on the degree of greenness andon profitability
62 Effect of λ1 on the EquilibriumQuantities )e parameterλ1 in the demand function q1 indicates the positive impact ofgreenness degree on the selling quantity of the greenproduct We conduct a sensitivity analysis of λ1 Whilevarying λ1 from 16 to 5 we record the equilibrium
Mathematical Problems in Engineering 11
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
quantities of the decision variables and the obtained profitsin Figure 3 As the value of λ1 increases we observe thefollowing
)e greenness degree of M1rsquos product increases
)ere is no effect of λ1 on 3PLrsquos carbon emissionreduction
)e wholesale price the selling quantity and the profitof M1 all increase
03 04 05 06 07
8
10
12
14
16
β
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
M1rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
80100
140
180
(b)
M2rsquos
who
lesa
le p
rice
03 04 05 06 07β
SSCCCS
SCCO
100120140160180200
(c)
03 04 05 06 07β
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
03 04 05 06 07β
SSCCCS
SCCO
40
50
60
70
80M
1rsquos se
lling
qua
ntity
(e)
03 04 05 06 07β
SSCCCS
SCCO
M2rsquos
selli
ng q
uant
ity
40
50
60
70
(f)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M1rsquos
pro
fit
(g)
03 04 05 06 07β
SSCCCS
SCCO
4000
6000
8000
10000
M2rsquos
pro
fit
(h)
03 04 05 06 07β
SSCCCS
SCCO
R1rsquos
prof
it
2000
6000
10000
(i)
03 04 05 06 07β
SSCCCS
SCCO
R2rsquos
prof
it
2000
6000
10000
(j)
03 04 05 06 07β
SSCCCS
SCCO
1400
1800
2200
2600
3PLrsquos
pro
fit
(k)
03 04 05 06 07β
SSCCCS
SCCO
15000
25000
35000
Supp
ly ch
ainrsquos
pro
fit
(l)
Figure 2 Effect of β on the equilibrium prices and profits
12 Mathematical Problems in Engineering
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
)e wholesale price the selling quantity and the profitof M2 initially decrease to a certain level ie they allreach a minimum after which they increase again)e profits of R1 R2 and 3PL increase In addition thetotal profit of the green supply chain increases
From the facts observed above we suggest the followingmanagerial insight
621 Insight 2 )e stronger the impact of the greenness of aproduct on the demand the more committed M1 is to green
15 20 25 30 35 40 45 50
10
20
30
40
λ1
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
M1rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(b)
110
120
130
140
M2rsquos
who
lesa
le p
rice
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(c)
15 20 25 30 35 40 45 50λ1
70
75
80
85
90
95
3PLrsquos
carb
on em
issio
nre
duct
ion
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(f )
4000
6000
8000
10000
M1rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(g)
4500
5500
6500
7500
M2rsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(h)
3000
5000
7000
R1rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(i)
3000
5000
7000
9000
R2rsquos
profi
t
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(j)
1500
2000
2500
3000
3PLrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(k)
20000
25000
30000
35000
Supp
ly ch
ainrsquos
pro
fit
15 20 25 30 35 40 45 50λ1
SSCCCS
SCCO
(l)
Figure 3 Effect of λ1 on the equilibrium quantities
Mathematical Problems in Engineering 13
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
product development As a result the selling quantity andprofit of M1 producing a green product all increase On theother hand when the impact of greenness on the level ofdemand is relatively weak the selling quantity and profit ofM2 gradually decrease However if the influence ofgreenness exceeds a certain value the increased sellingquantity of a green product has a positive effect on the sellingquantity of a nongreen product which causes M2rsquos profit toincrease As a result the profits of all other membersincrease
