Research ArticleSelection of Key Component Vendor from the Aspects ofCapability Productivity and Reliability

Vincent F Yu1 Catherine W Kuo2 and Luu Quoc Dat13

1 Department of Industrial Management National Taiwan University of Science and Technology No 43 Sec 4 Keelung RoadTaipei 10607 Taiwan

2Graduate Institute of Management National Taiwan University of Science and Technology No 43 Sec 4 Keelung RoadTaipei 10607 Taiwan

3 Faculty of Development Economics University of Economics and Business Vietnam National UniversityNo 144 XuanThuy Road Cau Giay District Hanoi 10000 Vietnam

Correspondence should be addressed to Catherine W Kuo ckworldwide66gmailcom

Received 16 March 2014 Revised 2 June 2014 Accepted 8 June 2014 Published 2 July 2014

Academic Editor W Y Szeto

Copyright copy 2014 Vincent F Yu et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

In a technology-driven industry the appropriate vendorssuppliers can effectively contribute to cobusiness development profits Keycomponent vendors help dynamically drive solution design firms to achieve strong performances especially when an integratedcircuit (IC) component that has technical know-how specifications dominates an electronic solution design This paper presents asystematic framework to examine the decision process for the selection of wireless fidelity (Wi-Fi) IC vendor alternatives from thebusiness ecosystem aspect in order to review the importance of buyer-supplier synergistic effects We implement the fuzzy analytichierarchy process technique which incorporates a vendorrsquos capability productivity and reliability characteristics into a hierarchicalstructure and deploys decision expertsrsquo judgments along with vague data analysis to solve a real-world problem faced by a leadingcompany specialized in the research and design of wireless networking solutions The findings indicate the Taiwanese local vendoris the top priority for alternatives selection and the results contribute significant values to the design firmrsquos operation management

1 Introduction

In the information communication and technology (ICT)industry where technological specifications are phased intoan electronic device the issues of suppliersrsquo competitiveadvantages are measured more in depth than the terms andconditions of pricecost productservice quality or deliveryA key component vendor as part of business supply chaincells is devoted to technological skills so as to achieve marketdriven requirements When a Wi-Fi IC component adoptstechnological specifications deploys a solution design-intechnique dominates 12 of a main board cost and evenshares 13 of the bill-of-material (BOM) cost in one wirelessnetworking device the decision to purchase or replace a keycomponent is more than just a bargaining power negotiationconducted by a single procurement department

Several research studies have released results on theimpacts of vendorsrsquo (suppliersrsquo) characteristics under differ-ent industrial viewpoints so as to examine and measure the

selection of vendorsupplier alternatives Appropriate ven-dorssuppliers can effectively contribute to cobusiness devel-opment profits especially in technology-driven industriesClose buyer-supplier relationships can share business infor-mation and technology development trends [1] During theproduct development stage the decision to integrate prod-uct architecture with a supply chain design is significantlyimportant for industries [2] Thus matching new productfeature developments with the choice of suppliers can impactfirm performance for example when solutions contain newelectronic components and new process techniques in theautomotive industry [3] The stable delivery of goods andtechnology ability are the top two criteria for selecting sup-pliers in the electronics industry [4] Product quality is onedistinct examination attribute of suppliers when outsourcingtechnological specification products that are applied duringa procurement decision process analysis for railway parts [5]Buyersrsquo operations can be severely impacted due to suppliersrsquo

Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2014 Article ID 124652 7 pageshttpdxdoiorg1011552014124652

2 Mathematical Problems in Engineering

reliability to deliver on time in this outsourced supply chainmanagement era [6] Even appropriate vendor alternativesare implemented when evaluating the quality of productdurability in steel component selection [7] For a notebookmanufacturer the lowest unit cost of an outsourcedTFT-LCDpart is not the first priority for an appropriate supplier [8]whereas for product cost effectiveness quality stability andon-time delivery concerns a garment manufacturing firmrsquostop management evaluates appropriate suppliers through itsRampD marketing and purchasing departmentsrsquo evaluationfeedback [9]

This paper measures and analyzes one Wi-Fi IC vendorrsquosalternatives by looking at the tactics within the enterprisersquosorganizational culture as well as operationmanagement char-acteristics in the wireless networking communications indus-try Following a review of knowledgeable product designengineers project managersrsquo judgments and salespersonsrsquofeedback we find some significant impact factors classifiedas follows (i) sensitivity to market competition the abilitiesof up-to-date advanced technology and the skills of financialmanagement through vendorsrsquo competitiveness capabilities(ii) the fact that product price justifies flexibility productionoutput arrangement and inventory planning management ofvendorsrsquo performance (iii) the confidence in componentsrsquoquality and delivery as well as the risk management of thevendors

Fuzzy analytic hierarchy process which was first pro-posed by [10] has become one of the most widely used toolsformultiple criteria decisionmaking (MCDM)The literaturehas proposed numerous fuzzy analytic hierarchy process(AHP) methods to solve various types of problems [11ndash19]Among the existing AHP approaches the extent analysismethod proposed by [12] is a commonly used approach thatis highly cited and has wide applications The AHP method-ology is utilized to demonstrate a hierarchical structure andto examine the weights of the decision elements reviewedand evaluated by experts while the proposed fuzzy AHPtechnique can effectively consider the vagueness of decisionmakersrsquo opinions on the ranking of alternative suppliersThisstudy applies the fuzzy AHP technique proposed by [12]to incorporate a vendorrsquos capability productivity and relia-bility characteristics into a hierarchical structure to deploydecision expertsrsquo judgment and also implements vague dataanalysis

The remainder of the paper is organized as followsSection 2 presents the research background along with therelated literature Section 3 proposes the fuzzy analytic hier-archy process methodology Section 4 applies the fuzzy AHPmethodology to the selection ofWi-Fi IC component vendoralternatives Finally Section 5 draws conclusions and discus-sions

2 Literature Review

Maximizing profits through cost-expenditure minimizationis the fundamental philosophy of a corporate operationmanagement strategy but reviewing the related influentialelements is an essential and critical process For amore global

industrial environment the issue on firmsrsquo competitionadvantage always stresses their operation and the contribu-tion from suppliersrsquo expertise and how it affects the firmsrsquosuccess Through firmsrsquo synergistic effects suppliersrsquo corecompetence can be integrated into new product design andbusiness development with the benefits being cost reductionand time efficiency Reference [20] highlights the impor-tance of high-tech business success through the synergisticresolution of strategic network effects while [21] examinesthe contribution of IT resource synergy to organizationalperformance and how competitiveness is substantial andflourishing In a technology-driven industry and marketenvironment the outsourced solutions from knowledgeablesuppliers present systematic impacts related to the develop-ment of productsprojects Reference [22] indicates that astrong relationship with suppliers can result in new productdevelopment outsourcing being controlled quite well intechnology-intensive markets Under a complete businessdevelopment ecosystem buyers (customersusers) and sup-pliers (solutionservice providers) are interdependent in avalue-added supply chain network Reference [23] shows thatthe partner selection of direct suppliers is one of the impor-tant success factors for the core business of a mobile businessecosystem Reference [24] analyzes the effect of early supplierinvolvement on project teamrsquos effectiveness Through newprojectproduct developersrsquo and contributorsrsquo coordinationin their supply chain team involvement continual customervalue creation can be achieved Reference [25] points outthat a demand and supply integration mechanism plays atremendous role due to intrateamsrsquo knowledge integrationandmanagement Reference [26] provides insights of coordi-nation between new product development and supply chainmanagement for value creation

Several research studies look at some factors affectingvendor selection criterion as analyzed by the fuzzy set theoryand AHP approaches Reference [13] indicates that steel qual-ity cost and delivery issues for a metal manufacturing com-pany are the major measurement criteria of supplier selec-tion implemented on electronic marketplaces Reference [17]identifies and measures suppliersrsquo technical ability variablefor a washing machine case research on supplier selectionReference [19] concludes that vendorsrsquo financial positionquality and delivery are the top three factors for a multicrite-ria supplier segmentation evaluation applied to a case analysisin the food industry Reference [27] addresses capabilitiesof suppliersrsquo financial technical and production factors thataffect a health product firmrsquos decision on supplier evaluationand selection Furthermore the risks from geographical loca-tion and political and economical stability impact supplierselection [28] and outsourcing risk management due toeconomic environmental crises [29] while the criteria ofrisk in inventory control management [30] are prime factorsacross suppliers and buyers Reference [31] proposes a fuzzylogic approach to supplier evaluation for development

In the electronics industry special material vendorssup-pliers mostly play the key role in devoting their capabilitiesproductivities and reliabilities to support the final prod-uctsolution providers during the new product design or newproject development phases Reference [18] notes that the

Mathematical Problems in Engineering 3

Table 1 Characteristics released on the vendorsupplier selectionreferencesCharacteristics ReferencesDelivery [1 4 6ndash9 13 17 19 27 28]Costprice [1 4 7ndash9 13 17ndash19 27ndash29 32]Quality [1 4 5 7 9 13 17ndash19 27ndash29 32 33]Technology [1 4 7 17 27 33]Risk [1 18 28]Production [4 7 17 27]Finance [4 5 7 17 19 32]Inventory [6 30]

cost criterion is the first priority of concern followed byquality service and risk for a Taiwanese digital consumermanufacturer to select its global suppliers Reference [32]addresses an evaluation process of supplier selection andfirmly identifies technique capability as well as design anddevelopment ability as the two major influential elements inprofessional technology for one electronic manufacturer Inthe initial stage of new product development [33] indicatesthat quality reliability and technological capability are impor-tant subcriteria factors adopted for plastic injection vendorselection by a personal digital assistant (PDA) developerTable 1 reviews the characteristics in the vendorsupplierselection Reference [34] uses a qualitative embedded single-case strategy in shipbuilding industry to explore the impor-tance of supplier capabilities in one shipyard and examineshow consistently the shipyard and its 20 suppliers assess thecapabilities of the suppliers

3 Fuzzy Analytic HierarchyProcess Methodology

This study adopts the extent analysis method proposed by[12] due to its computational simplicity The extent analysismethod is briefly discussed as follows

Let 119883 = 1199091 1199092 119909

119899 be an object set and let 119880 =

1199061 1199062 119906

119898 be a goal set According to [12] each object is

taken and an extent analysis for each goal (119892119894) is performed

respectively Therefore the 119898 extent analysis values for eachobject are obtained as 1198721

1198921198941198722

119892119894 119872

119899

119892119894 119894 = 1 2 119899

where 119872119895119892119894(119895 = 1 2 119898) are triangular fuzzy numbers

(TFNs)Assume that 119872119895

119892119894are the values of extent analysis of the

119894th object for119898 goalsThe value of fuzzy synthetic extent 119878119894is

defined as

119878119894=

119898

sum

119895=1

119872119895

119892119894otimes [

[

119899

sum

119894=1

119898

sum

119895=1

119872119895

119892119894

]

]

minus1

(1)

where sum119898119895=1

119872119895

119892119894= (sum119898

119895=1119897119895 sum119898

119895=1119898119895 sum119898

119895=1119906119895 ) 119895 = 1 2

119898 119894 = 1 2 119899Let119872

1= (1198971 1198981 1199061) and119872

2= (1198972 1198982 1199062) be two TFNs

whereby the degree of possibility of 1198721ge 1198722is defined as

follows

119881 (1198721ge 1198722) = sup119909ge119910

[min (1205831198721

(119909) 1205831198722

(119909))] (2)

y

x0

M1M2

m1m2

D

l1l2 u1u2d

V(M2 ge M1)

Figure 1 The comparison of two fuzzy numbers

The membership degree of possibility is expressed as

119881 (1198721ge 1198722) = ℎ119892119905 (119872

1cap1198722) = 1205831198722

(119889)

=

1 if 1198981ge 1198982

0 if 1198971ge 1199062

1198971minus 1199062

(1198982minus 1199062) minus (119898

1minus 1198971)

otherwise

(3)

where 119889 is the ordinate of the highest intersection point oftwo membership functions 120583

1198721(119909) and 120583

1198722(119909) as shown in

Figure 1The degree of possibility for a convex fuzzy number to be

greater than 119896 convex fuzzy numbers is defined as

119881 (119872 ge 11987211198722 119872

119896) = min119881 (119872 ge 119872

119894)

119894 = 1 2 119896

(4)

The weight vector is given by

1198821015840= (1198891015840(1198601) 1198891015840(1198602) 119889

1015840(119860119899))119879

(5)

where

119860119894(119894 = 1 2 119899) 119889

1015840(119860119894) = min119881 (119878

119894ge 119878119896)

119896 = 1 2 119899 119896 = 119894

(6)

Via normalization we obtain the weight vectors as

119882 = (119889(1198601) 119889(119860

2) 119889(119860

119899))119879

(7)

where119882 is a nonfuzzy numberIn this present case Changrsquos method [12] is applied to

solve a vendor selection and evaluation problem We adopt aldquoLikert scalerdquo of fuzzy numbers starting from 1 to 9 to trans-form the linguistic values into TFNs as shown in Table 2

4 The Empirical Case Analysis

To awireless networking technology-driven firm the intrare-lationship management with its vendors is conducted

4 Mathematical Problems in Engineering

Table 2 Triangular fuzzy conversation scale [11]

Linguistic values Triangular fuzzynumbers

Reciprocal triangularfuzzy scale

(1) Unimportant (U) (1 1 1) (1 1 1)(2) Between U and SL (1 2 3) (13 12 1)(3) Slightly important (SL) (2 3 4) (14 13 12)(4) Between SL and MI (3 4 5) (15 14 13)(5) Moderately important (MI) (4 5 6) (16 15 14)(6) Between MI and SI (5 6 7) (17 16 15)(7) Seriously important (SI) (6 7 8) (18 17 16)(8) Between SI and VSI (7 8 9) (19 18 17)(9) Very seriously important (VSI) (8 9 9) (19 19 18)

Table 3 Fuzzy AHP analysis of key Wi-Fi component IC vendorsrsquo evaluation and selection

Criteria Definition Subcriteria Definition

Capability (1198621)

Expertise andexperiences related tocompetitiveness

Market sensitivitylowast (MS-11986211) To meet market trends and customer

requirements

Technology availability (TA-11986212) To achieve up-to-date technological

specification designFinancial stability (FS-119862

13) To manage financial operation

Productivity (1198622) Flexibilities and

arrangement

Price policy (PP-11986221) To adjust costpricing offerings

Production capacity (PC-11986222) To fulfill just-in-time demand

Inventory strategylowastlowast (IS-11986223) To control materials and allocation of

finished goods

Reliability (1198623)

