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Supply Chain Performance Measurement Using a SCOR Based Fuzzy VIKOR Approach

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Supply Chain Management Under Fuzziness

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 313))

Abstract

Supply Chain performance measurement is a vital issue for supply chain management. Both from the academia and professional life, various models are proposed for this subject. In this chapter, the literature is investigated for current performance measurement models and a multi-criteria decision making approach is proposed for supply chain performance measurement. In this study, SCOR model is used for structuring the problem, Fuzzy Analytic Hierarchy Process (AHP) is used to determine the importance weights of the criteria and finally Fuzzy VIKOR is used to rank the alternatives based on expert evaluations.

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References

  • Baykasoglu, A., Kaplanoglu, V.: Application of activity-based costing to a land transportation company: a case study. Int. J. Prod. Econ. 116(2), 308–324 (2008)

    Article  Google Scholar 

  • Beamon, B.M.: Supply chain design and analysis: models and methods. Int. J. Prod. Econ. 55, 281–294 (1998)

    Article  Google Scholar 

  • Bhagwat, R., Sharma, M.K.: Performance measurement of supply chain management: a balanced scorecard approach. Comput. Ind. Eng. 53(1), 43–62 (2007a)

    Article  Google Scholar 

  • Bhagwat, R., Sharma, M.K.: Performance measurement of supply chain management using the analytical hierarchy process. Prod. Plann. Control 18(8), 666–680 (2007b)

    Article  Google Scholar 

  • Bhagwat, R., Sharma, M.K.: An application of the integrated AHP-PGP model for performance measurement of supply chain management. Prod. Plann. Control 20(8), 678–690 (2009)

    Article  Google Scholar 

  • Brewer, P.C., Speh, T.W.: Using the balanced scorecard to measure supply chain performance. J. Bus. Logistics 21(1), 75–94 (2000)

    Google Scholar 

  • Buckley, J.J.: Fuzzy hierarchical analysis. Fuzzy Sets and Syst. 17, 233–247 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  • Cagnazzo, L., Taticchi, P., Brun, A.: The role of performance measurement systems to support quality improvement initiatives at supply chain level. Int. J. Prod. Perform. Manage. 59(2), 163–185 (2010)

    Article  Google Scholar 

  • Chan, F.T.S.: Performance measurement in a supply chain. Int. J. Adv. Manuf. Technol. 21(7), 534–548 (2003)

    Article  Google Scholar 

  • Chan, F.T.S., Qi, H.: An innovative performance measurement method for supply chain management. Supply Chain Manag. Int. J. 8(3), 209–223 (2003)

    Article  MathSciNet  Google Scholar 

  • Chang, D.Y.: Applications of the extent analysis method on fuzzy AHP European. J.Oper. Res. 95, 649–655 (1996)

    Article  MATH  Google Scholar 

  • Chen, L.Y., Wang, T.C.: Optimizing partners’ choice in IS/IT outsourcing projects: the strategic decision of fuzzy VIKOR. Int. J. Prod. Econ. 120(1), 233–242 (2009)

    Article  Google Scholar 

  • Cooper, M.C., Lambert, D.M., Pagh, J.D.: Supply chain management: more than a new name for logistics. Int. J. Logistics Manage. 8(1), 1–14 (1997)

    Article  Google Scholar 

  • El-Baz, M.A.: Fuzzy performance measurement of a supply chain in manufacturing companies. Expert Syst. Appl 38(6), 6681–6688 (2011)

    Article  Google Scholar 

  • Elgazzar, S.H., Tipi, N.S., Hubbard, N.J., Leach, D.Z.: Linking supply chain processes performance to a company’s financial strategic objectives. Eur. J. Oper. Res. 223(1), 276–289 (2012)

    Article  Google Scholar 

  • Estampe, D., Lamouri, S., Paris, J.-L., Brahim-Djelloul, S.: A framework for analysing supply chain performance evaluation models. Int. J. Prod. Econ. 142(2), 247–258 (2013)

    Article  Google Scholar 

  • Felix, T.S., Chan, H.Q.: Feasibility of performance measurement system for supply chain: a process-based approach and measures. Integr. Manuf. Syst. 14(3), 179–190 (2003)

    Article  Google Scholar 

  • Folan, P., Browne, J., Jagdev, H.: Performance: Its meaning and content for today’s business research. Comput. Ind. 58, 605–620 (2007)