63 Effect of λ2 on the EquilibriumQuantities )e parameterλ2 in the demand function q2 indicates the negative impactof greenness degree on the selling quantity of the nongreenproduct When varying λ2 from 001 to 29 we plot theequilibrium quantities of the decision variables and theobtained profits in Figure 4 As the value of λ2 increases weobserve the following
)e greenness degree of M1rsquos product decreases Inparticular with the SS and CS structures in which M2chooses a single distribution channel the greennessdegree decreases drastically compared to that in otherdistribution channel structures)ere is no effect of λ2 on the 3PLrsquos carbon emissionreduction)e wholesale prices and the selling quantities of bothmanufacturers all decrease)e profits of R1 R2 and 3PL decrease As a result thetotal profit of the green supply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
631 Insight 3 It is interesting to note that λ2 has a negativeeffect on the greenness degree of M1rsquos product As thegreenness degree decreases consumersrsquo preference for thegreen product gradually decreases which also reduces thepreference for the nongreen product )e reduced demandadversely affects the profitability of the entire supply chainIn light of this fact the manufacturer selling a nongreenproduct is required to reduce the impact of the greennessdegree of a green product on the demand for a nongreenproduct
64 Effect of μ on the Equilibrium Quantities )e parameterμ indicates the positive impact of the 3PLrsquos carbon emissionreduction on the selling quantities of the green and nongreenproducts With varying μ from 0 to 5 we plot the equi-librium quantities of the decision variables and the obtainedprofits in Figure 5 As the value of μ increases we observe thefollowing
)e greenness degree of M1rsquos product increases)e 3PLrsquos carbon emission reduction increases)e selling quantities of the green and nongreenproducts all increase
Not only the profits of the all participants in the supplychain but also the total profit of the supply chainincrease
From the facts observed above we suggest the followingmanagerial insight
641 Insight 4 Lowering carbon emission with a 3PL has apositive impact on product sales As the sales volume ofproducts increases so does the volume of product ship-ments which results in an increase in the 3PLrsquos profit Inaddition as μ increases the green product becomesgreener which causes an increase in product sales Inother words a reduction in carbon emission by the 3PLhas a positive impact on the profitability of the supplychain
65 Effect of c3 on the EquilibriumQuantities )e parameterc3 in the profit function π3 indicates the marginal cost of the3PLrsquos efforts to reduce their carbon emissionsWhile varyingc3 from 3 to 10 we record the equilibrium quantities of thedecision variables and the obtained profits in Figure 6 As thevalue of c3 increases we observe the following
)e greenness degree of M1rsquos product decreases)e wholesale prices of both manufacturers decrease)e 3PLrsquos effort to reduce carbon emissions decreases)e selling quantities of both manufacturers decrease)e profits of all members in the green supply chaindecrease Subsequently the total profit of the greensupply chain also decreases
From the facts observed above we suggest the followingmanagerial insight
651 Insight 5 Increasing the cost of the 3PLrsquos effort toreduce carbon emissions without increasing the trans-portation charges of the products will cause the effects of the3PL to reduce their carbon emissions to be negative De-creasing the 3PLrsquos effort to reduce their carbon emissionscauses a decrease in the level of demand for both green andnongreen products implying that all members of the supplychain experience decreased profits
66 Effect of tm on the EquilibriumQuantities )e parametertm in the profit function π3 represents the shipping benefit ofthe 3PL from the manufacturers per unit shipment Whenvarying tm from 3 to 10 we record the equilibrium quantitiesof the decision variables and the obtained profits in Figure 7As the value of tm increases we observe the following