Accuracy andcommitments onmanagement

Product quality (PQ-11986231) To ensure product performance

On-time delivery (TD-11986232) To arrange delivery schedules

Risk management (RM-11986233) To manage risk factors

Note lowastkey subcriteria for Wi-Fi IC supplier selection lowastlowastmust subcriteria to judge Wi-Fi IC suppliersrsquo performance and management

through global business development so as to overcomethe limitations of technological knowledge To become aqualified key component vendor to fulfill system designersrsquorequirements alternative candidates should be fully and sys-tematically evaluated This research presents a measurementanalysis on a fifty-employee Taiwanese RampD design firmwitha very good track record for five consecutive years in wirelessnetworking solution design The critical decision for thisfirm is to select an appropriate value-added Wi-Fi IC vendorfrom two choices (a) Vendor A is a well-known world-classfirm that specializes in networking computing and mobilesolutions design for home and enterprise users includingapplications utilized on digital homes notebooks tabletsmobile phones mobile routers and so forth (b) Vendor B is apublicly traded IC design company in Taiwan with a broaderrange of high-tech product applications including solutionsfor implementation on computer peripherals communica-tion networks and multimedia Based on a questionnairesurvey feedback from 5 managers (2 electronic engineers 2project managers and one account manager) of each vendorand 7 managers (2 project managers 2 procurement man-agers 1 engineer for firmware 1 electronic engineer and onesales account) of the case studyrsquos design firm received inOcto-ber 2013 we apply a methodology to measure the weights ofthree criteria and nine subcriteria respectively and examinethe weights of the nine subcriteria versus alternatives fromthe final score of fuzzy AHP analysis Table 3 and Figure 2

define the criteria and subcriteria used to evaluate and selectWi-Fi IC vendors

Based on criteria and subcriteria defined in Table 3 and(1)ndash(7) we are able to calculate the importance weights of thecriteria and subcriteria as well as the weights of alternativesversus the subcriteria in Tables 4ndash6

We are now able to obtain the final score of each alterna-tive as Table 7

The data indicates that the vendorrsquos productivity(1198622 055) is a relatively greater concern versus the other

two criteria (see Table 4) On the weights of the subcriteriafinancial stability (119862

13 10) is the most important factor

under the decision choice on the capability term andinventory stability (119862

23 054) and production capability

(11986222 046) impact the greatest upon the productivity issue

while risk management (11986233 052) and on-time delivery

(11986232 048) hold critical weights under the reliability criterion

(see Table 5) For the weights of the two alternatives versusthe nine subcriteria respectively the Fuzzy AHP approachanalysis chooses Vendor B (119860

2 0724 versus119860

1 0276) as the

top priority for alternatives selection (see Tables 6 and 7)

5 Conclusions and Discussions

The selection of key component vendor alternatives involvesmultiple issues that can be systematically examined through

Mathematical Problems in Engineering 5

Table 4 The importance weights of the criteria

Criteria 1198621

1198622

1198623

119882119888

1198621

100 100 100 030 038 048 054 072 087 01198622

208 262 332 100 100 100 055 076 100 0551198623

115 139 184 100 132 180 100 100 100 045

Vendor A Vendor B

MS TA FS PP PC IS PQ TD RM

Selection of the best Wi-Fi IC vendor

Capability Productivity Reliability

Figure 2 Hierarchy of Wi-Fi component IC vendorsrsquo evaluation and selection problem

Table 5 The importance weights of the subcriteria

Subcriteria 11986211

11986212

11986213

119882119888

11986211

100 100 100 096 119 138 033 045 057 011986212

072 084 104 100 100 100 024 031 040 011986213

176 224 300 247 324 424 100 100 100 1Subcriteria 119862

2111986222

11986223

119882119888

11986221

100 100 100 030 040 051 022 028 037 011986222

195 249 331 100 100 100 029 039 047 04611986223

273 356 447 212 259 347 100 100 100 054Subcriteria 119862

3111986232

11986233

119882119888

11986231

100 100 100 020 025 031 025 032 040 011986232

318 400 500 100 100 100 044 057 074 04811986233

247 312 400 135 176 229 100 100 100 052

teamsrsquo analysis under a multicriteria decision process Tar-geting profit maximization a Wi-Fi IC component supplieris driven by a productrsquos bill-of-material (BOM) cost thatresults from the technological specificationsfeatures that arephased in during a new product design stage The insightsfrom this empirical case study identify some important issuesfor the evaluation measurement and analysis actions duringthe decision process for key component vendor selectionin technology-driven industries Through the perspectivesof synergistic effects and business ecosystems we offerthe following key results of our study for industries andacademia (i) The added value of the decision process onWi-Fi IC component vendorsrsquo selection encompasses technologyknow-how the main IC that makes up the main cost ofthe solution main board and the BOM cost performance(ii) The blueprint of the examination factors focuses on

Table 6 The weights of alternatives versus the subcriteria

11988211986211

1198601

1198602

119882119888

1198601

100 100 100 047 059 071 01198602

141 171 212 100 100 100 111988211986212

1198601

1198602

119882119888

1198601

100 100 100 036 049 067 01198602

149 203 276 100 100 100 111988211986213

1198601

1198602

119882119888

1198601

100 100 100 069 087 094 031198602

106 115 144 100 100 100 0711988211986221

1198601

1198602

119882119888

1198601

100 100 100 059 088 117 0441198602

085 113 170 100 100 100 05611988211986222

1198601

1198602

119882119888

1198601

100 100 100 057 076 104 0361198602

096 132 176 100 100 100 06411988211986223

1198601

1198602

119882119888

1198601

100 100 100 053 067 080 01198602

125 150 188 100 100 100 111988211986231

1198601

1198602

119882119888

1198601

100 100 100 043 058 077 0091198602

129 174 235 100 100 100 09111988211986232

1198601

1198602

119882119888

1198601

100 100 100 081 104 119 0521198602

084 096 124 100 100 100 04811988211986233

1198601

1198602

119882119888

1198601

100 100 100 059 079 096 0311198602

104 126 169 100 100 100 069

the evaluation issues of (a) competitiveness capability (b)productivity performance and (c) management reliability(iii) This study bridges gaps in previous research concerning

6 Mathematical Problems in Engineering

Table 7 Final score of each alternative

Alternative Score1198601

02761198602

0724

market sensitivity on market trends and customer require-ments (iv) The key characteristics to look at during the ven-dor selection process come from vendorsrsquo viewpoints and thesolution design firmrsquos examination of the impacts from threecriteria and nine subcriteria (v) The results herein indicatethat the strategic vendor evaluation analysis and report can beused as a reference by a firmrsquos operation management whenplanning a strategy for resource allocation

In an ICT technology-driven and customer-centric busi-ness ecosystem firms need to structure a value chain mech-anism through knowledge sharing network collaborationwith key suppliers and customers The scope and scale offuture research should integrate cross-functional cooperationamong teams to widely investigate the supply chain value ina global and dynamic context Given these issues we notethe following (1) Open innovation (OI) which involves agreater number of ideas knowledge areas and experiencescontributed by external partners is the key antecedent ofstrategic decisions made by firms (2) Knowledge manage-ment (KM) which drives firms by sharing and deployingknowledge to organizations for objective achievement is amultidisciplined theoretical approach suitable for industrialpractitioners in research and analysis Therefore in order tobuild up different research criteria that can be integrated withquantitativemeasurement analysis theories for future studieswe propose research objectives on customer value creationand supply chain value through the use of multipurposemodels

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] AH I Lee ldquoA fuzzy supplier selectionmodelwith the consider-ation of benefits opportunities costs and risksrdquo Expert Systemswith Applications vol 36 no 2 pp 2879ndash2893 2009

[2] B Nepal L Monplaisir and O Famuyiwa ldquoMatching productarchitecture with supply chain designrdquo European Journal ofOperational Research vol 216 no 2 pp 312ndash325 2012

[3] M Pero N Abdelkafi A Sianesi and T Blecker ldquoA frameworkfor the alignment of new product development and supplychainsrdquo Supply Chain Management vol 15 no 2 pp 115ndash1282010

[4] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[5] G Bruno E Esposito A Genovese andR Passaro ldquoAHP-basedapproaches for supplier evaluation problems and perspectivesrdquoJournal of Purchasing and Supply Management vol 18 no 3 pp159ndash172 2012

[6] E Elahi ldquoOutsourcing through competition what is the bestcompetition parameterrdquo International Journal of ProductionEconomics vol 144 no 1 pp 370ndash382 2013

[7] M Punniyamoorthy PMathiyalagan and P Parthiban ldquoA stra-tegic model using structural equation modeling and fuzzy logicin supplier selectionrdquo Expert Systems with Applications vol 38no 1 pp 458ndash474 2011

[8] A H I Lee H Kang and C Chang ldquoFuzzy multiple goal pro-gramming applied to TFT-LCD supplier selection by down-stream manufacturersrdquo Expert Systems with Applications vol36 no 3 pp 6318ndash6325 2009

[9] K Shaw R Shankar S S Yadav and L S Thakur ldquoSupplierselection using fuzzy AHP and fuzzy multi-objective linearprogramming for developing low carbon supply chainrdquo ExpertSystems with Applications vol 39 no 9 pp 8182ndash8192 2012

[10] P J M van Laarhoven and W Pedrycz ldquoA fuzzy extension ofSaatyrsquos priority theoryrdquo Fuzzy Sets and Systems vol 11 no 3 pp229ndash241 1983

[11] K P Anagnostopoulos M Gratziou and A P VavatsikosldquoUsing the fuzzy analytic hierarchy process for selecting waste-water facilities at prefectrure levelrdquo European Water pp 15ndash242007

[12] D Chang ldquoApplications of the extent analysis method on fuzzyAHPrdquo European Journal of Operational Research vol 95 no 3pp 649ndash655 1996

[13] I Chamodrakas D Batis and D Martakos ldquoSupplier selectionin electronic marketplaces using satisficing and fuzzy AHPrdquoExpert Systems with Applications vol 37 no 1 pp 490ndash4982010

[14] C A Bana e Costa and J-C Vansnick ldquoA critical analysis of theeigenvalue method used to derive priorities in AHPrdquo EuropeanJournal of Operational Research vol 187 no 3 pp 1422ndash14282008

[15] O Cakir ldquoOn the order of the preference intensities in fuzzyAHPrdquo Computers and Industrial Engineering vol 54 no 4 pp993ndash1005 2008

[16] LMikhailov ldquoDeriving priorities from fuzzy pairwise compari-son judgementsrdquo Fuzzy Sets and Systems vol 134 no 3 pp 365ndash385 2003

[17] O Kilincci and S A Onal ldquoFuzzy AHP approach for supplierselection in a washing machine companyrdquo Expert Systems withApplications vol 38 no 8 pp 9656ndash9664 2011

[18] C Ku C Chang and H Ho ldquoGlobal supplier selection usingfuzzy analytic hierarchy process and fuzzy goal programmingrdquoQuality and Quantity vol 44 no 4 pp 623ndash640 2010

[19] J Rezaei and R Ortt ldquoMulti-criteria supplier segmentationusing a fuzzy preference relations basedAHPrdquoEuropean Journalof Operational Research vol 225 no 1 pp 75ndash84 2013

[20] S Shim and B Lee ldquoSustainable competitive advantage of asystem goods innovator in a market with network effects andentry threatsrdquo Decision Support Systems vol 52 no 2 pp 308ndash317 2012

[21] J-L Chen ldquoThe synergistic effects of IT-enabled resources onorganizational capabilities and firm performancerdquo Informationand Management vol 49 no 3-4 pp 142ndash150 2012

[22] N Harmancioglu ldquoPortfolio of controls in outsourcing rela-tionships for global new product developmentrdquo IndustrialMarketing Management vol 38 no 4 pp 394ndash403 2009

[23] J Zhang and X Liang ldquoBusiness ecosystem strategies of mobilenetwork operators in the 3G era the case of China MobilerdquoTelecommunications Policy vol 35 no 2 pp 156ndash171 2011

Mathematical Problems in Engineering 7

[24] S J Wu and G L Ragatz ldquoEvaluating the total effect of earlysupplier involvement on project team effectiveness collabora-tion and interactionrdquo International Journal of Integrated SupplyManagement vol 5 no 3 pp 239ndash259 2010

[25] T L Esper A E Ellinger T P Stank D J Flint and M MoonldquoDemand and supply integration a conceptual framework ofvalue creation through knowledge managementrdquo Journal of theAcademy of Marketing Science vol 38 no 1 pp 5ndash18 2010

[26] P Hilletofth and D Eriksson ldquoCoordinating new productdevelopment with supply chain managementrdquo Industrial Man-agement and Data Systems vol 111 no 2 pp 264ndash281 2011

[27] J Roshandel S S Miri-Nargesi and L Hatami-ShirkouhildquoEvaluating and selecting the supplier in detergent productionindustry using hierarchical fuzzy TOPSISrdquo Applied Mathemat-ical Modelling vol 37 no 24 pp 10170ndash10181 2013

[28] A Zouggari and L Benyoucef ldquoSimulation based fuzzy TOPSISapproach for group multi-criteria supplier selection problemrdquoEngineering Applications of Artificial Intelligence vol 25 no 3pp 507ndash519 2012

[29] DWu D DWu Y Zhang and D L Olson ldquoSupply chain out-sourcing risk using an integrated stochastic-fuzzy optimizationapproachrdquo Information Sciences vol 235 pp 242ndash258 2013

[30] Y Kristianto P Helo J R Jiao and M Sandhu ldquoAdaptive fuzzyvendor managed inventory control for mitigating the Bull-whip effect in supply chainsrdquo European Journal of OperationalResearch vol 216 no 2 pp 346ndash355 2012

[31] LOsiro F R Lima-Junior andLC RCarpinetti ldquoA fuzzy logicapproach to supplier evaluation for developmentrdquo InternationalJournal of Production Economics vol 153 pp 95ndash112 2014

[32] Y Chen and R Chao ldquoSupplier selection using consistent fuzzypreference relationsrdquo Expert Systems with Applications vol 39no 3 pp 3233ndash3240 2012

