Analyzing private communities on Internet-based collaborative transportation networks

www.elsevier.com/locate/tre

Transportation Research Part E 43 (2007) 21–38

Analyzing private communities on Internet-basedcollaborative transportation networks

Rahul Kale a,*, Philip T. Evers b, Martin E. Dresner b

a Coggin College of Business, University of North Florida, Jacksonville, FL 32224, United Statesb Robert H. Smith School of Business, University of Maryland, College Park, MD 20742, United States

Received 22 March 2005; received in revised form 21 June 2005; accepted 11 July 2005

Abstract

The establishment of private communities on Internet-based transportation networks is a relatively newtrend that has met with mixed success. Within industry, there has been uncertainty over the costs and ben-efits of these communities to shippers and carriers. Through a theoretical model based on assumptionsderived from industry executives, this paper suggests that shippers may indeed benefit by establishing pri-vate communities. Further, the results show that in high-trust relationships carriers may be no worse off bycooperating with shippers in their private communities.� 2005 Elsevier Ltd. All rights reserved.

Keywords: Collaborative transportation networks; Internet business models; Transportation management; Shipper–carrier relationships

1. Introduction

The Internet offers a wide range of opportunities for conducting business. Some Internet com-panies operate as extensions of ‘‘brick and mortar’’ firms (for example, barnesandnoble.com)while others represent types of businesses that would not have been possible prior to the advent

1366-5545/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.doi:10.1016/j.tre.2005.07.004

* Corresponding author. Tel.: +1 904 620 1107.E-mail address: [email protected] (R. Kale).

http://barnesandnoble.com

mailto:[email protected]

22 R. Kale et al. / Transportation Research Part E 43 (2007) 21–38

of the Internet (for example, on-line database services such as Lexis-Nexus that deliver electronictext directly to end users). One new business category that has been facilitated by the Internet iselectronic marketplaces. Although the best known of these marketplaces, ebay.com, caters mainlyto consumers, other electronic marketplaces operate primarily in the business-to-business setting.

An electronic marketplace is defined as an inter-organizational information system where buy-ers and sellers can meet to conduct business. Thus, a marketplace is a form of intermediary thatestablishes electronic links between buyers and sellers interested in conducting transactions (Cho-udhury et al., 1998). Internet marketplaces in existence include Covisint in the automobile indus-try, Travelocity in the airline industry, and The Seam in the cotton industry. Several electronicmarkets operate in the logistics field, bringing together buyers and sellers in such areas as trans-portation, warehousing, and manufacturing (e.g., Descartes Systems Group, Manhattan Associ-ates, National Transportation Exchange, Nistevo, Transplace).

The purpose of this paper is to model a transportation exchange and demonstrate its potentialbenefits and costs. In particular, the costs and benefits of ‘‘collaborative communities’’ to shippersand carriers are analytically explored. Collaborative communities are formed within transporta-tion exchanges and facilitate the sharing of information between shippers and/or carriers.

2. Transportation exchanges

Transportation exchanges are Internet services that bring together buyers (shippers) and sellers(carriers) of transportation services in order to increase the efficiency of both shipper and carrieroperations. One way these exchanges benefit shippers is that they allow a larger number of carriersto bid for shipments, thereby increasing supply competition and reducing prices. Carriers, too,may benefit from transportation exchanges by gaining access to a large pool of shippers, allowingfor increased capacity utilization and reducing ‘‘dead-hauls’’. Anecdotal accounts suggest that by2001, there were as many as 100–250 transportation exchanges operating on the Internet (Pink-ham, 2001).

As with many other dot-com businesses, transportation exchanges have not been universallysuccessful. Among the reasons most often cited for their failure are that shippers and carriersuse the exchanges to transact only a small percentage of shipments and that shippers prefer tosend loads via their trusted contract carriers rather than rely on Internet-facilitated spot marketexchanges (Pinkham, 2001; Cooke, 2001). As well, carriers are reluctant to participate in transpor-tation exchanges in order to avoid reducing their businesses to ‘‘commodity’’ status, thereby erod-ing profit margins.

To increase their viability, some transportation exchanges have focused on facilitating existingrelationships between shippers and carriers, using the market to supplement, rather than replace,existing relationships. A number of success stories have been reported in the trade press (c.f., Han-non, 2003). For example, Transplace.com, a technology-oriented third party logistics provider,manages the transportation for participating shippers by analyzing shipping lanes and identifyingopportunities to combine loads across shippers. Transplace.com terms this concept ‘‘collaborativetransportation management’’ (CTM). According to Esper and Williams (2003, p. 55), ‘‘CTMessentially involves converting order forecasts developed via CPFR [Collaborative Planning,Forecasting and Replenishment] into shipment forecasts, and insuring their accurate fulfillment’’.

http://ebay.com

http://Transplace.com

http://Transplace.com

R. Kale et al. / Transportation Research Part E 43 (2007) 21–38 23

A term that is sometimes used to describe Internet-based collaborative services is ‘‘collaborativetransportation networks’’. These networks (e.g., NTE.com or Nistevo.com) allow shippers andcarriers to create ‘‘private communities’’ to better manage their transportation needs and re-sources. Depending on the rules of the community, shippers may share shipment information withtheir core carriers and/or participating shippers, in order to increase capacity utilization and re-duce short shipments (c.f., Cooke, 2001; Cullen, 2001). Participating shippers can also identifybackhaul opportunities for their contract carriers and, in turn, get a price break from the carriers(Strozniak, 2003).