)e greenness degree of M1rsquos product increases)e wholesale prices and the selling quantities of bothmanufacturers increase)e 3PLrsquos effort to reduce their carbon emissionsincreases
14 Mathematical Problems in Engineering
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
)e profits of all members in the green supply chainincrease Hence the total profit of the green supplychain also increases
From the facts observed above we suggest the followingmanagerial insight
661 Insight 6 As the transportation cost per unit ofproduct increases M1 increases the sales of green productsby increasing the greenness degree By increasing the sales ofgreen products M1 can compensate for the increasedshipping cost )e sales of M2rsquos nongreen products alsobenefit from the increase in the sales of green products As
8
10
12
14
M1rsquos
gre
enne
ss d
egre
e
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(c)
707580859095
3PLrsquos
carb
on em
issio
nre
duct
ion
00 05 10 15 20 25 30λ2
SSCC
CS SCCO
(d)
455055606570
M1rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(e)
455055606570
M2rsquos
selli
ng q
uant
ity
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(f )
3500
4500
5500
6500
M1rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(g)
4000
5000
6000
7000
8000
M2rsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(h)
2500
3500
4500
5500
R1rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(i)
3000
4000
5000
6000
R2rsquos
prof
it
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(j)
1600
1800
2000
2200
3PLrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(k)
16000
20000
24000
Supp
ly ch
ainrsquos
pro
fit
00 05 10 15 20 25 30λ2
SSCCCS
SCCO
(l)
Figure 4 Effect of λ2 on the equilibrium quantities
Mathematical Problems in Engineering 15
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
sales of both green and nongreen products increase so doesthe profitability of the supply chain
)e effects of tr on the equilibrium quantities areidentical to those of tm therefore we omit the sensitivityanalysis of tr for brevity
67 Comparison among the Five Distribution ChannelStructures It is also interesting to evaluate and compare theperformance outcomes of different distribution channelsUnder our numerical setting and from Figures 2ndash7 we canfind the following relationships
0 1 2 3 4 5
10
15
20
micro
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
140
180
220
M1rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(b)
100
140
180
M2rsquos
who
lesa
le p
rice
0 1 2 3 4 5micro
SSCCCS
SCCO
(c)
0
5
10
15
20
25
3PLrsquos
carb
on em
issio
nre
duct
ion
0 1 2 3 4 5micro
SSCC
CS SCCO
(d)
40
60
80
100
120M
1rsquos se
lling
qua
ntity
0 1 2 3 4 5micro
SSCCCS
SCCO
(e)
405060708090
110
M2rsquos
selli
ng q
uant
ity
0 1 2 3 4 5micro
SSCCCS
SCCO
(f )
5000
10000
15000
M1rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(g)
5000
10000
15000
M2rsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(h)
2000
6000
10000
14000
R1rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(i)
2000
6000
10000
14000
R2rsquos
profi
t
0 1 2 3 4 5micro
SSCCCS
SCCO
(j)
1600
2000
2400
3PLrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(k)
20000
40000
60000
Supp
ly ch
ainrsquos
pro
fit
0 1 2 3 4 5micro
SSCCCS
SCCO
(l)
Figure 5 Effect of μ on the equilibrium quantities
16 Mathematical Problems in Engineering
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
SSCCCS
SCCO
9101112131415
M1rsquo
s gre
enne
ss d
egre
e
4 5 6 7 8 9 103c3
(a)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M1rsquos
who
lesa
le p
rice
(b)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
(c)
SSCC
CS SCCO
468
10121416
3PLrsquos
carb
on em
issio
nre
duct
ion
4 5 6 7 8 9 103c3
(d)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
45505560657075
M1rsquos
selli
ng q
uant
ity
(e)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
455055606570
M2rsquos
selli
ng q