[33] C-Y Shen and K-T Yu ldquoEnhancing the efficacy of supplierselection decision-making on the initial stage of new productdevelopment a hybrid fuzzy approach considering the strategicand operational factors simultaneouslyrdquo Expert Systems withApplications vol 36 no 8 pp 11271ndash11281 2009

[34] I Ruuska T Ahola M Martinsuo and T Westerholm ldquoSup-plier capabilities in large shipbuilding projectsrdquo InternationalJournal of Project Management vol 31 no 4 pp 542ndash553 2013

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Stochastic AnalysisInternational Journal of

2 Mathematical Problems in Engineering

reliability to deliver on time in this outsourced supply chainmanagement era [6] Even appropriate vendor alternativesare implemented when evaluating the quality of productdurability in steel component selection [7] For a notebookmanufacturer the lowest unit cost of an outsourcedTFT-LCDpart is not the first priority for an appropriate supplier [8]whereas for product cost effectiveness quality stability andon-time delivery concerns a garment manufacturing firmrsquostop management evaluates appropriate suppliers through itsRampD marketing and purchasing departmentsrsquo evaluationfeedback [9]

This paper measures and analyzes one Wi-Fi IC vendorrsquosalternatives by looking at the tactics within the enterprisersquosorganizational culture as well as operationmanagement char-acteristics in the wireless networking communications indus-try Following a review of knowledgeable product designengineers project managersrsquo judgments and salespersonsrsquofeedback we find some significant impact factors classifiedas follows (i) sensitivity to market competition the abilitiesof up-to-date advanced technology and the skills of financialmanagement through vendorsrsquo competitiveness capabilities(ii) the fact that product price justifies flexibility productionoutput arrangement and inventory planning management ofvendorsrsquo performance (iii) the confidence in componentsrsquoquality and delivery as well as the risk management of thevendors

Fuzzy analytic hierarchy process which was first pro-posed by [10] has become one of the most widely used toolsformultiple criteria decisionmaking (MCDM)The literaturehas proposed numerous fuzzy analytic hierarchy process(AHP) methods to solve various types of problems [11ndash19]Among the existing AHP approaches the extent analysismethod proposed by [12] is a commonly used approach thatis highly cited and has wide applications The AHP method-ology is utilized to demonstrate a hierarchical structure andto examine the weights of the decision elements reviewedand evaluated by experts while the proposed fuzzy AHPtechnique can effectively consider the vagueness of decisionmakersrsquo opinions on the ranking of alternative suppliersThisstudy applies the fuzzy AHP technique proposed by [12]to incorporate a vendorrsquos capability productivity and relia-bility characteristics into a hierarchical structure to deploydecision expertsrsquo judgment and also implements vague dataanalysis

The remainder of the paper is organized as followsSection 2 presents the research background along with therelated literature Section 3 proposes the fuzzy analytic hier-archy process methodology Section 4 applies the fuzzy AHPmethodology to the selection ofWi-Fi IC component vendoralternatives Finally Section 5 draws conclusions and discus-sions

2 Literature Review

Maximizing profits through cost-expenditure minimizationis the fundamental philosophy of a corporate operationmanagement strategy but reviewing the related influentialelements is an essential and critical process For amore global

industrial environment the issue on firmsrsquo competitionadvantage always stresses their operation and the contribu-tion from suppliersrsquo expertise and how it affects the firmsrsquosuccess Through firmsrsquo synergistic effects suppliersrsquo corecompetence can be integrated into new product design andbusiness development with the benefits being cost reductionand time efficiency Reference [20] highlights the impor-tance of high-tech business success through the synergisticresolution of strategic network effects while [21] examinesthe contribution of IT resource synergy to organizationalperformance and how competitiveness is substantial andflourishing In a technology-driven industry and marketenvironment the outsourced solutions from knowledgeablesuppliers present systematic impacts related to the develop-ment of productsprojects Reference [22] indicates that astrong relationship with suppliers can result in new productdevelopment outsourcing being controlled quite well intechnology-intensive markets Under a complete businessdevelopment ecosystem buyers (customersusers) and sup-pliers (solutionservice providers) are interdependent in avalue-added supply chain network Reference [23] shows thatthe partner selection of direct suppliers is one of the impor-tant success factors for the core business of a mobile businessecosystem Reference [24] analyzes the effect of early supplierinvolvement on project teamrsquos effectiveness Through newprojectproduct developersrsquo and contributorsrsquo coordinationin their supply chain team involvement continual customervalue creation can be achieved Reference [25] points outthat a demand and supply integration mechanism plays atremendous role due to intrateamsrsquo knowledge integrationandmanagement Reference [26] provides insights of coordi-nation between new product development and supply chainmanagement for value creation

Several research studies look at some factors affectingvendor selection criterion as analyzed by the fuzzy set theoryand AHP approaches Reference [13] indicates that steel qual-ity cost and delivery issues for a metal manufacturing com-pany are the major measurement criteria of supplier selec-tion implemented on electronic marketplaces Reference [17]identifies and measures suppliersrsquo technical ability variablefor a washing machine case research on supplier selectionReference [19] concludes that vendorsrsquo financial positionquality and delivery are the top three factors for a multicrite-ria supplier segmentation evaluation applied to a case analysisin the food industry Reference [27] addresses capabilitiesof suppliersrsquo financial technical and production factors thataffect a health product firmrsquos decision on supplier evaluationand selection Furthermore the risks from geographical loca-tion and political and economical stability impact supplierselection [28] and outsourcing risk management due toeconomic environmental crises [29] while the criteria ofrisk in inventory control management [30] are prime factorsacross suppliers and buyers Reference [31] proposes a fuzzylogic approach to supplier evaluation for development

In the electronics industry special material vendorssup-pliers mostly play the key role in devoting their capabilitiesproductivities and reliabilities to support the final prod-uctsolution providers during the new product design or newproject development phases Reference [18] notes that the

Mathematical Problems in Engineering 3

Table 1 Characteristics released on the vendorsupplier selectionreferencesCharacteristics ReferencesDelivery [1 4 6ndash9 13 17 19 27 28]Costprice [1 4 7ndash9 13 17ndash19 27ndash29 32]Quality [1 4 5 7 9 13 17ndash19 27ndash29 32 33]Technology [1 4 7 17 27 33]Risk [1 18 28]Production [4 7 17 27]Finance [4 5 7 17 19 32]Inventory [6 30]

cost criterion is the first priority of concern followed byquality service and risk for a Taiwanese digital consumermanufacturer to select its global suppliers Reference [32]addresses an evaluation process of supplier selection andfirmly identifies technique capability as well as design anddevelopment ability as the two major influential elements inprofessional technology for one electronic manufacturer Inthe initial stage of new product development [33] indicatesthat quality reliability and technological capability are impor-tant subcriteria factors adopted for plastic injection vendorselection by a personal digital assistant (PDA) developerTable 1 reviews the characteristics in the vendorsupplierselection Reference [34] uses a qualitative embedded single-case strategy in shipbuilding industry to explore the impor-tance of supplier capabilities in one shipyard and examineshow consistently the shipyard and its 20 suppliers assess thecapabilities of the suppliers

3 Fuzzy Analytic HierarchyProcess Methodology

This study adopts the extent analysis method proposed by[12] due to its computational simplicity The extent analysismethod is briefly discussed as follows

Let 119883 = 1199091 1199092 119909

119899 be an object set and let 119880 =

1199061 1199062 119906

119898 be a goal set According to [12] each object is

taken and an extent analysis for each goal (119892119894) is performed

respectively Therefore the 119898 extent analysis values for eachobject are obtained as 1198721

1198921198941198722

119892119894 119872

119899

119892119894 119894 = 1 2 119899

where 119872119895119892119894(119895 = 1 2 119898) are triangular fuzzy numbers

(TFNs)Assume that 119872119895

119892119894are the values of extent analysis of the

119894th object for119898 goalsThe value of fuzzy synthetic extent 119878119894is

defined as

119878119894=

119898

sum

119895=1

119872119895

119892119894otimes [

[

119899

sum

119894=1

119898

sum

119895=1

119872119895

119892119894

]

]

minus1

(1)

where sum119898119895=1

119872119895

119892119894= (sum119898

119895=1119897119895 sum119898

119895=1119898119895 sum119898

119895=1119906119895 ) 119895 = 1 2

119898 119894 = 1 2 119899Let119872

1= (1198971 1198981 1199061) and119872

2= (1198972 1198982 1199062) be two TFNs

whereby the degree of possibility of 1198721ge 1198722is defined as

follows

119881 (1198721ge 1198722) = sup119909ge119910

[min (1205831198721

(119909) 1205831198722

(119909))] (2)

y

x0

M1M2

m1m2

D

l1l2 u1u2d

V(M2 ge M1)

Figure 1 The comparison of two fuzzy numbers

The membership degree of possibility is expressed as

119881 (1198721ge 1198722) = ℎ119892119905 (119872

1cap1198722) = 1205831198722

(119889)

=

1 if 1198981ge 1198982

0 if 1198971ge 1199062

1198971minus 1199062

(1198982minus 1199062) minus (119898

1minus 1198971)

otherwise

(3)

where 119889 is the ordinate of the highest intersection point oftwo membership functions 120583

1198721(119909) and 120583

1198722(119909) as shown in

Figure 1The degree of possibility for a convex fuzzy number to be

greater than 119896 convex fuzzy numbers is defined as

119881 (119872 ge 11987211198722 119872

119896) = min119881 (119872 ge 119872

119894)

119894 = 1 2 119896

(4)

The weight vector is given by

1198821015840= (1198891015840(1198601) 1198891015840(1198602) 119889

1015840(119860119899))119879

(5)

where

119860119894(119894 = 1 2 119899) 119889

1015840(119860119894) = min119881 (119878

119894ge 119878119896)

119896 = 1 2 119899 119896 = 119894

(6)

Via normalization we obtain the weight vectors as

119882 = (119889(1198601) 119889(119860

2) 119889(119860

119899))119879

(7)

where119882 is a nonfuzzy numberIn this present case Changrsquos method [12] is applied to

solve a vendor selection and evaluation problem We adopt aldquoLikert scalerdquo of fuzzy numbers starting from 1 to 9 to trans-form the linguistic values into TFNs as shown in Table 2

4 The Empirical Case Analysis

To awireless networking technology-driven firm the intrare-lationship management with its vendors is conducted

4 Mathematical Problems in Engineering

Table 2 Triangular fuzzy conversation scale [11]

Linguistic values Triangular fuzzynumbers

Reciprocal triangularfuzzy scale

(1) Unimportant (U) (1 1 1) (1 1 1)(2) Between U and SL (1 2 3) (13 12 1)(3) Slightly important (SL) (2 3 4) (14 13 12)(4) Between SL and MI (3 4 5) (15 14 13)(5) Moderately important (MI) (4 5 6) (16 15 14)(6) Between MI and SI (5 6 7) (17 16 15)(7) Seriously important (SI) (6 7 8) (18 17 16)(8) Between SI and VSI (7 8 9) (19 18 17)(9) Very seriously important (VSI) (8 9 9) (19 19 18)

Table 3 Fuzzy AHP analysis of key Wi-Fi component IC vendorsrsquo evaluation and selection

Criteria Definition Subcriteria Definition

Capability (1198621)

Expertise andexperiences related tocompetitiveness

Market sensitivitylowast (MS-11986211) To meet market trends and customer

requirements

Technology availability (TA-11986212) To achieve up-to-date technological

specification designFinancial stability (FS-119862

13) To manage financial operation

Productivity (1198622) Flexibilities and

arrangement

Price policy (PP-11986221) To adjust costpricing offerings

Production capacity (PC-11986222) To fulfill just-in-time demand

Inventory strategylowastlowast (IS-11986223) To control materials and allocation of

finished goods

Reliability (1198623)

Accuracy andcommitments onmanagement

Product quality (PQ-11986231) To ensure product performance

On-time delivery (TD-11986232) To arrange delivery schedules

Risk management (RM-11986233) To manage risk factors

Note lowastkey subcriteria for Wi-Fi IC supplier selection lowastlowastmust subcriteria to judge Wi-Fi IC suppliersrsquo performance and management

through global business development so as to overcomethe limitations of technological knowledge To become aqualified key component vendor to fulfill system designersrsquorequirements alternative candidates should be fully and sys-tematically evaluated This research presents a measurementanalysis on a fifty-employee Taiwanese RampD design firmwitha very good track record for five consecutive years in wirelessnetworking solution design The critical decision for thisfirm is to select an appropriate value-added Wi-Fi IC vendorfrom two choices (a) Vendor A is a well-known world-classfirm that specializes in networking computing and mobilesolutions design for home and enterprise users includingapplications utilized on digital homes notebooks tabletsmobile phones mobile routers and so forth (b) Vendor B is apublicly traded IC design company in Taiwan with a broaderrange of high-tech product applications including solutionsfor implementation on computer peripherals communica-tion networks and multimedia Based on a questionnairesurvey feedback from 5 managers (2 electronic engineers 2project managers and one account manager) of each vendorand 7 managers (2 project managers 2 procurement man-agers 1 engineer for firmware 1 electronic engineer and onesales account) of the case studyrsquos design firm received inOcto-ber 2013 we apply a methodology to measure the weights ofthree criteria and nine subcriteria respectively and examinethe weights of the nine subcriteria versus alternatives fromthe final score of fuzzy AHP analysis Table 3 and Figure 2

define the criteria and subcriteria used to evaluate and selectWi-Fi IC vendors

Based on criteria and subcriteria defined in Table 3 and(1)ndash(7) we are able to calculate the importance weights of thecriteria and subcriteria as well as the weights of alternativesversus the subcriteria in Tables 4ndash6

We are now able to obtain the final score of each alterna-tive as Table 7

The data indicates that the vendorrsquos productivity(1198622 055) is a relatively greater concern versus the other

two criteria (see Table 4) On the weights of the subcriteriafinancial stability (119862

13 10) is the most important factor

under the decision choice on the capability term andinventory stability (119862

23 054) and production capability

(11986222 046) impact the greatest upon the productivity issue

while risk management (11986233 052) and on-time delivery

(11986232 048) hold critical weights under the reliability criterion

(see Table 5) For the weights of the two alternatives versusthe nine subcriteria respectively the Fuzzy AHP approachanalysis chooses Vendor B (119860