    Article  Google Scholar 

  • Forme, F.-A.G.L., Genoulaz, V.B., Campagne, J.-P.: A framework to analyse collaborative performance. Comput. Ind. 58(7), 687–697 (2007)

    Article  Google Scholar 

  • Ganga, G.M.D., Carpinetti, L.C.R.: A fuzzy logic approach to supply chain performance management. Int. J. Prod. Econ. 134(1), 177–187 (2011)

    Article  Google Scholar 

  • Gilmour, P.: A strategic audit framework to improve supply chain performance. J. Bus. Ind. Mark. 14(5), 355–366 (1999)

    Article  Google Scholar 

  • Gou, J., Shen, G., Chai, R.: Model of service-oriented catering supply chain performance evaluation. J. Ind. Eng. Manage. 6(1), 215–226 (2013)

    Google Scholar 

  • Gunasekaran, A., Patel, C., McGaughey, R.E.: A framework for supply chain performance measurement. Int. J. Prod. Econ. 87(3), 333–347 (2004)

    Article  Google Scholar 

  • Harris, J.K., Swatman, P.M.: Efficient consumer response (ECR): a survey of the Australian grocery industry. Supply Chain Manage. Int. J. 4(1), 35–42 (1999)

    Article  Google Scholar 

  • Kaplan, R.S., Norton, D.P.: The Balanced Scorecard—Measures That Drive Performance. Harvard Business Review, January–February, pp. 71–79 (1992)

    Google Scholar 

  • Kulak, O., Kahraman, C.: Fuzzy Multi-Attribute Selection Among Transportation Companies Using Axiomatic Design and Analytic Hierarchy Process. Inf. Sci. 170, 191–210 (2005)

    Article  MATH  Google Scholar 

  • Kurnia, S., Johnston, R.B.: Adoption of efficient consumer response: the issue of mutuality. Supply Chain Manage Int. J. 6(5), 230–241 (2001)

    Article  Google Scholar 

  • Lambert, D.M., Pohlen, T.L.: Supply chain metrics. Int. J. Logistics Manage. 12(1), 1–19 (2001)

    Article  Google Scholar 

  • Lebas, M.: Performance measurement and performance management. Int. J. Prod. Econ. 41, 23–25 (1995)

    Article  Google Scholar 

  • Li, S., Rao, S.S., Ragu-Nathan, T., Ragu-Nathan, B.: Development and validation of a measurement instrument for studying supply chain management practices. J. Opertions Manage. 23(6), 618–641 (2005)

    Article  Google Scholar 

  • Lin, R.-J.: Using fuzzy DEMATEL to evaluate the green supply chain management practices. J. Cleaner Prod. 40, 32–39 (2013)

    Article  Google Scholar 

  • Lohtia, R., Tian, F., Xie, Subramaniam, R.: Efficient consumer response in Japan: Industry concerns, current status, benefits, and barriers to implementation. J. Bus. Res. 57(3), 306–311 (2004)

    Article  Google Scholar 

  • McCormac, K., Wilkerson, T., Marrow, D., Davey, M., Shah, M., Yee, D.: Managing Risk in Your Organization with the SCOR Methodology, http://supply-chain.org/f/Supply%20Chain%20Risk%20Project%20Report.pdf(2008)

  • Meyer, M.W.: Rethinking Performance Measurement: Beyond the Balanced Scorecard. Cambridge University Press, New York (2002)

    Google Scholar 

  • Moussa, A.M., Kamdem, J.S., Terraza, M.: Fuzzy risk adjusted performance measures: Application to Hedge funds, Insurance: Mathematics and Economics, Article in press (2012)

    Google Scholar 

  • Naini, S.G.J., Aliahmadi, A.R., Jafari-Eskandari, M.: Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: a case study of an auto industry supply chain. Resour. Conserv. Recycl. 55(6), 593–603 (2011)

    Article  Google Scholar 

  • Najmi, A., Makui, A.: Providing hierarchical approach for measuring supply chain performance using AHP and DEMATEL methodologies. Int. J. Ind. Eng. Comput. 1, 199–212 (2010)

    Google Scholar 

  • Odette.: 2013. www.odette.org/html/home.htm. (Accessed:24/03/2013)

  • Opricovic, S., Tzeng, G.H.: Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 156, 445–455 (2004)

    Article  MATH  Google Scholar 

  • Pan, N.F., Lin, T.C., Pan, N.H.: Estimating bridge performance based on a matrix-driven fuzzy linear regression model. Autom. Constr. 18(5), 578–586 (2009)