During discussions with industry officials regarding collaborative transportation networks, itwas noted that no general rules govern all private communities. In certain instances, the ownerof the community sets the rules, whereas in others cases the rules are set through open discussionsbetween the participating shippers and/or carriers. However, based on these same discussions, itwas concluded that collaborative transportation communities can generally be classified into threecategories as shown in Fig. 1.

The first is a ‘‘shippers� community’’. Typically, a shippers� community is geared towardsimproving the transportation performance of shippers. Shippers may share information on ship-ping requirements. If one shipper has extra needs, it can negotiate with a second shipper that hasexcess contracted capacity, thus creating cost savings for both shippers. The first shipper may re-ceive below-market prices for carrier capacity, while the second shipper may avoid defaulting withits contract carrier for reneging on contracted capacity.

With neutral exchanges, shippers and carriers may participate together in sharing informationon shipping requirements and capacity availability (e.g., Cooke, 2001). Though these communitiesmay be owned by shippers, neutral communities typically strive to benefit all of the participatingparties. Therefore, carriers may achieve higher capacity utilization and shippers fewer short ship-ments through the sharing of information on neutral exchanges.

Finally, it is conceivable that carriers could create carriers� communities to manage their rela-tionships with shippers. Although no such arrangements (of which the authors are aware) cur-rently exist, these communities would involve carriers sharing capacity and shipmentinformation for their own benefit.

4S

5S

C4

C5

Shippers’ Community Carriers’ Community Neutral Community

C3

S2

S3

C1

S1

C2

1C1S

Shipper Carrier Information flow

Fig. 1. General classification of on-line communities on transportation exchanges.

http://NTE.com

http://Nistevo.com


3. Literature review and research questions

Internet-based collaborative logistics networks are relatively new; consequently, very little aca-demic literature deals directly with such networks. In the only relevant research paper found onthe topic, Golicic and Davis (2003) presented a case study based on one such network. Though allof the participating shippers and carriers agreed that there were benefits to participating in thesenetworks, none were able to definitively establish whether they were, on the whole, better off bydoing so. Many aspects of collaborative communities are, however, similar to existing literature atthe intersection of supply chain management and Internet operations. As a consequence, relevantresearch efforts from these fields and their implications for collaborative logistics communities arebriefly noted below.

A private collaborative community formed between a shipper and its carrier base is quite sim-ilar to an inter-organizational system (IOS). There have been several studies in the literatureshowing that information sharing between firms through an IOS results in improved performance.For instance, Internet-based collaboration between online retailers of music compact discs andtheir vendors may result in reduced inventory levels and cycle time for the same level of customerservice. A consumer-direct-fulfillment arrangement between online retailers and their vendorsmay be facilitated through an IOS (Rabinovich, 2005). As Internet-based retailing facilitatesthe de-coupling of customer-order locations and inventory locations, online retailers may makebetter use of inventory location speculation and postponement strategies to improve inventorymanagement (Bailey and Rabinovich, 2005). Electronic data interchange is one of the more com-mon methods of establishing an information sharing relationship between two firms and has beenshown to lead to reductions in inventory carrying costs, obsolete inventory, and emergency ship-ments (c.f., Mukhopadhyay et al., 1995). In addition, an IOS enables various supply chain initia-tives such as Vendor Managed Inventory, Quick Response, Continuous Replenishment Planning,and Efficient Consumer Response. These programs have also been shown to result in reducedinventories, higher fill rates, shorter order cycles, reduced transaction costs, reduced transporta-tion costs, and improved customer service (c.f., Waller et al., 1999; Lee et al., 1999; Daughertyet al., 1999).

Though an IOS often leads to increased efficiencies, there are some issues that should be care-fully considered by firms when evaluating their implementation. While information sharing be-tween firms creates efficiencies, there is the potential for asymmetric benefits in which one firmreceives a larger share of the gains than the other. Indeed, one firm may benefit at the expenseof the other firm as adoption of an IOS could expose firms to the risks of opportunism or exploi-tation. A few conceptual papers allude to this possibility (e.g., Kumar et al., 1996; Premkumar,2000). Given the potential for vastly varying benefits, participating parties may actually resistthe implementation to enter IOS-based collaborative efforts (e.g., Clemons and Row, 1993).

Examples of collaborative transportation networks creating win–win scenarios for shippers andcarriers have been presented in the trade press. Given their potential to add value for shippers andcarriers, it is interesting to ask why these networks are not commonly employed. It may be thatfirms are unaware of the benefits of participating in these networks. Or perhaps, firms are reluc-tant to share information with competitors, customers, and/or suppliers. In this paper, the con-ditions under which shippers and carriers are likely to be better (or worse) off by participatingin a collaborative transportation network are investigated.


Based on the above discussion, the following questions are considered:

1. As shippers (and carriers) form private collaborative communities on Internet-based collab-orative networks, will such communities create efficiencies in shipper–carrier operations and,if so, by what means?

2. Is there a potential for asymmetric benefits, where one party may gain more than the other,depending upon the information sharing arrangement between them?