2 0724 versus119860

1 0276) as the

top priority for alternatives selection (see Tables 6 and 7)

5 Conclusions and Discussions

The selection of key component vendor alternatives involvesmultiple issues that can be systematically examined through

Mathematical Problems in Engineering 5

Table 4 The importance weights of the criteria

Criteria 1198621

1198622

1198623

119882119888

1198621

100 100 100 030 038 048 054 072 087 01198622

208 262 332 100 100 100 055 076 100 0551198623

115 139 184 100 132 180 100 100 100 045

Vendor A Vendor B

MS TA FS PP PC IS PQ TD RM

Selection of the best Wi-Fi IC vendor

Capability Productivity Reliability

Figure 2 Hierarchy of Wi-Fi component IC vendorsrsquo evaluation and selection problem

Table 5 The importance weights of the subcriteria

Subcriteria 11986211

11986212

11986213

119882119888

11986211

100 100 100 096 119 138 033 045 057 011986212

072 084 104 100 100 100 024 031 040 011986213

176 224 300 247 324 424 100 100 100 1Subcriteria 119862

2111986222

11986223

119882119888

11986221

100 100 100 030 040 051 022 028 037 011986222

195 249 331 100 100 100 029 039 047 04611986223

273 356 447 212 259 347 100 100 100 054Subcriteria 119862

3111986232

11986233

119882119888

11986231

100 100 100 020 025 031 025 032 040 011986232

318 400 500 100 100 100 044 057 074 04811986233

247 312 400 135 176 229 100 100 100 052

teamsrsquo analysis under a multicriteria decision process Tar-geting profit maximization a Wi-Fi IC component supplieris driven by a productrsquos bill-of-material (BOM) cost thatresults from the technological specificationsfeatures that arephased in during a new product design stage The insightsfrom this empirical case study identify some important issuesfor the evaluation measurement and analysis actions duringthe decision process for key component vendor selectionin technology-driven industries Through the perspectivesof synergistic effects and business ecosystems we offerthe following key results of our study for industries andacademia (i) The added value of the decision process onWi-Fi IC component vendorsrsquo selection encompasses technologyknow-how the main IC that makes up the main cost ofthe solution main board and the BOM cost performance(ii) The blueprint of the examination factors focuses on

Table 6 The weights of alternatives versus the subcriteria

11988211986211

1198601

1198602

119882119888

1198601

100 100 100 047 059 071 01198602

141 171 212 100 100 100 111988211986212

1198601

1198602

119882119888

1198601

100 100 100 036 049 067 01198602

149 203 276 100 100 100 111988211986213

1198601

1198602

119882119888

1198601

100 100 100 069 087 094 031198602

106 115 144 100 100 100 0711988211986221

1198601

1198602

119882119888

1198601

100 100 100 059 088 117 0441198602

085 113 170 100 100 100 05611988211986222

1198601

1198602

119882119888

1198601

100 100 100 057 076 104 0361198602

096 132 176 100 100 100 06411988211986223

1198601

1198602

119882119888

1198601

100 100 100 053 067 080 01198602

125 150 188 100 100 100 111988211986231

1198601

1198602

119882119888

1198601

100 100 100 043 058 077 0091198602

129 174 235 100 100 100 09111988211986232

1198601

1198602

119882119888

1198601

100 100 100 081 104 119 0521198602

084 096 124 100 100 100 04811988211986233

1198601

1198602

119882119888

1198601

100 100 100 059 079 096 0311198602

104 126 169 100 100 100 069

the evaluation issues of (a) competitiveness capability (b)productivity performance and (c) management reliability(iii) This study bridges gaps in previous research concerning

6 Mathematical Problems in Engineering

Table 7 Final score of each alternative

Alternative Score1198601

02761198602

0724

market sensitivity on market trends and customer require-ments (iv) The key characteristics to look at during the ven-dor selection process come from vendorsrsquo viewpoints and thesolution design firmrsquos examination of the impacts from threecriteria and nine subcriteria (v) The results herein indicatethat the strategic vendor evaluation analysis and report can beused as a reference by a firmrsquos operation management whenplanning a strategy for resource allocation

In an ICT technology-driven and customer-centric busi-ness ecosystem firms need to structure a value chain mech-anism through knowledge sharing network collaborationwith key suppliers and customers The scope and scale offuture research should integrate cross-functional cooperationamong teams to widely investigate the supply chain value ina global and dynamic context Given these issues we notethe following (1) Open innovation (OI) which involves agreater number of ideas knowledge areas and experiencescontributed by external partners is the key antecedent ofstrategic decisions made by firms (2) Knowledge manage-ment (KM) which drives firms by sharing and deployingknowledge to organizations for objective achievement is amultidisciplined theoretical approach suitable for industrialpractitioners in research and analysis Therefore in order tobuild up different research criteria that can be integrated withquantitativemeasurement analysis theories for future studieswe propose research objectives on customer value creationand supply chain value through the use of multipurposemodels

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] AH I Lee ldquoA fuzzy supplier selectionmodelwith the consider-ation of benefits opportunities costs and risksrdquo Expert Systemswith Applications vol 36 no 2 pp 2879ndash2893 2009

[2] B Nepal L Monplaisir and O Famuyiwa ldquoMatching productarchitecture with supply chain designrdquo European Journal ofOperational Research vol 216 no 2 pp 312ndash325 2012

[3] M Pero N Abdelkafi A Sianesi and T Blecker ldquoA frameworkfor the alignment of new product development and supplychainsrdquo Supply Chain Management vol 15 no 2 pp 115ndash1282010

[4] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[5] G Bruno E Esposito A Genovese andR Passaro ldquoAHP-basedapproaches for supplier evaluation problems and perspectivesrdquoJournal of Purchasing and Supply Management vol 18 no 3 pp159ndash172 2012

[6] E Elahi ldquoOutsourcing through competition what is the bestcompetition parameterrdquo International Journal of ProductionEconomics vol 144 no 1 pp 370ndash382 2013

[7] M Punniyamoorthy PMathiyalagan and P Parthiban ldquoA stra-tegic model using structural equation modeling and fuzzy logicin supplier selectionrdquo Expert Systems with Applications vol 38no 1 pp 458ndash474 2011

[8] A H I Lee H Kang and C Chang ldquoFuzzy multiple goal pro-gramming applied to TFT-LCD supplier selection by down-stream manufacturersrdquo Expert Systems with Applications vol36 no 3 pp 6318ndash6325 2009

[9] K Shaw R Shankar S S Yadav and L S Thakur ldquoSupplierselection using fuzzy AHP and fuzzy multi-objective linearprogramming for developing low carbon supply chainrdquo ExpertSystems with Applications vol 39 no 9 pp 8182ndash8192 2012

[10] P J M van Laarhoven and W Pedrycz ldquoA fuzzy extension ofSaatyrsquos priority theoryrdquo Fuzzy Sets and Systems vol 11 no 3 pp229ndash241 1983

[11] K P Anagnostopoulos M Gratziou and A P VavatsikosldquoUsing the fuzzy analytic hierarchy process for selecting waste-water facilities at prefectrure levelrdquo European Water pp 15ndash242007

[12] D Chang ldquoApplications of the extent analysis method on fuzzyAHPrdquo European Journal of Operational Research vol 95 no 3pp 649ndash655 1996

[13] I Chamodrakas D Batis and D Martakos ldquoSupplier selectionin electronic marketplaces using satisficing and fuzzy AHPrdquoExpert Systems with Applications vol 37 no 1 pp 490ndash4982010

[14] C A Bana e Costa and J-C Vansnick ldquoA critical analysis of theeigenvalue method used to derive priorities in AHPrdquo EuropeanJournal of Operational Research vol 187 no 3 pp 1422ndash14282008

[15] O Cakir ldquoOn the order of the preference intensities in fuzzyAHPrdquo Computers and Industrial Engineering vol 54 no 4 pp993ndash1005 2008

[16] LMikhailov ldquoDeriving priorities from fuzzy pairwise compari-son judgementsrdquo Fuzzy Sets and Systems vol 134 no 3 pp 365ndash385 2003

[17] O Kilincci and S A Onal ldquoFuzzy AHP approach for supplierselection in a washing machine companyrdquo Expert Systems withApplications vol 38 no 8 pp 9656ndash9664 2011

[18] C Ku C Chang and H Ho ldquoGlobal supplier selection usingfuzzy analytic hierarchy process and fuzzy goal programmingrdquoQuality and Quantity vol 44 no 4 pp 623ndash640 2010

[19] J Rezaei and R Ortt ldquoMulti-criteria supplier segmentationusing a fuzzy preference relations basedAHPrdquoEuropean Journalof Operational Research vol 225 no 1 pp 75ndash84 2013

[20] S Shim and B Lee ldquoSustainable competitive advantage of asystem goods innovator in a market with network effects andentry threatsrdquo Decision Support Systems vol 52 no 2 pp 308ndash317 2012

[21] J-L Chen ldquoThe synergistic effects of IT-enabled resources onorganizational capabilities and firm performancerdquo Informationand Management vol 49 no 3-4 pp 142ndash150 2012

[22] N Harmancioglu ldquoPortfolio of controls in outsourcing rela-tionships for global new product developmentrdquo IndustrialMarketing Management vol 38 no 4 pp 394ndash403 2009

[23] J Zhang and X Liang ldquoBusiness ecosystem strategies of mobilenetwork operators in the 3G era the case of China MobilerdquoTelecommunications Policy vol 35 no 2 pp 156ndash171 2011

Mathematical Problems in Engineering 7

[24] S J Wu and G L Ragatz ldquoEvaluating the total effect of earlysupplier involvement on project team effectiveness collabora-tion and interactionrdquo International Journal of Integrated SupplyManagement vol 5 no 3 pp 239ndash259 2010

[25] T L Esper A E Ellinger T P Stank D J Flint and M MoonldquoDemand and supply integration a conceptual framework ofvalue creation through knowledge managementrdquo Journal of theAcademy of Marketing Science vol 38 no 1 pp 5ndash18 2010

[26] P Hilletofth and D Eriksson ldquoCoordinating new productdevelopment with supply chain managementrdquo Industrial Man-agement and Data Systems vol 111 no 2 pp 264ndash281 2011

[27] J Roshandel S S Miri-Nargesi and L Hatami-ShirkouhildquoEvaluating and selecting the supplier in detergent productionindustry using hierarchical fuzzy TOPSISrdquo Applied Mathemat-ical Modelling vol 37 no 24 pp 10170ndash10181 2013

[28] A Zouggari and L Benyoucef ldquoSimulation based fuzzy TOPSISapproach for group multi-criteria supplier selection problemrdquoEngineering Applications of Artificial Intelligence vol 25 no 3pp 507ndash519 2012

[29] DWu D DWu Y Zhang and D L Olson ldquoSupply chain out-sourcing risk using an integrated stochastic-fuzzy optimizationapproachrdquo Information Sciences vol 235 pp 242ndash258 2013

[30] Y Kristianto P Helo J R Jiao and M Sandhu ldquoAdaptive fuzzyvendor managed inventory control for mitigating the Bull-whip effect in supply chainsrdquo European Journal of OperationalResearch vol 216 no 2 pp 346ndash355 2012

[31] LOsiro F R Lima-Junior andLC RCarpinetti ldquoA fuzzy logicapproach to supplier evaluation for developmentrdquo InternationalJournal of Production Economics vol 153 pp 95ndash112 2014

[32] Y Chen and R Chao ldquoSupplier selection using consistent fuzzypreference relationsrdquo Expert Systems with Applications vol 39no 3 pp 3233ndash3240 2012

[33] C-Y Shen and K-T Yu ldquoEnhancing the efficacy of supplierselection decision-making on the initial stage of new productdevelopment a hybrid fuzzy approach considering the strategicand operational factors simultaneouslyrdquo Expert Systems withApplications vol 36 no 8 pp 11271ndash11281 2009

[34] I Ruuska T Ahola M Martinsuo and T Westerholm ldquoSup-plier capabilities in large shipbuilding projectsrdquo InternationalJournal of Project Management vol 31 no 4 pp 542ndash553 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal of

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Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

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Discrete Dynamics in Nature and Society

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Decision SciencesAdvances in

Discrete MathematicsJournal of

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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 3

Table 1 Characteristics released on the vendorsupplier selectionreferencesCharacteristics ReferencesDelivery [1 4 6ndash9 13 17 19 27 28]Costprice [1 4 7ndash9 13 17ndash19 27ndash29 32]Quality [1 4 5 7 9 13 17ndash19 27ndash29 32 33]Technology [1 4 7 17 27 33]Risk [1 18 28]Production [4 7 17 27]Finance [4 5 7 17 19 32]Inventory [6 30]

cost criterion is the first priority of concern followed byquality service and risk for a Taiwanese digital consumermanufacturer to select its global suppliers Reference [32]addresses an evaluation process of supplier selection andfirmly identifies technique capability as well as design anddevelopment ability as the two major influential elements inprofessional technology for one electronic manufacturer Inthe initial stage of new product development [33] indicatesthat quality reliability and technological capability are impor-tant subcriteria factors adopted for plastic injection vendorselection by a personal digital assistant (PDA) developerTable 1 reviews the characteristics in the vendorsupplierselection Reference [34] uses a qualitative embedded single-case strategy in shipbuilding industry to explore the impor-tance of supplier capabilities in one shipyard and examineshow consistently the shipyard and its 20 suppliers assess thecapabilities of the suppliers

3 Fuzzy Analytic HierarchyProcess Methodology

This study adopts the extent analysis method proposed by[12] due to its computational simplicity The extent analysismethod is briefly discussed as follows

Let 119883 = 1199091 1199092 119909

119899 be an object set and let 119880 =

1199061 1199062 119906

119898 be a goal set According to [12] each object is

taken and an extent analysis for each goal (119892119894) is performed

respectively Therefore the 119898 extent analysis values for eachobject are obtained as 1198721

1198921198941198722

119892119894 119872

119899

119892119894 119894 = 1 2 119899

where 119872119895119892119894(119895 = 1 2 119898) are triangular fuzzy numbers

(TFNs)Assume that 119872119895

119892119894are the values of extent analysis of the

119894th object for119898 goalsThe value of fuzzy synthetic extent 119878119894is

defined as

119878119894=

119898

sum

119895=1

119872119895

119892119894otimes [

[

119899

sum

119894=1

119898

sum

119895=1

119872119895

119892119894

]

