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DEA models for supply chain efficiency evaluation

Author

Listed:
  • Liang Liang
  • Feng Yang
  • Wade Cook
  • Joe Zhu

Abstract

An appropriate performance measurement system is an important requirement for the effective management of a supply chain. Two hurdles are present in measuring the performance of a supply chain and its members. One is the existence of multiple measures that characterize the performance of chain members, and for which data must be acquired; the other is the existence of conflicts between the members of the chain with respect to specific measures. Conventional data envelopment analysis (DEA) cannot be employed directly to measure the performance of supply chain and its members, because of the existence of the intermediate measures connecting the supply chain members. In this paper it is shown that a supply chain can be deemed as efficient while its members may be inefficient in DEA-terms. The current study develops several DEA-based approaches for characterizing and measuring supply chain efficiency when intermediate measures are incorporated into the performance evaluation. The models are illustrated in a seller-buyer supply chain context, when the relationship between the seller and buyer is treated first as one of leader-follower, and second as one that is cooperative. In the leader-follower structure, the leader is first evaluated, and then the follower is evaluated using information related to the leader's efficiency. In the cooperative structure, the joint efficiency which is modelled as the average of the seller's and buyer's efficiency scores is maximized, and both supply chain members are evaluated simultaneously. Non-linear programming problems are developed to solve these new supply chain efficiency models. It is shown that these DEA-based non-linear programs can be treated as parametric linear programming problems, and best solutions can be obtained via a heuristic technique. The approaches are demonstrated with a numerical example. Copyright Springer Science+Business Media, LLC 2006

Suggested Citation

  • Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
  • Handle: RePEc:spr:annopr:v:145:y:2006:i:1:p:35-49:10.1007/s10479-006-0026-7
    DOI: 10.1007/s10479-006-0026-7
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    References listed on IDEAS

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    1. Porter, Michael E, 1974. "Consumer Behavior, Retailer Power and Market Performance in Consumer Goods Industries," The Review of Economics and Statistics, MIT Press, vol. 56(4), pages 419-436, November.
    2. Zhimin Huang, 2000. "Franchising cooperation through chance cross‐constrained games," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(8), pages 669-685, December.
    3. Hau L. Lee & Corey Billington, 1993. "Material Management in Decentralized Supply Chains," Operations Research, INFORMS, vol. 41(5), pages 835-847, October.
    4. Li, Susan X. & Huang, Zhimin & Ashley, Allan, 1996. "Improving buyer-seller system cooperation through inventory control," International Journal of Production Economics, Elsevier, vol. 43(1), pages 37-46, May.
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