3. Is it possible that one party may benefit at the expense of the other?4. Considering the above aspects, what are the conditions under which private communities are

beneficial to shippers and to carriers?

4. Shipper performance model

The models presented below are from a shipper�s point of view. Similar implications arise forcarriers. However, to avoid repetitive discussions, those implications will be merely stated whereappropriate without presenting modeling details.

4.1. The modeling framework

Consider a shipper–carrier dyad where the shipper has fairly stable transportation requirementsbetween a pair of locations. One of the most common methods by which a shipper handles suchrequirements is to enter into a contract with a carrier. Both the shipper and carrier commit to aparticular volume (q units, perhaps based on the average requirements of the shipper) and trans-portation rate (T per unit).

Once the contract is set, day-to-day transactions ensue. A carrier sends a vehicle to the shipperwith carrying capacity of q units. The shipper then tenders the shipment quantity of q units. How-ever, occurrences are seldom deterministic. On a given day, either the shipper�s requirements (S)or the carrier�s availability (C) may deviate from q. If either C or S is greater than q, the excessmay be handled via the spot transportation market. However, if C is less than q, then the shippersuffers in the form of either delayed shipments or lost sales. If S is less than q, then the shipper mayend up either paying for unused capacity or paying for default penalties.

With a conventional contractual relationship, the carrier becomes aware of the actual shipperrequirements only when the carrier arrives at the shipper�s dock. Similarly, the shipper becomesaware of the carrier�s actual capacity only when the carrier arrives at the shipper�s dock. By thetime a party is aware of a contract default, it may be too late to take remedial actions. There-fore, the party suffers in terms of either delayed delivery, lost sales, or reduced capacity utili-zation.

For this model, it is assumed that any shipments that cannot be made due to unavailable car-rying capacity result in lost sales, while all shipments that do get shipped produce sales revenues(i.e., they are sold at a price of P per unit). It is further assumed that, if a shipper fails to provide qunits, the shipper pays a penalty to the carrier for each unit of shipment defaulted (Ps per unit).Similarly, if a carrier defaults on its contracted capacity, it pays a penalty to the shipper for eachunit of capacity it is short (Pc per unit). Any requirements or available capacity above the contractquantity are transacted through the spot market, composed of all other shippers and carriers, at a


transportation rate of Ts per unit. It is assumed that the spot market is made up of a large numberof shippers and carriers; thus, the spot market price is independent of the shipping requirements(or available capacity) of any individual shipper (or carrier). To summarize the notation:

Contract quantity = q (units),Contract transport price = T ($/unit),Carrier penalty = Pc ($/unit),Shipper penalty = Ps ($/unit),Shipper�s selling price = P ($/unit),Shipper random requirement ¼ S ðunitsÞ with density f ðSÞ and c.d.f. F ðSÞ ¼

R s0 f ðtÞdt,

Carrier random availability ¼ C ðunitsÞ with density gðCÞ and c.d.f. GðCÞ ¼R c

0gðtÞdt, and

Spot market transport price ¼ T s ð$=unitÞ with density hðT sÞ and c.d.f. HðT sÞ ¼R T s

0 hðtÞdt.

Shipper performance is measured by computing gross shipper profits as follows:

Fig. 2whileromancontrathe cocapacgreate

Gross profit ¼ sales revenue� transportation cost� carrier penalty received=paid.

4.2. Conventional transportation management

Given the modeling framework described above, there are four possible scenarios, shown inFig. 2. In Case IA, both the shipper and the carrier default on the contract, however the shipper�s

S

C

II

IVIII

IB

IA

q

q

. Possible shipper–carrier transaction scenarios. Note: The X-axis represents shipper�s shipping requirements (S),the Y-axis represents the carrier�s capacity (C). q is the contract volume between the shipper and the carrier. The

numerals enumerate all possibilities in a shipper–carrier transaction: IA: Both shipper and carrier default on thect, however, S > C. IB: Both shipper and carrier default on the contract, however, S < C. II: Carrier defaults onntract while shipper requirements are greater than the contract. III: Shipper defaults on the contract while carrierity is greater than the contract. IV: Both shipper and carrier honor the contract and have requirements/capacityr than the contract.


requirements are greater than the carrier�s available capacity (a numerical example is given in Table1). Thus, the shipper loses sales while the carrier pays a default penalty to the shipper for the capac-ity deficit. Referring to Table 1, the shipper loses sales of 20 units, while the carrier pays a penalty tothe shipper for 20 units of lost sales (i.e., the difference between requirements and capacity).

Using the gross profit expression, the shipper�s profits for Case IA in a conventional system is asfollows:

TableCase e

Case

IAIBIIIIIIV

S ProfitIAconventional ¼

Z s

c¼0

Z q

s¼0

fP � c� c � T þ ðs� cÞ � P cgf ðsÞgðcÞdsdc. ð1Þ

The first two terms measure sales revenues and transportation cost, respectively, while the thirdterm represents the penalty paid by the carrier to the shipper, as the carrier defaults on the con-tract in this case.