uant
ity
(f)
SSCCCS
SCCO
3000
4000
5000
6000
7000
M1rsquos
pro
fit
4 5 6 7 8 9 103c3
(g)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
4000
5000
6000
7000
8000
M2rsquos
pro
fit
(h)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
2500
3500
4500
5500
R1rsquos
profi
t
(i)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
3000
4000
5000
6000
R2rsquos
profi
t
(j)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
1500
1700
1900
2100
3PLrsquos
pro
fit
(k)
SSCCCS
SCCO
4 5 6 7 8 9 103c3
16000
20000
24000
Supp
ly ch
ainrsquo
s pro
fit
(l)
Figure 6 Effect of c3 on the equilibrium quantities
Mathematical Problems in Engineering 17
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
6 8 10 12 14
9
10
11
12
13
14
tm
M1rsquos
gre
enne
ss d
egre
e
SSCCCS
SCCO
(a)
100
110
120
130
M1rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(b)
100
110
120
130
140
M2rsquos
who
lesa
le p
rice
6 8 10 12 14tm
SSCCCS
SCCO
(c)
6
8
10
12
3PLrsquos
carb
on em
issio
nre
duct
ion
6 8 10 12 14tm
SSCC
CS SCCO
(d)
45
50
55
60
65
70M
1rsquos se
lling
qua
ntity
6 8 10 12 14tm
SSCCCS
SCCO
(e)
50
55
60
65
M2rsquos
selli
ng q
uant
ity
6 8 10 12 14tm
SSCCCS
SCCO
(f )
3500
4500
5500
M1rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(g)
4500
5500
6500
M2rsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(h)
3000
4000
5000
R1rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(i)
2500
3500
4500
R2rsquos
prof
it
6 8 10 12 14tm
SSCCCS
SCCO
(j)
1500
2000
2500
3PLrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(k)
17000
19000
21000
23000
Supp
ly ch
ainrsquos
pro
fit
6 8 10 12 14tm
SSCCCS
SCCO
(l)
Figure 7 Effect of tm on the equilibrium quantities
18 Mathematical Problems in Engineering
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
πCOm1 lt π
SCm1 lt π
CCm1 lt π
CSm1
πCOm2 lt π
CSm2 lt π
CCm2 lt π
SCm2
πCSr1 lt π
CCr1 lt π
SCr1 and πSS
r1 lt πCOr1 lt π
SCr1
πSCr2 lt πCCr2 lt π
CSr2 and πSSr2 lt π
CCr2 lt π
CSr2
min πSS3 πCO31113872 1113873ltmin πCS
3 πSC31113872 1113873lt πCC
3
πCOgsc lt π
SSgsc ltmin πCS
gsc πSCgsc1113872 1113873lt πCC
gsc
(29)
From equation (29) we suggest the following managerialinsight
671 Insight 7 )e CO distribution channel structure is theworst in terms of the profitability of manufacturers Whilethe competition between manufacturers is maintained in themarket the cooperation between retailers adversely affectsthe manufacturersrsquo profits For each retailer the best dis-tribution channel structure is that one manufacturer choosesa single channel while the other chooses a cross channel Bydoing so retailers can maximize their selling quantities andprofits If both manufacturers choose cross-channels thetotal shipments of green and nongreen products are max-imized thus maximizing the 3PLrsquos profit Figures 2ndash7 showthat for each supply chain member the optimal distributionchannel structure is different However our numerical ex-periments suggested that for sustainability and profitabilityof the supply chain the CC structure is best
7 Conclusion
In this study we discussed the equilibrium decisions ofpricing the greenness degree and carbon emission reduc-tion efforts in a three-echelon supply chain consisting of twocompeting manufacturers two retailers and one third-partylogistics firm Under Cournot competition by the manu-facturers we assumed five different distribution channelstructures established a three-stage game model for each ofthem and solved the models analytically Finally extensivenumerical experiments were conducted to investigate theeffects of the parameters on the equilibrium quantities Ourfindings reveal that competition between the two manu-facturers promotes not only sustainability but also profit-ability of the supply chain As the competition becomesmore intense a green product becomes greener leading toincreases in the sales volumes of both green and nongreenproducts In short competition is one of the main factorsincreasing the sustainability and profitability of the supplychain We also found that each member of the supply chainprefers a different distribution channel structure Howeverfor the overall profit of the supply chain manufacturerslearned that choosing a cross-distribution channel is anadvantage over other distribution channel structures )econtributions of this study to the literature on the greenproduct market are as follows (i) )is study is the first toaddress the effects of single and cross-distribution channelsin a market where green and nongreen products coexist (ii)
