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A framework and algorithm for fair demand and capacity sharing in collaborative networks

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  • Yilmaz, Ibrahim
  • Yoon, Sang Won
  • Seok, Hyesung

Abstract

This paper presents a framework for balancing fairness and efficiency in the collaborative networks (CNs) of enterprises. In any CN, the collaboration process often leads to a dilemma: the need to choose between fairness and efficiency. The objective of this research is to propose an algorithm that attempts to increase optimal weights of fairness while maintaining efficiency. In this research, two concepts are utilized to distinguish the balance between fairness and efficiency in CNs: 1) the generalized α-fair concept; and 2) Jain's fairness index. The performance of the proposed algorithm has been tested with conceptual heterogeneous and homogeneous CNs (HeCNs and HoCNs, respectively) based on the enterprise capacity. The experimental results indicate that a balance between efficiency and fairness in CNs is possible while forming a network and obtaining mutual benefits fairly among the enterprises. In addition, the proposed algorithm can minimize the deviation between most and least beneficial enterprises in CN in terms of total profit, lost sale cost, and inventory cost.

Suggested Citation

  • Yilmaz, Ibrahim & Yoon, Sang Won & Seok, Hyesung, 2017. "A framework and algorithm for fair demand and capacity sharing in collaborative networks," International Journal of Production Economics, Elsevier, vol. 193(C), pages 137-147.
  • Handle: RePEc:eee:proeco:v:193:y:2017:i:c:p:137-147
    DOI: 10.1016/j.ijpe.2017.06.027
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    References listed on IDEAS

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    1. Yoon, Sang Won & Nof, Shimon Y., 2011. "Affiliation/dissociation decision models in demand and capacity sharing collaborative network," International Journal of Production Economics, Elsevier, vol. 130(2), pages 135-143, April.
    2. Galeotti, Andrea & Goyal, Sanjeev & Kamphorst, Jurjen, 2006. "Network formation with heterogeneous players," Games and Economic Behavior, Elsevier, vol. 54(2), pages 353-372, February.
    3. Moghaddam, Mohsen & Nof, Shimon Y., 2014. "Combined demand and capacity sharing with best matching decisions in enterprise collaboration," International Journal of Production Economics, Elsevier, vol. 148(C), pages 93-109.
    4. Moghaddam, Mohsen & Nof, Shimon Y., 2016. "Real-time optimization and control mechanisms for collaborative demand and capacity sharing," International Journal of Production Economics, Elsevier, vol. 171(P4), pages 495-506.
    5. Thomas, Douglas J. & Griffin, Paul M., 1996. "Coordinated supply chain management," European Journal of Operational Research, Elsevier, vol. 94(1), pages 1-15, October.
    6. Seok, Hyesung & Nof, Shimon Y., 2014. "Dynamic coalition reformation for adaptive demand and capacity sharing," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 136-146.
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    Cited by:

    1. Yilmaz, Ibrahim & Yoon, Sang Won, 2020. "Dynamic-distributed decisions and sharing protocol for fair resource sharing in collaborative network," International Journal of Production Economics, Elsevier, vol. 226(C).
    2. Lohmer, Jacob & Bugert, Niels & Lasch, Rainer, 2020. "Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study," International Journal of Production Economics, Elsevier, vol. 228(C).

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