In Case IB, both the shipper and the carrier default on the contract. However, in this case, thecarrier�s carrying capacity is greater than the shipper�s shipping requirements. In the specificexample shown in Table 1, the carrier incurs 20 units of unutilized capacity. The shipper compen-sates the carrier by paying a penalty for these 20 unused units. The following equation gives ship-per profits in Case IB:

S ProfitIBconventional ¼

Z q

c¼s

Z q

s¼0

fP � s� T � s� ðc� sÞ � P sgf ðsÞgðcÞdsdc. ð2Þ

The first two terms again indicate the sales revenues and transportation cost, respectively, whereasthe third term now gives the penalty paid by the shipper to the carrier, as the shipper defaults onthe contract in this case.

In Case II, the carrier defaults on the contract while the shipper�s requirements are greater thanthe contract quantity. Since the shipper knows beforehand that its requirements are greater thanthe contract quantity, it arranges for spot transportation for the requirements above the contractquantity (in the example, 50 units). However, as the carrier defaults on the contract by 30 units, andsince the shipper does not know in advance that the carrier is going to default, the shipper cannotuse the spot market for the default quantity and loses sales equal to the carrier default. The carrierpays the shipper a penalty for this loss. The following equation measures shipper profits in Case II:

S ProfitIIconventional ¼

Z q

c¼0

Z 1

s¼qfP � c� T � cþ ðq� cÞ � P c

þZ P

T s¼0

fðs� qÞ � ðP � T sÞghðtsÞdtsgf ðsÞgðcÞdsdc. ð3Þ

1xamples for shipper–carrier transactions (contract quantity = 100 units)

Shipper requirements Carrier capacity

70 5050 70

150 7070 150

150 150


The first three terms in Eq. (3) represent the revenues, transportation cost, and the default paid bythe carrier to the shipper. The last, innermost integral gives the revenues earned by the shipper byplacing shipments in excess of the contract quantity through the spot market.

In Case III, the shipper defaults on the contract while the carrier�s capacity is greater than thecontracted amount. In this case, due to the shipper default, the carrier loses revenues equal to theshipment price for 30 units. The shipper pays a penalty to compensate for these 30 units of unuti-lized carrier space. Excess capacity above the contracted amount is sold on the spot market by thecarrier (50 units). Shipper profits in Case III are as follows:

S ProfitIIIconventional ¼

Z 1

c¼q

Z q

s¼0

fP � s� T � s� ðq� sÞ � P sgf ðsÞgðcÞdsdc. ð4Þ

Finally, in Case IV, both the shipper�s requirements and the carrier�s capacity are greater thanthe contracted amount. Thus, both are able to honor the contract. The shipper sells the shipmentsabove the contract quantity (50 units) through the spot market, while the carrier sells its excesscapacity on the spot market (50 units). The following equation gives shipper profits for Case IV:

S ProfitIVconventional ¼

Z 1

c¼q

Z 1

s¼qP � q� T � qþ

Z P

T s¼0

fðs� qÞ � ðP � T sÞghðtsÞdts

� �f ðsÞgðcÞdsdc.

ð5Þ
The total expected shipper profits ðS Profittotal
conventionalÞ using conventional shipping methods un-der all cases is given by the sum of all the five expressions:

S Profittotalconventional ¼ S ProfitIA

conventional þ S ProfitIBconventional þ S ProfitII

conventional

þ S ProfitIIIconventional þ S ProfitIV

conventional.

The revenue and cost coefficients derived from Eqs. (1)–(5) are shown in Table 2, under the col-umn heading ‘‘Conventional Transaction’’. It is assumed that a shipper will only ship productsthrough the spot market if the spot market price for carrier capacity, Ts, is less than or equal tothe profit made by selling the product, P. For the sake of convenience, this is shown in Table 2 sim-ply by multiplying the units that the shipper plans to send through the spot market by the per unitexpected revenues earned by the shipper on these excess units. The term E(Profit)spot indicates theexpected per unit profit earned by the shipper by shipping excess units through the spot market.

4.3. Shippers� community

Before examining performance on a shippers� community, it is necessary to characterize ship-per–carrier relationships as either ‘‘low-trust’’ or ‘‘high-trust’’. A high-trust relationship is onewhere the shipper–carrier pair has a long standing contract and both parties are concerned aboutmaintaining this relationship. A low-trust relationship is one where the shipper and carrier arefocused only on their own short-term performance. As described below, the degree of trust inthe relationship will affect default quantities and thus profit performance.

By using a shippers� community and thereby obtaining information about carrier capacitiesprior to shipments being tendered, a shipper obtains two benefits. First, the shipper may be ableto default its contract carrier without the possibility of recourse (shown in Case IA). In this case,

Table 2Coefficients for shipper and carrier profit functions

Case Conventional system Shippers� exchange Carriers� exchange Neutral exchange

IA P * c � T * c + (s � c) * Pc P * c � T * c + (q � c) * Pc + (s � c)

* (P � Ts) * E(Profit)spot (LT)P * c � T * c + (s � c) * Pc P * c � T * c + (s � c)

* Pc + (s � c) * (P � Ts)

* E(Profit)spotorP * c � T * c + (s � c) * Pc + (s � c)

* (P � Ts) * E(Profit)spot (HT)

IB P * s � T * s � (c � s) * Ps P * s � T * s � (c � s) * Ps P * s � T * s � (q � s)

* Ps (LT)P * s � T * s � (c � s)