]

minus1

(1)

where sum119898119895=1

119872119895

119892119894= (sum119898

119895=1119897119895 sum119898

119895=1119898119895 sum119898

119895=1119906119895 ) 119895 = 1 2

119898 119894 = 1 2 119899Let119872

1= (1198971 1198981 1199061) and119872

2= (1198972 1198982 1199062) be two TFNs

whereby the degree of possibility of 1198721ge 1198722is defined as

follows

119881 (1198721ge 1198722) = sup119909ge119910

[min (1205831198721

(119909) 1205831198722

(119909))] (2)

y

x0

M1M2

m1m2

D

l1l2 u1u2d

V(M2 ge M1)

Figure 1 The comparison of two fuzzy numbers

The membership degree of possibility is expressed as

119881 (1198721ge 1198722) = ℎ119892119905 (119872

1cap1198722) = 1205831198722

(119889)

=

1 if 1198981ge 1198982

0 if 1198971ge 1199062

1198971minus 1199062

(1198982minus 1199062) minus (119898

1minus 1198971)

otherwise

(3)

where 119889 is the ordinate of the highest intersection point oftwo membership functions 120583

1198721(119909) and 120583

1198722(119909) as shown in

Figure 1The degree of possibility for a convex fuzzy number to be

greater than 119896 convex fuzzy numbers is defined as

119881 (119872 ge 11987211198722 119872

119896) = min119881 (119872 ge 119872

119894)

119894 = 1 2 119896

(4)

The weight vector is given by

1198821015840= (1198891015840(1198601) 1198891015840(1198602) 119889

1015840(119860119899))119879

(5)

where

119860119894(119894 = 1 2 119899) 119889

1015840(119860119894) = min119881 (119878

119894ge 119878119896)

119896 = 1 2 119899 119896 = 119894

(6)

Via normalization we obtain the weight vectors as

119882 = (119889(1198601) 119889(119860

2) 119889(119860

119899))119879

(7)

where119882 is a nonfuzzy numberIn this present case Changrsquos method [12] is applied to

solve a vendor selection and evaluation problem We adopt aldquoLikert scalerdquo of fuzzy numbers starting from 1 to 9 to trans-form the linguistic values into TFNs as shown in Table 2

4 The Empirical Case Analysis

To awireless networking technology-driven firm the intrare-lationship management with its vendors is conducted

4 Mathematical Problems in Engineering

Table 2 Triangular fuzzy conversation scale [11]

Linguistic values Triangular fuzzynumbers

Reciprocal triangularfuzzy scale

(1) Unimportant (U) (1 1 1) (1 1 1)(2) Between U and SL (1 2 3) (13 12 1)(3) Slightly important (SL) (2 3 4) (14 13 12)(4) Between SL and MI (3 4 5) (15 14 13)(5) Moderately important (MI) (4 5 6) (16 15 14)(6) Between MI and SI (5 6 7) (17 16 15)(7) Seriously important (SI) (6 7 8) (18 17 16)(8) Between SI and VSI (7 8 9) (19 18 17)(9) Very seriously important (VSI) (8 9 9) (19 19 18)

Table 3 Fuzzy AHP analysis of key Wi-Fi component IC vendorsrsquo evaluation and selection

Criteria Definition Subcriteria Definition

Capability (1198621)

Expertise andexperiences related tocompetitiveness

Market sensitivitylowast (MS-11986211) To meet market trends and customer

requirements

Technology availability (TA-11986212) To achieve up-to-date technological

specification designFinancial stability (FS-119862

13) To manage financial operation

Productivity (1198622) Flexibilities and

arrangement

Price policy (PP-11986221) To adjust costpricing offerings

Production capacity (PC-11986222) To fulfill just-in-time demand

Inventory strategylowastlowast (IS-11986223) To control materials and allocation of

finished goods

Reliability (1198623)

Accuracy andcommitments onmanagement

Product quality (PQ-11986231) To ensure product performance

On-time delivery (TD-11986232) To arrange delivery schedules

Risk management (RM-11986233) To manage risk factors

Note lowastkey subcriteria for Wi-Fi IC supplier selection lowastlowastmust subcriteria to judge Wi-Fi IC suppliersrsquo performance and management

through global business development so as to overcomethe limitations of technological knowledge To become aqualified key component vendor to fulfill system designersrsquorequirements alternative candidates should be fully and sys-tematically evaluated This research presents a measurementanalysis on a fifty-employee Taiwanese RampD design firmwitha very good track record for five consecutive years in wirelessnetworking solution design The critical decision for thisfirm is to select an appropriate value-added Wi-Fi IC vendorfrom two choices (a) Vendor A is a well-known world-classfirm that specializes in networking computing and mobilesolutions design for home and enterprise users includingapplications utilized on digital homes notebooks tabletsmobile phones mobile routers and so forth (b) Vendor B is apublicly traded IC design company in Taiwan with a broaderrange of high-tech product applications including solutionsfor implementation on computer peripherals communica-tion networks and multimedia Based on a questionnairesurvey feedback from 5 managers (2 electronic engineers 2project managers and one account manager) of each vendorand 7 managers (2 project managers 2 procurement man-agers 1 engineer for firmware 1 electronic engineer and onesales account) of the case studyrsquos design firm received inOcto-ber 2013 we apply a methodology to measure the weights ofthree criteria and nine subcriteria respectively and examinethe weights of the nine subcriteria versus alternatives fromthe final score of fuzzy AHP analysis Table 3 and Figure 2

define the criteria and subcriteria used to evaluate and selectWi-Fi IC vendors

Based on criteria and subcriteria defined in Table 3 and(1)ndash(7) we are able to calculate the importance weights of thecriteria and subcriteria as well as the weights of alternativesversus the subcriteria in Tables 4ndash6

We are now able to obtain the final score of each alterna-tive as Table 7

The data indicates that the vendorrsquos productivity(1198622 055) is a relatively greater concern versus the other

two criteria (see Table 4) On the weights of the subcriteriafinancial stability (119862

13 10) is the most important factor

under the decision choice on the capability term andinventory stability (119862

23 054) and production capability

(11986222 046) impact the greatest upon the productivity issue

while risk management (11986233 052) and on-time delivery

(11986232 048) hold critical weights under the reliability criterion

(see Table 5) For the weights of the two alternatives versusthe nine subcriteria respectively the Fuzzy AHP approachanalysis chooses Vendor B (119860

2 0724 versus119860

1 0276) as the

top priority for alternatives selection (see Tables 6 and 7)

5 Conclusions and Discussions

The selection of key component vendor alternatives involvesmultiple issues that can be systematically examined through

Mathematical Problems in Engineering 5

Table 4 The importance weights of the criteria

Criteria 1198621

1198622

1198623

119882119888

1198621

100 100 100 030 038 048 054 072 087 01198622

208 262 332 100 100 100 055 076 100 0551198623

115 139 184 100 132 180 100 100 100 045

Vendor A Vendor B

MS TA FS PP PC IS PQ TD RM

Selection of the best Wi-Fi IC vendor

Capability Productivity Reliability

Figure 2 Hierarchy of Wi-Fi component IC vendorsrsquo evaluation and selection problem

Table 5 The importance weights of the subcriteria

Subcriteria 11986211

11986212

11986213

119882119888

11986211

100 100 100 096 119 138 033 045 057 011986212

072 084 104 100 100 100 024 031 040 011986213

176 224 300 247 324 424 100 100 100 1Subcriteria 119862

2111986222

11986223

119882119888

11986221

100 100 100 030 040 051 022 028 037 011986222

195 249 331 100 100 100 029 039 047 04611986223

273 356 447 212 259 347 100 100 100 054Subcriteria 119862

3111986232

11986233

119882119888

11986231

100 100 100 020 025 031 025 032 040 011986232

318 400 500 100 100 100 044 057 074 04811986233

247 312 400 135 176 229 100 100 100 052

teamsrsquo analysis under a multicriteria decision process Tar-geting profit maximization a Wi-Fi IC component supplieris driven by a productrsquos bill-of-material (BOM) cost thatresults from the technological specificationsfeatures that arephased in during a new product design stage The insightsfrom this empirical case study identify some important issuesfor the evaluation measurement and analysis actions duringthe decision process for key component vendor selectionin technology-driven industries Through the perspectivesof synergistic effects and business ecosystems we offerthe following key results of our study for industries andacademia (i) The added value of the decision process onWi-Fi IC component vendorsrsquo selection encompasses technologyknow-how the main IC that makes up the main cost ofthe solution main board and the BOM cost performance(ii) The blueprint of the examination factors focuses on

Table 6 The weights of alternatives versus the subcriteria

11988211986211

1198601

1198602

119882119888

1198601

100 100 100 047 059 071 01198602

141 171 212 100 100 100 111988211986212

1198601

1198602

119882119888

1198601

100 100 100 036 049 067 01198602

149 203 276 100 100 100 111988211986213

1198601

1198602

119882119888

1198601

100 100 100 069 087 094 031198602

106 115 144 100 100 100 0711988211986221

1198601

1198602

119882119888

1198601

100 100 100 059 088 117 0441198602

085 113 170 100 100 100 05611988211986222

1198601

1198602

119882119888

1198601

100 100 100 057 076 104 0361198602

096 132 176 100 100 100 06411988211986223

1198601

1198602

119882119888

1198601

100 100 100 053 067 080 01198602

125 150 188 100 100 100 111988211986231

1198601

1198602

119882119888

1198601

100 100 100 043 058 077 0091198602

129 174 235 100 100 100 09111988211986232

1198601

1198602

119882119888

1198601

100 100 100 081 104 119 0521198602

084 096 124 100 100 100 04811988211986233

1198601

1198602

119882119888

1198601

100 100 100 059 079 096 0311198602

104 126 169 100 100 100 069

the evaluation issues of (a) competitiveness capability (b)productivity performance and (c) management reliability(iii) This study bridges gaps in previous research concerning

6 Mathematical Problems in Engineering

Table 7 Final score of each alternative

Alternative Score1198601

02761198602

0724

market sensitivity on market trends and customer require-ments (iv) The key characteristics to look at during the ven-dor selection process come from vendorsrsquo viewpoints and thesolution design firmrsquos examination of the impacts from threecriteria and nine subcriteria (v) The results herein indicatethat the strategic vendor evaluation analysis and report can beused as a reference by a firmrsquos operation management whenplanning a strategy for resource allocation

In an ICT technology-driven and customer-centric busi-ness ecosystem firms need to structure a value chain mech-anism through knowledge sharing network collaborationwith key suppliers and customers The scope and scale offuture research should integrate cross-functional cooperationamong teams to widely investigate the supply chain value ina global and dynamic context Given these issues we notethe following (1) Open innovation (OI) which involves agreater number of ideas knowledge areas and experiencescontributed by external partners is the key antecedent ofstrategic decisions made by firms (2) Knowledge manage-ment (KM) which drives firms by sharing and deployingknowledge to organizations for objective achievement is amultidisciplined theoretical approach suitable for industrialpractitioners in research and analysis Therefore in order tobuild up different research criteria that can be integrated withquantitativemeasurement analysis theories for future studieswe propose research objectives on customer value creationand supply chain value through the use of multipurposemodels

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] AH I Lee ldquoA fuzzy supplier selectionmodelwith the consider-ation of benefits opportunities costs and risksrdquo Expert Systemswith Applications vol 36 no 2 pp 2879ndash2893 2009

[2] B Nepal L Monplaisir and O Famuyiwa ldquoMatching productarchitecture with supply chain designrdquo European Journal ofOperational Research vol 216 no 2 pp 312ndash325 2012

[3] M Pero N Abdelkafi A Sianesi and T Blecker ldquoA frameworkfor the alignment of new product development and supplychainsrdquo Supply Chain Management vol 15 no 2 pp 115ndash1282010

[4] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[5] G Bruno E Esposito A Genovese andR Passaro ldquoAHP-basedapproaches for supplier evaluation problems and perspectivesrdquoJournal of Purchasing and Supply Management vol 18 no 3 pp159ndash172 2012

[6] E Elahi ldquoOutsourcing through competition what is the bestcompetition parameterrdquo International Journal of ProductionEconomics vol 144 no 1 pp 370ndash382 2013

[7] M Punniyamoorthy PMathiyalagan and P Parthiban ldquoA stra-tegic model using structural equation modeling and fuzzy logicin supplier selectionrdquo Expert Systems with Applications vol 38no 1 pp 458ndash474 2011

[8] A H I Lee H Kang and C Chang ldquoFuzzy multiple goal pro-gramming applied to TFT-LCD supplier selection by down-stream manufacturersrdquo Expert Systems with Applications vol36 no 3 pp 6318ndash6325 2009

[9] K Shaw R Shankar S S Yadav and L S Thakur ldquoSupplierselection using fuzzy AHP and fuzzy multi-objective linearprogramming for developing low carbon supply chainrdquo ExpertSystems with Applications vol 39 no 9 pp 8182ndash8192 2012

[10] P J M van Laarhoven and W Pedrycz ldquoA fuzzy extension ofSaatyrsquos priority theoryrdquo Fuzzy Sets and Systems vol 11 no 3 pp229ndash241 1983

[11] K P Anagnostopoulos M Gratziou and A P VavatsikosldquoUsing the fuzzy analytic hierarchy process for selecting waste-water facilities at prefectrure levelrdquo European Water pp 15ndash242007

[12] D Chang ldquoApplications of the extent analysis method on fuzzyAHPrdquo European Journal of Operational Research vol 95 no 3pp 649ndash655 1996

[13] I Chamodrakas D Batis and D Martakos ldquoSupplier selectionin electronic marketplaces using satisficing and fuzzy AHPrdquoExpert Systems with Applications vol 37 no 1 pp 490ndash4982010

[14] C A Bana e Costa and J-C Vansnick ldquoA critical analysis of theeigenvalue method used to derive priorities in AHPrdquo EuropeanJournal of Operational Research vol 187 no 3 pp 1422ndash14282008

[15] O Cakir ldquoOn the order of the preference intensities in fuzzyAHPrdquo Computers and Industrial Engineering vol 54 no 4 pp993ndash1005 2008

[16] LMikhailov ldquoDeriving priorities from fuzzy pairwise compari-son judgementsrdquo Fuzzy Sets and Systems vol 134 no 3 pp 365ndash385 2003