    Article  Google Scholar 

  • Qian, L., Ben-Arieh, D.: Parametric cost estimation based on activity-based costing: a case study for design and development of rotational parts. Int. J. Prod. Econ. 113(2), 805–818 (2008)

    Article  Google Scholar 

  • Ravi, V., Shankar, R., Tiwari, M.K.: Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach. Comput. Ind. Eng. 48(2), 327–356 (2005)

    Article  Google Scholar 

  • Saaty, T.L.: The Analytic Hierarchy Process. McGraw Hill. RWS Publications, New York (1980)

    MATH  Google Scholar 

  • Sanayei, A., Mousavi, S.F., Yazdankhah, A.: Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Syst. Appl. 37(1), 24–30 (2010)

    Article  Google Scholar 

  • SCC (2010). Supply Chain Council SCOR Model Version 10.00—Appendix A., Available at: http://supply-chain.org/f/SCOR%208.0%20Metrics%20tables.pdf

  • Schulze, M., Seuring, S., Ewering, C.: Applying activity-based costing in a supply chain environment. Int. J. Prod. Econ. 135(2), 716–725 (2012)

    Article  Google Scholar 

  • Shemshadi, A., Shirazi, H., Toreihi, M., Tarokh, M.J.: A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst. Appl. 38(10), 12160–12167 (2011)

    Article  Google Scholar 

  • Stapleton, D., Hanna, J.B., Yagla, S., Johnson Markussen, D.: Measuring logistics performance using the strategic profit model. Int. J. Logistics Manage. 13(1), 89–107 (2002)

    Article  Google Scholar 

  • Theeranuphattana, A., Tang, J.C., Khang, D.B.: An integrated approach to measuring supply chain performance. Ind. Eng. Manage. Syst. 11(1), 54–69 (2012)

    Google Scholar 

  • Tsai, W.-H., Hung, S.-J.: A fuzzy goal programming approach for green supply chain optimisation under activity-based costing and performance evaluation with a value-chain structure. Int. J. Prod. Res. 47(18), 4991–5017 (2009)

    Article  MATH  Google Scholar 

  • van Laarhoven, P.J.M., Pedrycz, W.: A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst. 11, 229–241 (1983)

    Article  MATH  Google Scholar 

  • Wang, G., Huang, S.H., Dismukes, J.P.: Product-driven supply chain selection using integrated multi-criteria decision-making methodology. Int. J. Prod. Econ. 91(1), 1–15 (2004)

    Article  Google Scholar 

  • Yalcin, N., Bayrakdaroglu, A., Kahraman, C.: Application of fuzzy multi-criteria decision making methods for financial performance evaluation of Turkish manufacturing industries. Expert Syst. Appl. 39(1), 350–364 (2012)

    Article  Google Scholar 

  • Yu, P.L.: A class of solutions for group decision problems. Manage. Sci. 19, 936–946 (1973)

    Article  MATH  Google Scholar 

  • Yu, X., Guo, S., Guo, J., Huang, X.: Rank B2C e-commerce websites in e-alliance based on AHP and fuzzy TOPSIS. Expert Syst. Appl. 38(4), 3550–3557 (2011)

    Article  Google Scholar 

  • Zadeh, L.: Fuzzy Sets. Inf. Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  • Zeleny, M.: Multiple Criteria Decision Making. McGraw-Hill, New York (1982)

    MATH  Google Scholar 

  • Zhihong, W., Yan, W., He, W.: Performance evaluation indicator system and model construction of the green supply chain. In: Intelligent system design and engineering applications, pp. 1042–1044 (2013)

    Google Scholar 

  • Zhou, Z., Zhao, L., Lui, S., Ma, C.: A generalized fuzzy DEA/AR performance assessment model. Math. Comput. Modell. 55(11/12), 2117–2128 (2012)

    Article  MATH  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, 34367, Macka Istanbul, Turkey

    Başar Öztayşi & Özge Sürer

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  1. Başar Öztayşi
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  2. Özge Sürer
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Correspondence to Başar Öztayşi .

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Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, İstanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University, İstanbul, Turkey

    Başar Öztayşi

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Öztayşi, B., Sürer, Ö. (2014). Supply Chain Performance Measurement Using a SCOR Based Fuzzy VIKOR Approach. In: Kahraman, C., Öztayşi, B. (eds) Supply Chain Management Under Fuzziness. Studies in Fuzziness and Soft Computing, vol 313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53939-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-53939-8_9

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