* Ps

orP * s � T * s � (c � s) * Ps (HT)

II P * c � T * c + (q � c) * Pc

+ (s � q) * (P � Ts) * E(Profit)spot

P * c � T * c + (q � c) * Pc + (s � c)

* (P � Ts)

* E(Profit)spot

P * c � T * c + (q � c)

* Pc + (s � q) *(P � Ts)

* E(Profit)spot

P * c � T

* c + (q � c) * Pc

+ (s � c) * (P � Ts)

* E(Profit)spot

III P * s � T * s � (q � s) * Ps P * s � T * s � (q � s) * Ps P * s � T * s � (q � s) * Ps P * s � T * s

� (q � s) * Ps

IV P * q � T * q + (s � q)

* (P � Ts) * E(Profit)spot

P * q � T * q + (s � q)


P * q � T * q + (s � q)


P * q � T * q

+ (s � q) * (P � Ts)

* E(Profit)spot

Note: (LT) = low-trust shipper–carrier relationship; (HT) = high-trust shipper–carrier relationship.

R.

Ka

leet

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ran

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both the shipper and the carrier default on the contract, but the shipper�s requirements are greaterthan the carrier�s capacity. In a ‘‘low-trust’’ relationship, a shipper may default a carrier againstthe contract quantity, instead of the actual shipment quantity tendered by the shipper (see Fig. 3).This is termed an ‘‘unfair’’ default, and in a high-trust relationship this default would not becharged. Using the example from Table 1, in Case IA, a shipper penalizes a carrier by 50 units(i.e., defaulting the carrier against the contract) instead of penalizing the carrier by the fairamount of 20 units (i.e., the actual lost sales for the shipper).

A second benefit of shippers� communities to shippers is that with the advance knowledge of car-rier capacity, a shipper may be able to make better use of the spot market. This may happen whenthe carrier defaults on its contract and the shipper�s requirements are greater than the carrier�scapacity (i.e., in Cases IA and II). In Case IA (Fig. 3), both the shipper and the carrier defaulton the contract, however the shipper�s requirements are greater than the carrier�s capacity. Underconventional contracting, a shipper would lose sales due to the carrier default (20 units, in Table 1example). On a shippers� exchange, the shipper would have prior information on carrier capacityand would, therefore, know in advance that the carrier is going to default on the contract. With thisadvance knowledge, the shipper can plan to send a shipment equal to the carrier�s default quantity(20 units) through the spot market, assuming the shipper earns positive profits (P > Ts).

The profit equation for Case IA in a shippers� exchange can be stated as follows:

Fig. 3requirIn a ctrustmay d

S ProfitIAshippers’ exchange ¼

Z s

c¼0

Z q

s¼0

�P � c� T � cþ ðq� cÞ � P c

þZ P

T s¼0

fðs� cÞ � ðP � T sÞghðtsÞdts

�f ðsÞgðcÞdsdc. ð6Þ

770

IBq

q

Carrier default on a shippers’ exchange

IA

III

II

IV

Carrier default in a conventional transaction

C

550

S

. Case IA: Shippers� exchange vs. conventional method. Note: Considering Case IA from Table 1, the shipper�sements (S) are 70 units and the carrier�s capacity (C) is 50 units. Thus, both default on the contract though S > C.onventional transaction, the carrier would be liable to the shipper for 20 units of lost sales. However, in a low-relationship on a shippers� exchange, since the carrier does not know the actual shipper requirements, a shipperefault the carrier by 50 units instead of the fair default of 20 units.


The last term (innermost integral) in Eq. (6) represents the revenues earned by the shipper fromsending the default quantity through the spot market. In the case of a shippers� exchange, thecoefficient for the carrier�s default is (q � c) instead of (s � c) as it is under conventional contract-ing. The difference represents the unfair default (q � c) � (s � c) = (q � s) which a shipper mayearn on a shippers� exchange in a low-trust relationship (equal to 30 units in the example givenin Table 1).

In a high-trust relationship, however, shipper profits on a shippers� exchange in Case IA are asfollows:

Fig. 4requirsales oremaiknowlthis si

S ProfitIAshippers’ exchange ¼

Z s

c¼0

Z q

s¼0

�P � c� T � cþ ðs� cÞ � P c

þZ P

T s¼0



For a high-trust relationship, it is assumed that the default quantity is the fair quantity. Theshipper�s earnings from the spot market are the same as in Eq. (6), while the carrier penalty isthe same as in the conventional method (Eq. (1)).

In Case II (see Fig. 4), the shipper�s requirements are above the contract quantity and the car-rier defaults on the contract. The shipper may benefit from advance information about the car-rier�s capacity and send all of its goods in excess of carrier capacity through the spot market(80 units in the example), instead of just the quantity above the contract (50 units). The shipperprofits in this case are as follows:

70

150

q

q

IA

IB

III

Spot market sales in aconventional transa

Lost sales in aconventional transaction

Spot market sales on a shipper’s exchange

II

IV

C

S

ction

. Case II: Shippers� exchange vs. conventional method. Note: Considering Case II from Table 1, the shipper�sements (S) are 150 units and the carrier�s capacity (C) is 70 units. In a conventional transaction, the shipper losesf 30 units (carrier capacity shortage) and sells 50 units in excess of the contract through the spot market. The

ning 70 units are shipped by the contract carrier. However, on a shippers� exchange, a shipper has advanceedge of the carrier default and can plan to also ship the default units (30 units) through the spot market. Thus, intuation, the shipper ships 80 units through the spot market and avoids losing any sales.