[17] O Kilincci and S A Onal ldquoFuzzy AHP approach for supplierselection in a washing machine companyrdquo Expert Systems withApplications vol 38 no 8 pp 9656ndash9664 2011

[18] C Ku C Chang and H Ho ldquoGlobal supplier selection usingfuzzy analytic hierarchy process and fuzzy goal programmingrdquoQuality and Quantity vol 44 no 4 pp 623ndash640 2010

[19] J Rezaei and R Ortt ldquoMulti-criteria supplier segmentationusing a fuzzy preference relations basedAHPrdquoEuropean Journalof Operational Research vol 225 no 1 pp 75ndash84 2013

[20] S Shim and B Lee ldquoSustainable competitive advantage of asystem goods innovator in a market with network effects andentry threatsrdquo Decision Support Systems vol 52 no 2 pp 308ndash317 2012

[21] J-L Chen ldquoThe synergistic effects of IT-enabled resources onorganizational capabilities and firm performancerdquo Informationand Management vol 49 no 3-4 pp 142ndash150 2012

[22] N Harmancioglu ldquoPortfolio of controls in outsourcing rela-tionships for global new product developmentrdquo IndustrialMarketing Management vol 38 no 4 pp 394ndash403 2009

[23] J Zhang and X Liang ldquoBusiness ecosystem strategies of mobilenetwork operators in the 3G era the case of China MobilerdquoTelecommunications Policy vol 35 no 2 pp 156ndash171 2011

Mathematical Problems in Engineering 7

[24] S J Wu and G L Ragatz ldquoEvaluating the total effect of earlysupplier involvement on project team effectiveness collabora-tion and interactionrdquo International Journal of Integrated SupplyManagement vol 5 no 3 pp 239ndash259 2010

[25] T L Esper A E Ellinger T P Stank D J Flint and M MoonldquoDemand and supply integration a conceptual framework ofvalue creation through knowledge managementrdquo Journal of theAcademy of Marketing Science vol 38 no 1 pp 5ndash18 2010

[26] P Hilletofth and D Eriksson ldquoCoordinating new productdevelopment with supply chain managementrdquo Industrial Man-agement and Data Systems vol 111 no 2 pp 264ndash281 2011

[27] J Roshandel S S Miri-Nargesi and L Hatami-ShirkouhildquoEvaluating and selecting the supplier in detergent productionindustry using hierarchical fuzzy TOPSISrdquo Applied Mathemat-ical Modelling vol 37 no 24 pp 10170ndash10181 2013

[28] A Zouggari and L Benyoucef ldquoSimulation based fuzzy TOPSISapproach for group multi-criteria supplier selection problemrdquoEngineering Applications of Artificial Intelligence vol 25 no 3pp 507ndash519 2012

[29] DWu D DWu Y Zhang and D L Olson ldquoSupply chain out-sourcing risk using an integrated stochastic-fuzzy optimizationapproachrdquo Information Sciences vol 235 pp 242ndash258 2013

[30] Y Kristianto P Helo J R Jiao and M Sandhu ldquoAdaptive fuzzyvendor managed inventory control for mitigating the Bull-whip effect in supply chainsrdquo European Journal of OperationalResearch vol 216 no 2 pp 346ndash355 2012

[31] LOsiro F R Lima-Junior andLC RCarpinetti ldquoA fuzzy logicapproach to supplier evaluation for developmentrdquo InternationalJournal of Production Economics vol 153 pp 95ndash112 2014

[32] Y Chen and R Chao ldquoSupplier selection using consistent fuzzypreference relationsrdquo Expert Systems with Applications vol 39no 3 pp 3233ndash3240 2012

[33] C-Y Shen and K-T Yu ldquoEnhancing the efficacy of supplierselection decision-making on the initial stage of new productdevelopment a hybrid fuzzy approach considering the strategicand operational factors simultaneouslyrdquo Expert Systems withApplications vol 36 no 8 pp 11271ndash11281 2009

[34] I Ruuska T Ahola M Martinsuo and T Westerholm ldquoSup-plier capabilities in large shipbuilding projectsrdquo InternationalJournal of Project Management vol 31 no 4 pp 542ndash553 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

4 Mathematical Problems in Engineering

Table 2 Triangular fuzzy conversation scale [11]

Linguistic values Triangular fuzzynumbers

Reciprocal triangularfuzzy scale

(1) Unimportant (U) (1 1 1) (1 1 1)(2) Between U and SL (1 2 3) (13 12 1)(3) Slightly important (SL) (2 3 4) (14 13 12)(4) Between SL and MI (3 4 5) (15 14 13)(5) Moderately important (MI) (4 5 6) (16 15 14)(6) Between MI and SI (5 6 7) (17 16 15)(7) Seriously important (SI) (6 7 8) (18 17 16)(8) Between SI and VSI (7 8 9) (19 18 17)(9) Very seriously important (VSI) (8 9 9) (19 19 18)

Table 3 Fuzzy AHP analysis of key Wi-Fi component IC vendorsrsquo evaluation and selection

Criteria Definition Subcriteria Definition

Capability (1198621)

Expertise andexperiences related tocompetitiveness

Market sensitivitylowast (MS-11986211) To meet market trends and customer

requirements

Technology availability (TA-11986212) To achieve up-to-date technological

specification designFinancial stability (FS-119862

13) To manage financial operation

Productivity (1198622) Flexibilities and

arrangement

Price policy (PP-11986221) To adjust costpricing offerings

Production capacity (PC-11986222) To fulfill just-in-time demand

Inventory strategylowastlowast (IS-11986223) To control materials and allocation of

finished goods

Reliability (1198623)

Accuracy andcommitments onmanagement

Product quality (PQ-11986231) To ensure product performance

On-time delivery (TD-11986232) To arrange delivery schedules

Risk management (RM-11986233) To manage risk factors

Note lowastkey subcriteria for Wi-Fi IC supplier selection lowastlowastmust subcriteria to judge Wi-Fi IC suppliersrsquo performance and management

through global business development so as to overcomethe limitations of technological knowledge To become aqualified key component vendor to fulfill system designersrsquorequirements alternative candidates should be fully and sys-tematically evaluated This research presents a measurementanalysis on a fifty-employee Taiwanese RampD design firmwitha very good track record for five consecutive years in wirelessnetworking solution design The critical decision for thisfirm is to select an appropriate value-added Wi-Fi IC vendorfrom two choices (a) Vendor A is a well-known world-classfirm that specializes in networking computing and mobilesolutions design for home and enterprise users includingapplications utilized on digital homes notebooks tabletsmobile phones mobile routers and so forth (b) Vendor B is apublicly traded IC design company in Taiwan with a broaderrange of high-tech product applications including solutionsfor implementation on computer peripherals communica-tion networks and multimedia Based on a questionnairesurvey feedback from 5 managers (2 electronic engineers 2project managers and one account manager) of each vendorand 7 managers (2 project managers 2 procurement man-agers 1 engineer for firmware 1 electronic engineer and onesales account) of the case studyrsquos design firm received inOcto-ber 2013 we apply a methodology to measure the weights ofthree criteria and nine subcriteria respectively and examinethe weights of the nine subcriteria versus alternatives fromthe final score of fuzzy AHP analysis Table 3 and Figure 2

define the criteria and subcriteria used to evaluate and selectWi-Fi IC vendors

Based on criteria and subcriteria defined in Table 3 and(1)ndash(7) we are able to calculate the importance weights of thecriteria and subcriteria as well as the weights of alternativesversus the subcriteria in Tables 4ndash6

We are now able to obtain the final score of each alterna-tive as Table 7

The data indicates that the vendorrsquos productivity(1198622 055) is a relatively greater concern versus the other

two criteria (see Table 4) On the weights of the subcriteriafinancial stability (119862

13 10) is the most important factor

under the decision choice on the capability term andinventory stability (119862

23 054) and production capability

(11986222 046) impact the greatest upon the productivity issue

while risk management (11986233 052) and on-time delivery

(11986232 048) hold critical weights under the reliability criterion

(see Table 5) For the weights of the two alternatives versusthe nine subcriteria respectively the Fuzzy AHP approachanalysis chooses Vendor B (119860

2 0724 versus119860

1 0276) as the

top priority for alternatives selection (see Tables 6 and 7)

5 Conclusions and Discussions

The selection of key component vendor alternatives involvesmultiple issues that can be systematically examined through

Mathematical Problems in Engineering 5

Table 4 The importance weights of the criteria

Criteria 1198621

1198622

1198623

119882119888

1198621

100 100 100 030 038 048 054 072 087 01198622

208 262 332 100 100 100 055 076 100 0551198623

115 139 184 100 132 180 100 100 100 045

Vendor A Vendor B

MS TA FS PP PC IS PQ TD RM

Selection of the best Wi-Fi IC vendor

Capability Productivity Reliability

Figure 2 Hierarchy of Wi-Fi component IC vendorsrsquo evaluation and selection problem

Table 5 The importance weights of the subcriteria

Subcriteria 11986211

11986212

11986213

119882119888

11986211

100 100 100 096 119 138 033 045 057 011986212

072 084 104 100 100 100 024 031 040 011986213

176 224 300 247 324 424 100 100 100 1Subcriteria 119862

2111986222

11986223

119882119888

11986221

100 100 100 030 040 051 022 028 037 011986222

195 249 331 100 100 100 029 039 047 04611986223

273 356 447 212 259 347 100 100 100 054Subcriteria 119862

3111986232

11986233

119882119888

11986231

100 100 100 020 025 031 025 032 040 011986232

318 400 500 100 100 100 044 057 074 04811986233

247 312 400 135 176 229 100 100 100 052

teamsrsquo analysis under a multicriteria decision process Tar-geting profit maximization a Wi-Fi IC component supplieris driven by a productrsquos bill-of-material (BOM) cost thatresults from the technological specificationsfeatures that arephased in during a new product design stage The insightsfrom this empirical case study identify some important issuesfor the evaluation measurement and analysis actions duringthe decision process for key component vendor selectionin technology-driven industries Through the perspectivesof synergistic effects and business ecosystems we offerthe following key results of our study for industries andacademia (i) The added value of the decision process onWi-Fi IC component vendorsrsquo selection encompasses technologyknow-how the main IC that makes up the main cost ofthe solution main board and the BOM cost performance(ii) The blueprint of the examination factors focuses on

Table 6 The weights of alternatives versus the subcriteria

11988211986211

1198601

1198602

119882119888

1198601

100 100 100 047 059 071 01198602

141 171 212 100 100 100 111988211986212

1198601

1198602

119882119888

1198601

100 100 100 036 049 067 01198602

149 203 276 100 100 100 111988211986213

1198601

1198602

119882119888

1198601

100 100 100 069 087 094 031198602

106 115 144 100 100 100 0711988211986221

1198601

1198602

119882119888

1198601

100 100 100 059 088 117 0441198602

085 113 170 100 100 100 05611988211986222

1198601

1198602

119882119888

1198601

100 100 100 057 076 104 0361198602

096 132 176 100 100 100 06411988211986223

1198601

1198602

119882119888

1198601

100 100 100 053 067 080 01198602

125 150 188 100 100 100 111988211986231

1198601

1198602

119882119888

1198601

100 100 100 043 058 077 0091198602

129 174 235 100 100 100 09111988211986232

1198601

1198602

119882119888

1198601

100 100 100 081 104 119 0521198602

084 096 124 100 100 100 04811988211986233

1198601

1198602

119882119888

1198601

100 100 100 059 079 096 0311198602

104 126 169 100 100 100 069

the evaluation issues of (a) competitiveness capability (b)productivity performance and (c) management reliability(iii) This study bridges gaps in previous research concerning

6 Mathematical Problems in Engineering

Table 7 Final score of each alternative

Alternative Score1198601

02761198602

0724

market sensitivity on market trends and customer require-ments (iv) The key characteristics to look at during the ven-dor selection process come from vendorsrsquo viewpoints and thesolution design firmrsquos examination of the impacts from threecriteria and nine subcriteria (v) The results herein indicatethat the strategic vendor evaluation analysis and report can beused as a reference by a firmrsquos operation management whenplanning a strategy for resource allocation

In an ICT technology-driven and customer-centric busi-ness ecosystem firms need to structure a value chain mech-anism through knowledge sharing network collaborationwith key suppliers and customers The scope and scale offuture research should integrate cross-functional cooperationamong teams to widely investigate the supply chain value ina global and dynamic context Given these issues we notethe following (1) Open innovation (OI) which involves agreater number of ideas knowledge areas and experiencescontributed by external partners is the key antecedent ofstrategic decisions made by firms (2) Knowledge manage-ment (KM) which drives firms by sharing and deployingknowledge to organizations for objective achievement is amultidisciplined theoretical approach suitable for industrialpractitioners in research and analysis Therefore in order tobuild up different research criteria that can be integrated withquantitativemeasurement analysis theories for future studieswe propose research objectives on customer value creationand supply chain value through the use of multipurposemodels

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] AH I Lee ldquoA fuzzy supplier selectionmodelwith the consider-ation of benefits opportunities costs and risksrdquo Expert Systemswith Applications vol 36 no 2 pp 2879ndash2893 2009

[2] B Nepal L Monplaisir and O Famuyiwa ldquoMatching productarchitecture with supply chain designrdquo European Journal ofOperational Research vol 216 no 2 pp 312ndash325 2012

[3] M Pero N Abdelkafi A Sianesi and T Blecker ldquoA frameworkfor the alignment of new product development and supplychainsrdquo Supply Chain Management vol 15 no 2 pp 115ndash1282010

[4] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[5] G Bruno E Esposito A Genovese andR Passaro ldquoAHP-basedapproaches for supplier evaluation problems and perspectivesrdquoJournal of Purchasing and Supply Management vol 18 no 3 pp159ndash172 2012

[6] E Elahi ldquoOutsourcing through competition what is the bestcompetition parameterrdquo International Journal of ProductionEconomics vol 144 no 1 pp 370ndash382 2013

[7] M Punniyamoorthy PMathiyalagan and P Parthiban ldquoA stra-tegic model using structural equation modeling and fuzzy logicin supplier selectionrdquo Expert Systems with Applications vol 38no 1 pp 458ndash474 2011

[8] A H I Lee H Kang and C Chang ldquoFuzzy multiple goal pro-gramming applied to TFT-LCD supplier selection by down-stream manufacturersrdquo Expert Systems with Applications vol36 no 3 pp 6318ndash6325 2009