)is study identifies a strategy that can be used by a 3PL firmto reduce its carbon emissions under single and cross-dis-tribution channels of a green product (iii) )e study pro-vides guidelines to those making strategic decisions formanufacturers of green products and 3PL firms when theyattempt to reduce their carbon footprint )e results of thisstudy can also help policymakers to devise a variety ofmonetary benefit policies such as subsidies for greenproducts andor carbon tax exemptions
Several future research studies related to this topic arepossible One can modify our supply chain model to con-sider collusion behavior between manufacturers Deter-mining how such collusion affects equilibrium decisions andthe selection of the distribution channel can be an interestingextension of this study Another extension is to apply thenewsvendor model to retailers While this paper assumesthat the retailers sell all products that they ordered theassumption of uncertain demands for green and nongreenproducts is more realistic )is type of stochastic demandmay lead to different results Finally this paper assumed noshipping cost between retailers and consumers Howeverthe distance means and speed of transportation betweenretailers and consumers can affect the efforts made by a 3PLfirm to reduce their carbon emission levels Consideringthose aspects can serve a possible extension of this study
Appendix
A1 α1 2 minus β21113872 1113873 + α2β minus tr(2 minus β) 1 minus β21113872 1113873
A2 α2 2 minus β21113872 1113873 + α1β minus tr(2 minus β) 1 minus β21113872 1113873
A3 λ1 2 minus β21113872 1113873 minus βλ2
A4 βλ1 minus λ2 2 minus β21113872 1113873
A5 2tm +A1
1 minus β2+μeSS(2 minus β)
1 minus β
A6 2tm +A2
1 minus β2+μeSS(2 minus β)
1 minus β
A7 64 minus 84β2 + 21β4 minus β6
B1 α1 minus tr(1 minus β)
B2 α2 minus tr(1 minus β)
C1 α1 + α2β minus tr 1 minus β21113872 1113873
C2 2α1 minus α2β minus tr 2 minus 3β + β21113872 1113873
D1 2α2 minus α1β minus tr 2 minus 3β + β21113872 1113873
D2 α1β + α2 minus tr 1 minus β21113872 1113873
(A1)
Mathematical Problems in Engineering 19
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
Data Availability
No data were used to support this study
Conflicts of Interest
)e author declares that there are no conflicts of interest
References
[1] IPCC Fourth Assessment Report IPCC Geneva Switzerland2007 httpswwwipccchassessment-reportar4
[2] UNDRR ldquoTerminology on disaster risk reductionrdquo UNDRRGeneva Switzerland 2017 httpswwwunisdrorgweinformterminology
[3] O Ampuero and N Vila ldquoConsumer perceptions of productpackagingrdquo Journal of Consumer Marketing vol 23 no 2pp 100ndash112 2006
[4] C S E Bale N J Mccullen T J Foxon A M Rucklidge andW F Gale ldquoModeling diffusion of energy innovations on aheterogeneous social network and approaches to integrationof real-world datardquo Complexity vol 19 no 6 pp 83ndash94 2014
[5] A Biswas and M Roy ldquoGreen products an exploratory studyon the consumer behaviour in emerging economies of theEastrdquo Journal of Cleaner Production vol 87 pp 463ndash4682015
[6] F Taghikhah A Voinov and N Shukla ldquoExtending thesupply chain to address sustainabilityrdquo Journal of CleanerProduction vol 229 pp 652ndash666 2019
[7] R B Handfield S V Walton L K Seegers and S A MelnykldquoldquoGreenrdquo value chain practices in the furniture industryrdquoJournal of OperationsManagement vol 15 no 4 pp 293ndash3151997