S ProfitIIshippers’ exchange ¼

Z q

c¼0

Z 1

s¼q

�P � c� T � cþ ðq� cÞ � P c

þZ P

T s¼0



The difference between this equation and Eq. (3) is the coefficient for the quantity of shipmentssent through the spot market. In the case of the conventional transaction (Eq. (3)), only thoseshipments above the contract quantity may be sent through the spot market (s � q). However,in the case of a shippers� exchange (Eq. (8)), a shipper may send all of the goods in excess of carriercapacity through the spot market (s � c).

In the other cases (Case IB, Case III, and Case IV), there is no difference in the shipper profitequations between the shippers� exchange and the conventional approach. In Case IB both theshipper and its contract carrier default on the contract with the carrier capacity being greater thanthe shipper requirement. The shipper sends its shipments via the carrier (50 units, using the examplefrom Table 1) and pays a default penalty to the carrier (for 20 units) to compensate the carrier fornot using all available capacity (20 out of 70 units). In Case III, the shipper defaults on the contractand the carrier�s availability exceeds the contract quantity. The shipper sends its complete shipmentthrough the contract carrier (70 units) and pays default penalties to the carrier to compensate forthe default quantity (30 units). And in Case IV, both the shipper and the carrier honor the contract.

Based on this discussion, the outcomes in Cases IB, III, and IV are identical to the correspond-ing cases using the conventional approach. The following expressions summarize the profitsearned under the various assumptions:

S ProfitIBshippers’ exchange ¼ S ProfitIB

conventional;

S ProfitIIIshippers’ exchange ¼ S ProfitIII

conventional; and

S ProfitIVshippers’ exchange ¼ S ProfitIV

conventional.

The total expected shipper�s profits ðS Profittotalshippers’ exchangeÞ using a shippers� exchange is given

by the sum of all five expressions

S Profittotalshippers’ exchange ¼ S ProfitIA

shippers’ exchange þ S ProfitIBshippers’ exchange þ S ProfitII

shippers’ exchange

þ S ProfitIIIshippers’ exchange þ S ProfitIV

shippers’ exchange.

The shipper�s performance under other information sharing options (carriers� exchange andneutral exchange) may be similarly stated by integrating the appropriate coefficients in Table 2under the applicable limits. Given the similarity between obtaining these equations and those de-scribed in detail above, shipper performance expressions for the neutral and carrier�s communitiesare not presented here.

4.4. Shipper performance comparisons

The total expected shipper profits on a shippers� exchange less the total expected shipper profitsusing the conventional method ðS Profittotal

shippers’ exchange � S ProfittotalconventionalÞ in a low-trust relation-

ship is equal to:


Z s

c¼0

Z q

s¼0

ðq� sÞ � P c þZ P

T s¼0


� �f ðsÞgðcÞdsdc

� �

þZ q

c¼0

Z 1

s¼q

Z P

T s¼0

fðq� cÞ � ðP � T sÞghðtsÞf ðsÞgðcÞdtsdsdc� �

. ð9Þ

The first term represents the difference in shipper performance in Case IA, while the second termrepresents the shipper performance difference in Case II. As noted above, shipper performance inall other cases (IB, III, and IV) are the same under the two approaches. The first term representsthe unfair default earned by the shipper on a shippers� exchange (30 units in Table 1) and the netrevenues earned by the shipper from sending the shipments not covered by the defaulting carriervia the spot market (20 units in Table 1). The second term indicates that in Case II, a shipper mayearn more spot market revenues on a shippers� exchange than in a conventional system. Access toreal-time information regarding a carrier�s available capacity explains the differential earnings. Ona shippers� exchange, the shipper knows in advance that the carrier is going to default on the con-tract. Hence, a shipper is able to send these default quantities through the spot market (30 units inTable 1).

In the case of a high-trust relationship, a shipper only earns fair default penalties from its con-tract carrier. In this case, the difference between shipper profits on a shippers� exchange and usinga conventional approach ðS Profittotal

shippers’ exchange � S ProfittotalconventionalÞ is shown as follows:

Z s

c¼0

Z q

s¼0

Z P

T s¼0

fðs� cÞ � ðP � T sÞghðtsÞf ðsÞgðcÞdtsdsdc� �

þZ q

c¼0

Z 1

s¼q

Z P

T s¼0

fðq� cÞ � ðP � T sÞghðtsÞf ðsÞgðcÞdtsdsdc� �

. ð10Þ

The first term represents the difference in performance in Case IA, while the second term repre-sents the performance difference in Case II. As noted earlier, in all other cases (IB, III, and IV)there are no profit differences between the two approaches. The first term represents the spot mar-ket revenues earned in Case IA by sending the shipments not covered by the defaulting carrier (20units in Table 1). The second term indicates that a shipper earns more spot market revenues on ashippers� exchange than under the conventional method in Case II.