[9] K Shaw R Shankar S S Yadav and L S Thakur ldquoSupplierselection using fuzzy AHP and fuzzy multi-objective linearprogramming for developing low carbon supply chainrdquo ExpertSystems with Applications vol 39 no 9 pp 8182ndash8192 2012

[10] P J M van Laarhoven and W Pedrycz ldquoA fuzzy extension ofSaatyrsquos priority theoryrdquo Fuzzy Sets and Systems vol 11 no 3 pp229ndash241 1983

[11] K P Anagnostopoulos M Gratziou and A P VavatsikosldquoUsing the fuzzy analytic hierarchy process for selecting waste-water facilities at prefectrure levelrdquo European Water pp 15ndash242007

[12] D Chang ldquoApplications of the extent analysis method on fuzzyAHPrdquo European Journal of Operational Research vol 95 no 3pp 649ndash655 1996

[13] I Chamodrakas D Batis and D Martakos ldquoSupplier selectionin electronic marketplaces using satisficing and fuzzy AHPrdquoExpert Systems with Applications vol 37 no 1 pp 490ndash4982010

[14] C A Bana e Costa and J-C Vansnick ldquoA critical analysis of theeigenvalue method used to derive priorities in AHPrdquo EuropeanJournal of Operational Research vol 187 no 3 pp 1422ndash14282008

[15] O Cakir ldquoOn the order of the preference intensities in fuzzyAHPrdquo Computers and Industrial Engineering vol 54 no 4 pp993ndash1005 2008

[16] LMikhailov ldquoDeriving priorities from fuzzy pairwise compari-son judgementsrdquo Fuzzy Sets and Systems vol 134 no 3 pp 365ndash385 2003

[17] O Kilincci and S A Onal ldquoFuzzy AHP approach for supplierselection in a washing machine companyrdquo Expert Systems withApplications vol 38 no 8 pp 9656ndash9664 2011

[18] C Ku C Chang and H Ho ldquoGlobal supplier selection usingfuzzy analytic hierarchy process and fuzzy goal programmingrdquoQuality and Quantity vol 44 no 4 pp 623ndash640 2010

[19] J Rezaei and R Ortt ldquoMulti-criteria supplier segmentationusing a fuzzy preference relations basedAHPrdquoEuropean Journalof Operational Research vol 225 no 1 pp 75ndash84 2013

[20] S Shim and B Lee ldquoSustainable competitive advantage of asystem goods innovator in a market with network effects andentry threatsrdquo Decision Support Systems vol 52 no 2 pp 308ndash317 2012

[21] J-L Chen ldquoThe synergistic effects of IT-enabled resources onorganizational capabilities and firm performancerdquo Informationand Management vol 49 no 3-4 pp 142ndash150 2012

[22] N Harmancioglu ldquoPortfolio of controls in outsourcing rela-tionships for global new product developmentrdquo IndustrialMarketing Management vol 38 no 4 pp 394ndash403 2009

[23] J Zhang and X Liang ldquoBusiness ecosystem strategies of mobilenetwork operators in the 3G era the case of China MobilerdquoTelecommunications Policy vol 35 no 2 pp 156ndash171 2011

Mathematical Problems in Engineering 7

[24] S J Wu and G L Ragatz ldquoEvaluating the total effect of earlysupplier involvement on project team effectiveness collabora-tion and interactionrdquo International Journal of Integrated SupplyManagement vol 5 no 3 pp 239ndash259 2010

[25] T L Esper A E Ellinger T P Stank D J Flint and M MoonldquoDemand and supply integration a conceptual framework ofvalue creation through knowledge managementrdquo Journal of theAcademy of Marketing Science vol 38 no 1 pp 5ndash18 2010

[26] P Hilletofth and D Eriksson ldquoCoordinating new productdevelopment with supply chain managementrdquo Industrial Man-agement and Data Systems vol 111 no 2 pp 264ndash281 2011

[27] J Roshandel S S Miri-Nargesi and L Hatami-ShirkouhildquoEvaluating and selecting the supplier in detergent productionindustry using hierarchical fuzzy TOPSISrdquo Applied Mathemat-ical Modelling vol 37 no 24 pp 10170ndash10181 2013

[28] A Zouggari and L Benyoucef ldquoSimulation based fuzzy TOPSISapproach for group multi-criteria supplier selection problemrdquoEngineering Applications of Artificial Intelligence vol 25 no 3pp 507ndash519 2012

[29] DWu D DWu Y Zhang and D L Olson ldquoSupply chain out-sourcing risk using an integrated stochastic-fuzzy optimizationapproachrdquo Information Sciences vol 235 pp 242ndash258 2013

[30] Y Kristianto P Helo J R Jiao and M Sandhu ldquoAdaptive fuzzyvendor managed inventory control for mitigating the Bull-whip effect in supply chainsrdquo European Journal of OperationalResearch vol 216 no 2 pp 346ndash355 2012

[31] LOsiro F R Lima-Junior andLC RCarpinetti ldquoA fuzzy logicapproach to supplier evaluation for developmentrdquo InternationalJournal of Production Economics vol 153 pp 95ndash112 2014

[32] Y Chen and R Chao ldquoSupplier selection using consistent fuzzypreference relationsrdquo Expert Systems with Applications vol 39no 3 pp 3233ndash3240 2012

[33] C-Y Shen and K-T Yu ldquoEnhancing the efficacy of supplierselection decision-making on the initial stage of new productdevelopment a hybrid fuzzy approach considering the strategicand operational factors simultaneouslyrdquo Expert Systems withApplications vol 36 no 8 pp 11271ndash11281 2009

[34] I Ruuska T Ahola M Martinsuo and T Westerholm ldquoSup-plier capabilities in large shipbuilding projectsrdquo InternationalJournal of Project Management vol 31 no 4 pp 542ndash553 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 5

Table 4 The importance weights of the criteria

Criteria 1198621

1198622

1198623

119882119888

1198621

100 100 100 030 038 048 054 072 087 01198622

208 262 332 100 100 100 055 076 100 0551198623

115 139 184 100 132 180 100 100 100 045

Vendor A Vendor B

MS TA FS PP PC IS PQ TD RM

Selection of the best Wi-Fi IC vendor

Capability Productivity Reliability

Figure 2 Hierarchy of Wi-Fi component IC vendorsrsquo evaluation and selection problem

Table 5 The importance weights of the subcriteria

Subcriteria 11986211

11986212

11986213

119882119888

11986211

100 100 100 096 119 138 033 045 057 011986212

072 084 104 100 100 100 024 031 040 011986213

176 224 300 247 324 424 100 100 100 1Subcriteria 119862

2111986222

11986223

119882119888

11986221

100 100 100 030 040 051 022 028 037 011986222

195 249 331 100 100 100 029 039 047 04611986223

273 356 447 212 259 347 100 100 100 054Subcriteria 119862

3111986232

11986233

119882119888

11986231

100 100 100 020 025 031 025 032 040 011986232

318 400 500 100 100 100 044 057 074 04811986233

247 312 400 135 176 229 100 100 100 052

teamsrsquo analysis under a multicriteria decision process Tar-geting profit maximization a Wi-Fi IC component supplieris driven by a productrsquos bill-of-material (BOM) cost thatresults from the technological specificationsfeatures that arephased in during a new product design stage The insightsfrom this empirical case study identify some important issuesfor the evaluation measurement and analysis actions duringthe decision process for key component vendor selectionin technology-driven industries Through the perspectivesof synergistic effects and business ecosystems we offerthe following key results of our study for industries andacademia (i) The added value of the decision process onWi-Fi IC component vendorsrsquo selection encompasses technologyknow-how the main IC that makes up the main cost ofthe solution main board and the BOM cost performance(ii) The blueprint of the examination factors focuses on

Table 6 The weights of alternatives versus the subcriteria

11988211986211

1198601

1198602

119882119888

1198601

100 100 100 047 059 071 01198602

141 171 212 100 100 100 111988211986212

1198601

1198602

119882119888

1198601

100 100 100 036 049 067 01198602

149 203 276 100 100 100 111988211986213

1198601

1198602

119882119888

1198601

100 100 100 069 087 094 031198602

106 115 144 100 100 100 0711988211986221

1198601

1198602

119882119888

1198601

100 100 100 059 088 117 0441198602

085 113 170 100 100 100 05611988211986222

1198601

1198602

119882119888

1198601

100 100 100 057 076 104 0361198602

096 132 176 100 100 100 06411988211986223

1198601

1198602

119882119888

1198601

100 100 100 053 067 080 01198602

125 150 188 100 100 100 111988211986231

1198601

1198602

119882119888

1198601

100 100 100 043 058 077 0091198602

129 174 235 100 100 100 09111988211986232

1198601

1198602

119882119888

1198601

100 100 100 081 104 119 0521198602

084 096 124 100 100 100 04811988211986233

1198601

1198602

119882119888

1198601

100 100 100 059 079 096 0311198602

104 126 169 100 100 100 069

the evaluation issues of (a) competitiveness capability (b)productivity performance and (c) management reliability(iii) This study bridges gaps in previous research concerning

6 Mathematical Problems in Engineering

Table 7 Final score of each alternative

Alternative Score1198601

02761198602

0724

market sensitivity on market trends and customer require-ments (iv) The key characteristics to look at during the ven-dor selection process come from vendorsrsquo viewpoints and thesolution design firmrsquos examination of the impacts from threecriteria and nine subcriteria (v) The results herein indicatethat the strategic vendor evaluation analysis and report can beused as a reference by a firmrsquos operation management whenplanning a strategy for resource allocation

In an ICT technology-driven and customer-centric busi-ness ecosystem firms need to structure a value chain mech-anism through knowledge sharing network collaborationwith key suppliers and customers The scope and scale offuture research should integrate cross-functional cooperationamong teams to widely investigate the supply chain value ina global and dynamic context Given these issues we notethe following (1) Open innovation (OI) which involves agreater number of ideas knowledge areas and experiencescontributed by external partners is the key antecedent ofstrategic decisions made by firms (2) Knowledge manage-ment (KM) which drives firms by sharing and deployingknowledge to organizations for objective achievement is amultidisciplined theoretical approach suitable for industrialpractitioners in research and analysis Therefore in order tobuild up different research criteria that can be integrated withquantitativemeasurement analysis theories for future studieswe propose research objectives on customer value creationand supply chain value through the use of multipurposemodels

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] AH I Lee ldquoA fuzzy supplier selectionmodelwith the consider-ation of benefits opportunities costs and risksrdquo Expert Systemswith Applications vol 36 no 2 pp 2879ndash2893 2009

[2] B Nepal L Monplaisir and O Famuyiwa ldquoMatching productarchitecture with supply chain designrdquo European Journal ofOperational Research vol 216 no 2 pp 312ndash325 2012

[3] M Pero N Abdelkafi A Sianesi and T Blecker ldquoA frameworkfor the alignment of new product development and supplychainsrdquo Supply Chain Management vol 15 no 2 pp 115ndash1282010

[4] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[5] G Bruno E Esposito A Genovese andR Passaro ldquoAHP-basedapproaches for supplier evaluation problems and perspectivesrdquoJournal of Purchasing and Supply Management vol 18 no 3 pp159ndash172 2012

[6] E Elahi ldquoOutsourcing through competition what is the bestcompetition parameterrdquo International Journal of ProductionEconomics vol 144 no 1 pp 370ndash382 2013

[7] M Punniyamoorthy PMathiyalagan and P Parthiban ldquoA stra-tegic model using structural equation modeling and fuzzy logicin supplier selectionrdquo Expert Systems with Applications vol 38no 1 pp 458ndash474 2011

[8] A H I Lee H Kang and C Chang ldquoFuzzy multiple goal pro-gramming applied to TFT-LCD supplier selection by down-stream manufacturersrdquo Expert Systems with Applications vol36 no 3 pp 6318ndash6325 2009

[9] K Shaw R Shankar S S Yadav and L S Thakur ldquoSupplierselection using fuzzy AHP and fuzzy multi-objective linearprogramming for developing low carbon supply chainrdquo ExpertSystems with Applications vol 39 no 9 pp 8182ndash8192 2012

[10] P J M van Laarhoven and W Pedrycz ldquoA fuzzy extension ofSaatyrsquos priority theoryrdquo Fuzzy Sets and Systems vol 11 no 3 pp229ndash241 1983

[11] K P Anagnostopoulos M Gratziou and A P VavatsikosldquoUsing the fuzzy analytic hierarchy process for selecting waste-water facilities at prefectrure levelrdquo European Water pp 15ndash242007

[12] D Chang ldquoApplications of the extent analysis method on fuzzyAHPrdquo European Journal of Operational Research vol 95 no 3pp 649ndash655 1996

[13] I Chamodrakas D Batis and D Martakos ldquoSupplier selectionin electronic marketplaces using satisficing and fuzzy AHPrdquoExpert Systems with Applications vol 37 no 1 pp 490ndash4982010

[14] C A Bana e Costa and J-C Vansnick ldquoA critical analysis of theeigenvalue method used to derive priorities in AHPrdquo EuropeanJournal of Operational Research vol 187 no 3 pp 1422ndash14282008

[15] O Cakir ldquoOn the order of the preference intensities in fuzzyAHPrdquo Computers and Industrial Engineering vol 54 no 4 pp993ndash1005 2008

[16] LMikhailov ldquoDeriving priorities from fuzzy pairwise compari-son judgementsrdquo Fuzzy Sets and Systems vol 134 no 3 pp 365ndash385 2003

[17] O Kilincci and S A Onal ldquoFuzzy AHP approach for supplierselection in a washing machine companyrdquo Expert Systems withApplications vol 38 no 8 pp 9656ndash9664 2011

[18] C Ku C Chang and H Ho ldquoGlobal supplier selection usingfuzzy analytic hierarchy process and fuzzy goal programmingrdquoQuality and Quantity vol 44 no 4 pp 623ndash640 2010

[19] J Rezaei and R Ortt ldquoMulti-criteria supplier segmentationusing a fuzzy preference relations basedAHPrdquoEuropean Journalof Operational Research vol 225 no 1 pp 75ndash84 2013

[20] S Shim and B Lee ldquoSustainable competitive advantage of asystem goods innovator in a market with network effects andentry threatsrdquo Decision Support Systems vol 52 no 2 pp 308ndash317 2012