[8] A A Hervani M M Helms and J Sarkis ldquoPerformancemeasurement for green supply chain managementrdquo Bench-marking An International Journal vol 12 no 4 pp 330ndash3532005
[9] C Lau ldquoBenchmarking green logistics performance with acomposite indexrdquo Benchmarking An International Journalvol 18 pp 873ndash896 2011
[10] A Parmigiani R D Klassen and M V Russo ldquoEfficiencymeets accountability performance implications of supplychain configuration control and capabilitiesrdquo Journal ofOperations Management vol 29 no 3 pp 212ndash223 2011
[11] J Sarkis ldquoA boundaries and flows perspective of green supplychain managementrdquo Supply Chain Management An Inter-national Journal vol 17 no 2 pp 202ndash216 2012
[12] C-T Zhang and L-P Liu ldquoResearch on coordinationmechanism in three-level green supply chain under non-cooperative gamerdquo Applied Mathematical Modelling vol 37no 5 pp 3369ndash3379 2013
[13] C-T Zhang H-X Wang and M-L Ren ldquoResearch onpricing and coordination strategy of green supply chain underhybrid production moderdquo Computers amp Industrial Engi-neering vol 72 pp 24ndash31 2014
[14] Y Huang and S Wang ldquoMulti-level green supply chaincoordination with different power structures and channelstructures using game-theoretic approachrdquo in Proceedings ofthe World Congress on Engineering and Computer Sciencevol 2 San Francisco CA USA October 2018
[15] S R Madani and M Rasti-Barzoki ldquoSustainable supply chainmanagement with pricing greening and governmental tariffsdetermining strategies a game-theoretic approachrdquo Com-puters amp Industrial Engineering vol 105 pp 287ndash298 2017
[16] W Zhu and Y He ldquoGreen product design in supply chainsunder competitionrdquo European Journal of Operational Re-search vol 258 no 1 pp 165ndash180 2017
[17] H Song and X Gao ldquoGreen supply chain game model andanalysis under revenue-sharing contractrdquo Journal of CleanerProduction vol 170 pp 183ndash192 2018
[18] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channelsupply chainsrdquo Journal Of Cleaner Production vol 170pp 1029ndash1043 2018
[19] J Heydari K Govindan and A Aslani ldquoPricing and greeningdecisions in a three-tier dual channel supply chainrdquo Inter-national Journal of Production Economics vol 217 pp 185ndash196 2019
[20] K Rahmani and M Yavari ldquoPricing policies for a dual-channel green supply chain under demand disruptionsrdquoComputers amp Industrial Engineering vol 127 pp 493ndash5102019
[21] Z Hong and X Guo ldquoGreen product supply chain contractsconsidering environmental responsibilitiesrdquo Omega vol 83pp 155ndash166 2019
[22] T W McGuire and R Staelin ldquoAn industry equilibriumanalysis of downstream vertical integrationrdquo Marketing Sci-ence vol 2 no 2 pp 161ndash191 1983
[23] S C Choi ldquoPrice competition in a duopoly common retailerchannelrdquo Journal of Retailing vol 72 no 2 pp 117ndash1341996
[24] R Moner-Colonques J J Sempere-Monerris and A Urbanoldquo)e manufacturersrsquo choice of distribution policy undersuccessive duopolyrdquo Southern Economic Journal vol 70no 3 pp 532ndash548 2004
[25] C Wu and S Mallik ldquoCross sales in supply chains anequilibrium analysisrdquo International Journal of ProductionEconomics vol 126 no 2 pp 158ndash167 2010
[26] J Bian X Guo and K W Li ldquoDistribution channel strategiesin a mixed marketrdquo International Journal of ProductionEconomics vol 162 pp 13ndash24 2015
[27] J Bian X Guo and KW Li ldquoDecentralization or integrationdistribution channel selection under environmental taxationrdquoTransportation Research Part E Logistics and TransportationReview vol 113 pp 170ndash193 2018
[28] J Nie L Zhong H Yan andW Yang ldquoRetailersrsquo distributionchannel strategies with cross-channel effect in a competitivemarketrdquo International Journal of Production Economicsvol 213 pp 32ndash45 2019
