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Further study of production possibility set and performance evaluation model in supply chain DEA

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  • Zhongbao Zhou
  • Mei Wang
  • Hui Ding
  • Chaoqun Ma
  • Wenbin Liu

Abstract

Performance evaluation is an importance issue in supply chain management. Yang et al. (Ann. Oper. Res. 38(6):195–211, 2011 ) defined two types of supply chain production possibility sets and proved the equivalence between them. Based on the sub-perfect CRS production possibility set, they proposed a supply chain DEA model to appraise the overall technical efficiency of supply chains. The relationship among efficiency scores of the proposed model, CCR models of system and subsystems are discussed. However, we find that the equivalence between the two types of supply chain production possibility sets is not correct. The proofs of their three theorems are all problematic. In this paper, we correct some results and give three new proofs. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Zhongbao Zhou & Mei Wang & Hui Ding & Chaoqun Ma & Wenbin Liu, 2013. "Further study of production possibility set and performance evaluation model in supply chain DEA," Annals of Operations Research, Springer, vol. 206(1), pages 585-592, July.
    • Handle: RePEc:spr:annopr:v:206:y:2013:i:1:p:585-592:10.1007/s10479-013-1365-9
    DOI: 10.1007/s10479-013-1365-9
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    References listed on IDEAS

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    1. Chen, Ci & Yan, Hong, 2011. "Network DEA model for supply chain performance evaluation," European Journal of Operational Research, Elsevier, vol. 213(1), pages 147-155, August.
    2. Feng Yang & Dexiang Wu & Liang Liang & Gongbing Bi & Desheng Wu, 2011. "Supply chain DEA: production possibility set and performance evaluation model," Annals of Operations Research, Springer, vol. 185(1), pages 195-211, May.
    3. Cook, Wade D. & Liang, Liang & Zhu, Joe, 2010. "Measuring performance of two-stage network structures by DEA: A review and future perspective," Omega, Elsevier, vol. 38(6), pages 423-430, December.
    4. Markus Biehl & Wade Cook & David Johnston, 2006. "The efficiency of joint decision making in buyer-supplier relationships," Annals of Operations Research, Springer, vol. 145(1), pages 15-34, July.
    5. Zhu, Joe, 2004. "A buyer-seller game model for selection and negotiation of purchasing bids: Extensions and new models," European Journal of Operational Research, Elsevier, vol. 154(1), pages 150-156, April.
    6. Edgar Alfonso & Dusko Kalenatic & Cesar López, 2010. "Modeling the synergy level in a vertical collaborative supply chain through the IMP interaction model and DEA framework," Annals of Operations Research, Springer, vol. 181(1), pages 813-827, December.
    7. Yao Chen & Liang Liang & Feng Yang, 2006. "A DEA game model approach to supply chain efficiency," Annals of Operations Research, Springer, vol. 145(1), pages 5-13, July.
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    2. Sinem Buyuksaatci Kiris & Enes Eryarsoy & Selim Zaim & Dursun Delen, 2023. "An integrated approach for lean production using simulation and data envelopment analysis," Annals of Operations Research, Springer, vol. 320(2), pages 863-886, January.
    3. Masoud Rabbani & Reza Yazdanparast & Mahdi Mobini, 2019. "An algorithm for performance evaluation of resilience engineering culture based on graph theory and matrix approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 228-241, April.
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    5. Liu, Wenbin & Zhou, Zhongbao & Liu, Debin & Xiao, Helu, 2015. "Estimation of portfolio efficiency via DEA," Omega, Elsevier, vol. 52(C), pages 107-118.

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