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An integrated fuzzy-goal-programming-based framework for selecting suppliers in strategic alliance formation

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  • Famuyiwa, Oluwafemi
  • Monplaisir, Leslie
  • Nepal, Bimal

Abstract

There has been an exponential growth in the number of strategic alliances formed in the last decade between manufacturers and their suppliers. Yet 60-70% of these alliances fail in their first year. One of the reasons for such failure is the incompatibility of members of the alliance. Hence, there is a need for a tool to help decision makers to rate the compatibility of potential partners in a strategic alliance. This paper fulfills this requirement by presenting an integrated method for rating the compatibility of potential members of a strategic alliance. The method utilizes a model based on fuzzy logic/goal programming to analyze the vague, imprecise, and usually subjective information regarding the compatibility of potential suppliers that is available during the early formation of a strategic partnership. A sample case study is presented to demonstrate the application of the framework.

Suggested Citation

  • Famuyiwa, Oluwafemi & Monplaisir, Leslie & Nepal, Bimal, 2008. "An integrated fuzzy-goal-programming-based framework for selecting suppliers in strategic alliance formation," International Journal of Production Economics, Elsevier, vol. 113(2), pages 862-875, June.
    • Handle: RePEc:eee:proeco:v:113:y:2008:i:2:p:862-875
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    References listed on IDEAS

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    Cited by:

    1. Oderanti, Festus Oluseyi & De Wilde, Philippe, 2010. "Dynamics of business games with management of fuzzy rules for decision making," International Journal of Production Economics, Elsevier, vol. 128(1), pages 96-109, November.
    2. Chia Sun, 2014. "A conceptual framework for R&D strategic alliance assessment for Taiwan’s biotechnology industry," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 259-279, January.
    3. Zeki Ayağ & Funda Samanlioglu, 2016. "An intelligent approach to supplier evaluation in automotive sector," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 889-903, August.
    4. Feng, Bo & Fan, Zhi-Ping & Ma, Jian, 2010. "A method for partner selection of codevelopment alliances using individual and collaborative utilities," International Journal of Production Economics, Elsevier, vol. 124(1), pages 159-170, March.
    5. Woo, Hong Seng & Saghiri, Soroosh, 2011. "Order assignment considering buyer, third-party logistics provider, and suppliers," International Journal of Production Economics, Elsevier, vol. 130(2), pages 144-152, April.
    6. Dinu Simona & Pacuraru Raluca, 2011. "Intelligent modeling method based on genetic algorithm for partner selection in virtual organizations," Business and Economic Horizons (BEH), Prague Development Center, vol. 5(2), pages 23-34, April.
    7. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.
    8. Simona, Dinu & Raluca, Pacuraru, 2011. "Intelligent modeling method based on genetic algorithm for partner selection in virtual organizations," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 5(2), pages 1-12, April.

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