Both Eqs. (9) (low-trust) and (10) (high-trust), yield a positive quantity. Therefore,S Profittotal

shippers’ exchange > S Profittotalconventional or:

Proposition. Shipper performance, as measured by profits, is higher on a shippers� community thanthrough the conventional method of transportation management.

Other comparisons, between (1) conventional method and neutral community, (2) conventionalmethod and carriers� community, (3) shippers� community and neutral community, (4) shippers�community and carrier�s community, and (5) carriers� community and neutral community, aresimilar in logic to the comparison discussed above and are briefly outlined in Appendix A.

Based on this analysis (a numerical example is presented in Appendix B), in the case of low-trust relationships, shipper performance in various collaborative transportation networks ranks,from best to worst, as follows: (1) shippers� community, (2) neutral community, (3) conventional


method, (4) carriers� community. In high-trust relationships, the ranking is: (1–2) shippers� andneutral community (tie), (3–4) conventional method and carriers� community (tie).

Rankings for carrier performance in low-trust relationships are: (1) carrier�s community, (2)neutral community, (3) conventional method, (4) shippers� community and finally, in high-trustrelationships, the ranking of carrier performance is: (1–2) carrier�s and neutral community (tie),(3–4) conventional method and shippers� community (tie).

5. Conclusions, implications and limitations

The establishment of private communities on Internet-based transportation networks is a rel-atively new trend that has met with mixed success. Within industry, there has been uncertaintyover the costs and benefits of these communities to shippers and carriers. Through a theoreticalmodel based on assumptions derived from industry executives, this paper suggests that shippersmay indeed benefit by establishing private communities. The benefits arise from two sources:(1) the ability to use advance information on available capacity to better use the spot market,and (2) the ability in low-trust relationships to penalize carriers by the full value of carrier de-faults, rather than by the fair value. These ‘‘unfair’’ defaults reflect the potential that a carriermay be made worse off by participating in an online transportation community and may explainthe hesitation among carriers to participate in such communities. On the other hand, the resultsshow that in high-trust relationships carriers are no worse off by cooperating with shippers in theirprivate communities.

The findings suggest that carriers entering into collaborative communities should push for asmuch transparency in exchange relationships as possible in order to benefit from the communities.In situations where shippers face hesitancy on the part of contract carriers to participate in col-laborative exchanges, shippers may need to create incentives for the carriers to participate. Thisfinding conforms with evidence in the trade literature showing that in some cases, shippers paycarrier membership fees for participation in collaborative communities (Cooke, 2001).

A number of simplifying assumptions have been made with this model. One of the assumptionsis that penalties for non-compliance with contract terms are made through default payments foreach shipment in which a default occurs. However, in some collaborative arrangements, defaultpayments may not be assessed on a shipment basis. To a large extent, the results may still apply.For example, suppose the carrier does not have the capacity promised to the shipper. Based ondiscussions with executives of logistics networks, the shipper may rate the carrier on the network�suser feedback system based upon its experience. When other shippers pick carriers for their owntransportation needs, they use this rating as one of their selection criteria. Thus, if a carrier de-faults with its contract shipper, the carrier�s future business may be adversely affected. The defaultpenalty can be interpreted, in a broad sense, similar to a ‘‘stockout penalty’’ in inventory manage-ment and used to operationalize the negative implications of the carrier not fulfilling its contractterms.

A second assumption is that transportation rates are linear with respect to volume. In actuality,a carrier may have a schedule of rates with breaks depending on shipment volumes. Therefore,carrying capacity may not be easily or costlessly transferred between shippers. It is further as-sumed that the spot market is independent of the two parties under consideration. This assump-


tion requires a spot market composed of a large number of shippers and carriers. As a result,small numbers of firms cannot influence the price of the spot market. In practice, however, itmay be common that on particular transportation lanes only a handful of carriers offer service,so that one or two carriers can clearly affect the spot market price.

Appendix A. Summary of analytical results

(1) S Profittotalshippers’ exchange > S Profittotal

conventional.

(2) S Profittotalcarriers’ exchange < S Profittotal

conventional, in a low-trust relationship, and

S Profittotalcarriers’ exchange ¼ S Profittotal

conventional, in a high-trust relationship.

(3) S Profittotalneutral exchange > S Profittotal

conventional.


carriers’ exchange.


neutral exchange, in a low-trust relationship, and

S Profittotalshippers’ exchange ¼ S Profittotal

neutral exchange, in a high-trust relationship.

(6) S Profittotalcarriers’ exchange < S Profittotal

neutral exchange.

For low-trust relationships, the following rankings are obtained from 1 and 2:

S Profittotalshippers’ exchange > S Profittotal

conventional > S Profittotalcarriers’ exchange, and from 3 and 5:


neutral exchange > S Profittotalconventional. Hence, in a low-trust relation-

ship: S Profittotalshippers’ exchange > S Profittotal

neutral exchange > S Profittotalconventional > S Profittotal


For high-trust relationships, the following rankings are obtained from 1 and 2:


conventional ¼ S Profittotalcarriers’ exchange, and from 3 and 5:

S Profittotalshippers’ exchange ¼ S Profittotal

neutral exchange > S Profittotalconventional. Hence, in a high-trust relation-

ship: S Profittotalshippers’ exchange ¼ S Profittotal

neutral exchange > S Profittotalconventional ¼ S Profittotal


Appendix B. Numerical example1

The shipper profit expressions found in this article for the various transportation managementoptions were solved using ‘‘Matlab’’ software. A few numerical examples of shipper profits aregiven below for a shippers� community, a carriers� community, a neutral community, and the con-ventional method. Table B1 shows the input parameters used in these examples, while Table B2shows the baseline case—shipper profits in a conventional transaction.