[21] J-L Chen ldquoThe synergistic effects of IT-enabled resources onorganizational capabilities and firm performancerdquo Informationand Management vol 49 no 3-4 pp 142ndash150 2012

[22] N Harmancioglu ldquoPortfolio of controls in outsourcing rela-tionships for global new product developmentrdquo IndustrialMarketing Management vol 38 no 4 pp 394ndash403 2009

[23] J Zhang and X Liang ldquoBusiness ecosystem strategies of mobilenetwork operators in the 3G era the case of China MobilerdquoTelecommunications Policy vol 35 no 2 pp 156ndash171 2011

Mathematical Problems in Engineering 7

[24] S J Wu and G L Ragatz ldquoEvaluating the total effect of earlysupplier involvement on project team effectiveness collabora-tion and interactionrdquo International Journal of Integrated SupplyManagement vol 5 no 3 pp 239ndash259 2010

[25] T L Esper A E Ellinger T P Stank D J Flint and M MoonldquoDemand and supply integration a conceptual framework ofvalue creation through knowledge managementrdquo Journal of theAcademy of Marketing Science vol 38 no 1 pp 5ndash18 2010

[26] P Hilletofth and D Eriksson ldquoCoordinating new productdevelopment with supply chain managementrdquo Industrial Man-agement and Data Systems vol 111 no 2 pp 264ndash281 2011

[27] J Roshandel S S Miri-Nargesi and L Hatami-ShirkouhildquoEvaluating and selecting the supplier in detergent productionindustry using hierarchical fuzzy TOPSISrdquo Applied Mathemat-ical Modelling vol 37 no 24 pp 10170ndash10181 2013

[28] A Zouggari and L Benyoucef ldquoSimulation based fuzzy TOPSISapproach for group multi-criteria supplier selection problemrdquoEngineering Applications of Artificial Intelligence vol 25 no 3pp 507ndash519 2012

[29] DWu D DWu Y Zhang and D L Olson ldquoSupply chain out-sourcing risk using an integrated stochastic-fuzzy optimizationapproachrdquo Information Sciences vol 235 pp 242ndash258 2013

[30] Y Kristianto P Helo J R Jiao and M Sandhu ldquoAdaptive fuzzyvendor managed inventory control for mitigating the Bull-whip effect in supply chainsrdquo European Journal of OperationalResearch vol 216 no 2 pp 346ndash355 2012

[31] LOsiro F R Lima-Junior andLC RCarpinetti ldquoA fuzzy logicapproach to supplier evaluation for developmentrdquo InternationalJournal of Production Economics vol 153 pp 95ndash112 2014

[32] Y Chen and R Chao ldquoSupplier selection using consistent fuzzypreference relationsrdquo Expert Systems with Applications vol 39no 3 pp 3233ndash3240 2012

[33] C-Y Shen and K-T Yu ldquoEnhancing the efficacy of supplierselection decision-making on the initial stage of new productdevelopment a hybrid fuzzy approach considering the strategicand operational factors simultaneouslyrdquo Expert Systems withApplications vol 36 no 8 pp 11271ndash11281 2009

[34] I Ruuska T Ahola M Martinsuo and T Westerholm ldquoSup-plier capabilities in large shipbuilding projectsrdquo InternationalJournal of Project Management vol 31 no 4 pp 542ndash553 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

6 Mathematical Problems in Engineering

Table 7 Final score of each alternative

Alternative Score1198601

02761198602

0724

market sensitivity on market trends and customer require-ments (iv) The key characteristics to look at during the ven-dor selection process come from vendorsrsquo viewpoints and thesolution design firmrsquos examination of the impacts from threecriteria and nine subcriteria (v) The results herein indicatethat the strategic vendor evaluation analysis and report can beused as a reference by a firmrsquos operation management whenplanning a strategy for resource allocation

In an ICT technology-driven and customer-centric busi-ness ecosystem firms need to structure a value chain mech-anism through knowledge sharing network collaborationwith key suppliers and customers The scope and scale offuture research should integrate cross-functional cooperationamong teams to widely investigate the supply chain value ina global and dynamic context Given these issues we notethe following (1) Open innovation (OI) which involves agreater number of ideas knowledge areas and experiencescontributed by external partners is the key antecedent ofstrategic decisions made by firms (2) Knowledge manage-ment (KM) which drives firms by sharing and deployingknowledge to organizations for objective achievement is amultidisciplined theoretical approach suitable for industrialpractitioners in research and analysis Therefore in order tobuild up different research criteria that can be integrated withquantitativemeasurement analysis theories for future studieswe propose research objectives on customer value creationand supply chain value through the use of multipurposemodels

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] AH I Lee ldquoA fuzzy supplier selectionmodelwith the consider-ation of benefits opportunities costs and risksrdquo Expert Systemswith Applications vol 36 no 2 pp 2879ndash2893 2009

[2] B Nepal L Monplaisir and O Famuyiwa ldquoMatching productarchitecture with supply chain designrdquo European Journal ofOperational Research vol 216 no 2 pp 312ndash325 2012

[3] M Pero N Abdelkafi A Sianesi and T Blecker ldquoA frameworkfor the alignment of new product development and supplychainsrdquo Supply Chain Management vol 15 no 2 pp 115ndash1282010

[4] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[5] G Bruno E Esposito A Genovese andR Passaro ldquoAHP-basedapproaches for supplier evaluation problems and perspectivesrdquoJournal of Purchasing and Supply Management vol 18 no 3 pp159ndash172 2012

[6] E Elahi ldquoOutsourcing through competition what is the bestcompetition parameterrdquo International Journal of ProductionEconomics vol 144 no 1 pp 370ndash382 2013

[7] M Punniyamoorthy PMathiyalagan and P Parthiban ldquoA stra-tegic model using structural equation modeling and fuzzy logicin supplier selectionrdquo Expert Systems with Applications vol 38no 1 pp 458ndash474 2011

[8] A H I Lee H Kang and C Chang ldquoFuzzy multiple goal pro-gramming applied to TFT-LCD supplier selection by down-stream manufacturersrdquo Expert Systems with Applications vol36 no 3 pp 6318ndash6325 2009

[9] K Shaw R Shankar S S Yadav and L S Thakur ldquoSupplierselection using fuzzy AHP and fuzzy multi-objective linearprogramming for developing low carbon supply chainrdquo ExpertSystems with Applications vol 39 no 9 pp 8182ndash8192 2012

[10] P J M van Laarhoven and W Pedrycz ldquoA fuzzy extension ofSaatyrsquos priority theoryrdquo Fuzzy Sets and Systems vol 11 no 3 pp229ndash241 1983

[11] K P Anagnostopoulos M Gratziou and A P VavatsikosldquoUsing the fuzzy analytic hierarchy process for selecting waste-water facilities at prefectrure levelrdquo European Water pp 15ndash242007

[12] D Chang ldquoApplications of the extent analysis method on fuzzyAHPrdquo European Journal of Operational Research vol 95 no 3pp 649ndash655 1996

[13] I Chamodrakas D Batis and D Martakos ldquoSupplier selectionin electronic marketplaces using satisficing and fuzzy AHPrdquoExpert Systems with Applications vol 37 no 1 pp 490ndash4982010

[14] C A Bana e Costa and J-C Vansnick ldquoA critical analysis of theeigenvalue method used to derive priorities in AHPrdquo EuropeanJournal of Operational Research vol 187 no 3 pp 1422ndash14282008

[15] O Cakir ldquoOn the order of the preference intensities in fuzzyAHPrdquo Computers and Industrial Engineering vol 54 no 4 pp993ndash1005 2008

[16] LMikhailov ldquoDeriving priorities from fuzzy pairwise compari-son judgementsrdquo Fuzzy Sets and Systems vol 134 no 3 pp 365ndash385 2003

[17] O Kilincci and S A Onal ldquoFuzzy AHP approach for supplierselection in a washing machine companyrdquo Expert Systems withApplications vol 38 no 8 pp 9656ndash9664 2011

[18] C Ku C Chang and H Ho ldquoGlobal supplier selection usingfuzzy analytic hierarchy process and fuzzy goal programmingrdquoQuality and Quantity vol 44 no 4 pp 623ndash640 2010

[19] J Rezaei and R Ortt ldquoMulti-criteria supplier segmentationusing a fuzzy preference relations basedAHPrdquoEuropean Journalof Operational Research vol 225 no 1 pp 75ndash84 2013

[20] S Shim and B Lee ldquoSustainable competitive advantage of asystem goods innovator in a market with network effects andentry threatsrdquo Decision Support Systems vol 52 no 2 pp 308ndash317 2012

[21] J-L Chen ldquoThe synergistic effects of IT-enabled resources onorganizational capabilities and firm performancerdquo Informationand Management vol 49 no 3-4 pp 142ndash150 2012

[22] N Harmancioglu ldquoPortfolio of controls in outsourcing rela-tionships for global new product developmentrdquo IndustrialMarketing Management vol 38 no 4 pp 394ndash403 2009

[23] J Zhang and X Liang ldquoBusiness ecosystem strategies of mobilenetwork operators in the 3G era the case of China MobilerdquoTelecommunications Policy vol 35 no 2 pp 156ndash171 2011

Mathematical Problems in Engineering 7

[24] S J Wu and G L Ragatz ldquoEvaluating the total effect of earlysupplier involvement on project team effectiveness collabora-tion and interactionrdquo International Journal of Integrated SupplyManagement vol 5 no 3 pp 239ndash259 2010

[25] T L Esper A E Ellinger T P Stank D J Flint and M MoonldquoDemand and supply integration a conceptual framework ofvalue creation through knowledge managementrdquo Journal of theAcademy of Marketing Science vol 38 no 1 pp 5ndash18 2010

[26] P Hilletofth and D Eriksson ldquoCoordinating new productdevelopment with supply chain managementrdquo Industrial Man-agement and Data Systems vol 111 no 2 pp 264ndash281 2011

[27] J Roshandel S S Miri-Nargesi and L Hatami-ShirkouhildquoEvaluating and selecting the supplier in detergent productionindustry using hierarchical fuzzy TOPSISrdquo Applied Mathemat-ical Modelling vol 37 no 24 pp 10170ndash10181 2013

[28] A Zouggari and L Benyoucef ldquoSimulation based fuzzy TOPSISapproach for group multi-criteria supplier selection problemrdquoEngineering Applications of Artificial Intelligence vol 25 no 3pp 507ndash519 2012

[29] DWu D DWu Y Zhang and D L Olson ldquoSupply chain out-sourcing risk using an integrated stochastic-fuzzy optimizationapproachrdquo Information Sciences vol 235 pp 242ndash258 2013

[30] Y Kristianto P Helo J R Jiao and M Sandhu ldquoAdaptive fuzzyvendor managed inventory control for mitigating the Bull-whip effect in supply chainsrdquo European Journal of OperationalResearch vol 216 no 2 pp 346ndash355 2012

[31] LOsiro F R Lima-Junior andLC RCarpinetti ldquoA fuzzy logicapproach to supplier evaluation for developmentrdquo InternationalJournal of Production Economics vol 153 pp 95ndash112 2014

[32] Y Chen and R Chao ldquoSupplier selection using consistent fuzzypreference relationsrdquo Expert Systems with Applications vol 39no 3 pp 3233ndash3240 2012

[33] C-Y Shen and K-T Yu ldquoEnhancing the efficacy of supplierselection decision-making on the initial stage of new productdevelopment a hybrid fuzzy approach considering the strategicand operational factors simultaneouslyrdquo Expert Systems withApplications vol 36 no 8 pp 11271ndash11281 2009

[34] I Ruuska T Ahola M Martinsuo and T Westerholm ldquoSup-plier capabilities in large shipbuilding projectsrdquo InternationalJournal of Project Management vol 31 no 4 pp 542ndash553 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 7

[24] S J Wu and G L Ragatz ldquoEvaluating the total effect of earlysupplier involvement on project team effectiveness collabora-tion and interactionrdquo International Journal of Integrated SupplyManagement vol 5 no 3 pp 239ndash259 2010

[25] T L Esper A E Ellinger T P Stank D J Flint and M MoonldquoDemand and supply integration a conceptual framework ofvalue creation through knowledge managementrdquo Journal of theAcademy of Marketing Science vol 38 no 1 pp 5ndash18 2010

[26] P Hilletofth and D Eriksson ldquoCoordinating new productdevelopment with supply chain managementrdquo Industrial Man-agement and Data Systems vol 111 no 2 pp 264ndash281 2011

[27] J Roshandel S S Miri-Nargesi and L Hatami-ShirkouhildquoEvaluating and selecting the supplier in detergent productionindustry using hierarchical fuzzy TOPSISrdquo Applied Mathemat-ical Modelling vol 37 no 24 pp 10170ndash10181 2013

[28] A Zouggari and L Benyoucef ldquoSimulation based fuzzy TOPSISapproach for group multi-criteria supplier selection problemrdquoEngineering Applications of Artificial Intelligence vol 25 no 3pp 507ndash519 2012

[29] DWu D DWu Y Zhang and D L Olson ldquoSupply chain out-sourcing risk using an integrated stochastic-fuzzy optimizationapproachrdquo Information Sciences vol 235 pp 242ndash258 2013

[30] Y Kristianto P Helo J R Jiao and M Sandhu ldquoAdaptive fuzzyvendor managed inventory control for mitigating the Bull-whip effect in supply chainsrdquo European Journal of OperationalResearch vol 216 no 2 pp 346ndash355 2012

[31] LOsiro F R Lima-Junior andLC RCarpinetti ldquoA fuzzy logicapproach to supplier evaluation for developmentrdquo InternationalJournal of Production Economics vol 153 pp 95ndash112 2014

[32] Y Chen and R Chao ldquoSupplier selection using consistent fuzzypreference relationsrdquo Expert Systems with Applications vol 39no 3 pp 3233ndash3240 2012

[33] C-Y Shen and K-T Yu ldquoEnhancing the efficacy of supplierselection decision-making on the initial stage of new productdevelopment a hybrid fuzzy approach considering the strategicand operational factors simultaneouslyrdquo Expert Systems withApplications vol 36 no 8 pp 11271ndash11281 2009

[34] I Ruuska T Ahola M Martinsuo and T Westerholm ldquoSup-plier capabilities in large shipbuilding projectsrdquo InternationalJournal of Project Management vol 31 no 4 pp 542ndash553 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of