[29] J Bian X Zhao and Y Liu ldquoSingle vs cross distributionchannels with manufacturersrsquo dynamic tacit collusionrdquo In-ternational Journal of Production Economics vol 220p 107456 2019
[30] A A Tsay and N Agrawal ldquoModeling conflict and coordi-nation in multi-channel distribution systems a reviewrdquoHandbook of Quantitative Supply Chain Analysis pp 557ndash606 Kluwer Academic Publishers Berlin Germany 2004
[31] O Alp N K Erkip and R Gullu ldquoOptimal lot-sizingvehicle-dispatching policies under stochastic lead times and stepwisefixed costsrdquo Operations Research vol 51 no 1 pp 160ndash1662003
[32] A V Vasiliauskas and G Jakubauskas ldquoPrinciple and benefitsof third party logistics approach when managing logisticssupply chainrdquo Transport vol 22 no 2 pp 68ndash72 2007
[33] K Li A I Sivakumar and V K Ganesan ldquoAnalysis andalgorithms for coordinated scheduling of parallel machinemanufacturing and 3PL transportationrdquo International
20 Mathematical Problems in Engineering
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21
Journal of Production Economics vol 115 no 2 pp 482ndash4912008
[34] M A Ulku and J H Bookbinder ldquoOptimal quoting of de-livery time by a third party logistics provider the impact ofshipment consolidation and temporal pricing schemesrdquoEuropean Journal of Operational Research vol 221 no 1pp 110ndash117 2012
[35] U5 Gurler O Alp and N Ccedil Buyukkaramikli ldquoCoordinatedinventory replenishment and outsourced transportation op-erationsrdquo Transportation Research Part E Logistics andTransportation Review vol 70 pp 400ndash415 2014
[36] C Cheng ldquoMechanism design for enterprise transportationoutsourcing based on combinatorial auctionrdquo in Proceedingsof the the 11th International Conference on Service Systems andService Management pp 25ndash27 Beijing Germany June 2014
[37] Y Suzuki ldquoA new truck-routing approach for reducing fuelconsumption and pollutants emissionrdquo Transportation Re-search Part D Transport and Environment vol 16 no 1pp 73ndash77 2011
[38] P De Giovanni and G Zaccour ldquoA two-period game of aclosed-loop supply chainrdquo European Journal of OperationalResearch vol 232 no 1 pp 22ndash40 2014
[39] X Zhu A Garcia-Diaz M Jin and Y Zhang ldquoVehicle fuelconsumption minimization in routing over-dimensioned andoverweight trucks in capacitated transportation networksrdquoJournal of Cleaner Production vol 85 pp 331ndash336 2014
[40] E Bazan M Y Jaber and S Zanoni ldquoSupply chain modelswith greenhouse gases emissions energy usage and differentcoordination decisionsrdquo Applied Mathematical Modellingvol 39 no 17 pp 5131ndash5151 2015
[41] T Maiti and B C Giri ldquoA closed loop supply chain underretail price and product quality dependent demandrdquo Journalof Manufacturing Systems vol 37 pp 624ndash637 2015
[42] J Li Q Su and L Ma ldquoProduction and transportationoutsourcing decisions in the supply chain under single andmultiple carbon policiesrdquo Journal of Cleaner Productionvol 141 pp 1109ndash1122 2017
[43] M-B Jamali and M Rasti-Barzoki ldquoA game theoretic ap-proach to investigate the effects of third-party logistics in asustainable supply chain by reducing delivery time and carbonemissionsrdquo Journal of Cleaner Production vol 235 pp 636ndash652 2019
[44] X Chen X Wang and M Zhou ldquoFirmsrsquo green RampD co-operation behaviour in a supply chain technological spilloverpower and coordinationrdquo International Journal Of ProductionEconomics vol 218 pp 118ndash134 2019
[45] L Xu CWang and H Li ldquoDecision and coordination of low-carbon supply chain considering technological spillover andenvironmental awarenessrdquo Scientific Reports vol 7 pp 1ndash142017
[46] J Gao H Han L Hou and H Wang ldquoPricing and effortdecisions in a closed-loop supply chain under differentchannel power structuresrdquo Journal of Cleaner Productionvol 112 pp 2043ndash2057 2016
Mathematical Problems in Engineering 21