1 The authors would like to thank Kuldeep Amarnath for his help in solving the equations using the Matlabsoftware.

Table B3Shipper profits on a shippers� exchange in a low-trust environment

Carrier mean Shipper mean IA IB II III IV Total

80 80 1055.30 440.59 465.64 159.85 80.95 2202.3480 100 873.81 229.73 1514.70 149.37 264.03 3031.6480 120 324.32 55.60 2691.40 57.01 471.19 3599.52100 80 377.12 363.51 268.52 503.76 255.13 1768.04100 100 354.30 224.27 874.30 470.74 832.10 2755.71100 120 141.18 61.21 1556.00 179.66 1485.00 3423.06120 80 71.36 134.13 83.75 847.68 429.30 1566.21120 100 74.03 92.20 272.85 792.11 1400.20 2631.39120 120 31.26 27.21 486.02 302.31 2498.70 3345.51

Table B1Input parameters

Symbol Variable Values

Q Contract size between primary shipper–carrier 100 unitsT Per unit cost of transportation $50/unitPc Carrier penalty per unit of default $20/unitPs Shipper penalty per unit of default $40/unitP Shipper�s selling price per unit of product $80/unitTs (random) Spot market transportation price per unit Normal, mean 100, SD 60

(or 100, 60)S (random) Primary shipper�s requirements Normal, with following values (80, 20),

(100, 20), (120, 20)C (random) Contract carrier�s capacity Normal, with following values (80, 20),

(100, 20), (120, 20)

Table B2Shipper profits in a conventional transaction


80 80 806.61 440.59 394.92 159.85 80.95 1076.3180 100 688.74 229.73 1291.80 149.37 264.03 1934.9380 120 259.90 55.60 2316.40 57.01 471.19 2900.20100 80 309.92 363.51 242.47 503.76 255.13 1364.87100 100 297.73 224.27 792.20 470.74 832.10 2319.31100 120 120.14 61.21 1417.80 179.66 1485.00 3143.67120 80 61.42 134.13 78.31 847.68 429.30 1489.42120 100 64.68 92.20 255.70 792.11 1400.20 2540.21120 120 27.56 27.21 457.17 302.31 2498.70 3285.40


B.1. Shippers’ exchange

In a low-trust environment, shipper profits on a shippers� exchange are given in Table B3. Com-pared to the conventional method, shipper profits are greater in Case IA (as the shipper earns

Table B4Shipper profits on a shippers� exchange in a high-trust environment


80 80 936.51 440.59 465.64 159.85 80.95 2083.5580 100 806.67 229.73 1514.70 149.37 264.03 2964.5180 120 306.50 55.60 2691.40 57.01 471.19 3581.70100 80 343.15 363.51 268.52 503.76 255.13 1734.06100 100 331.32 224.27 874.30 470.74 832.10 2732.73100 120 134.30 61.21 1556.00 179.66 1485.00 3416.17120 80 66.20 134.13 83.75 847.68 429.30 1561.05120 100 69.97 92.20 272.85 792.11 1400.20 2627.33120 120 29.91 27.21 486.02 302.31 2498.70 3344.16


opportunistic defaults and sends all remaining shipments through the spot market) and Case II (asthe shipper sends all remaining shipments through the spot market).

In a high-trust environment, shipper profits on a shippers� exchange are shown in Table B4.Compared with shipper profits on a shippers� exchange in a low-trust environment, profits in CaseIA are now lower, as the shipper does not earn any unfair default penalties from its contractcarrier.

B.2. Neutral exchange

Since shipper profits on a neutral exchange are identical to shipper profits on a shippers� ex-change in a high-trust environment, no table is presented.

B.3. Carriers’ exchange

Shipper profits on a carriers� exchange in a low-trust environment are given in Table B5. Com-pared with the conventional method, shipper profits are less in Case IB, as the carrier earns oppor-tunistic default penalties from the shipper. In all other cases, shipper profits in a low-trustenvironment are the same as the conventional method.

Table B5Shipper profits on a carriers� exchange in a low-trust environment


80 80 806.61 202.53 394.92 159.85 80.95 1644.8680 100 688.74 161.22 1291.80 149.37 264.03 2555.1680 120 259.90 45.01 2316.40 57.01 471.19 3149.51100 80 309.92 228.62 242.47 503.76 255.13 1539.90100 100 297.73 177.53 792.20 470.74 832.10 2570.30100 120 120.14 52.72 1417.80 179.66 1485.00 3255.32120 80 61.42 98.17 78.31 847.68 429.30 1514.88120 100 64.68 78.02 255.70 792.11 1400.20 2590.72120 120 27.56 24.32 457.17 302.31 2498.70 3310.06


Lastly, in a high-trust environment, shipper profits on a carriers� exchange are the same as theconventional method, so no table is presented in this final case.

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Analyzing private communities on Internet-based collaborative transportation networks

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