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Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application

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  • Mohammad Amirkhan

    (Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran)

  • Hosein Didehkhani

    (Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran)

  • Kaveh Khalili-Damghani

    (Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran)

  • Ashkan Hafezalkotob

    (Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran)

Abstract

The issue of efficiency analysis of network and multi-stage systems, as one of the most interesting fields in data envelopment analysis (DEA), has attracted much attention in recent years. A pure serial three-stage (PSTS) process is a specific kind of network in which all the outputs of the first stage are used as the only inputs in the second stage and in addition, all the outputs of the second stage are applied as the only inputs in the third stage. In this paper, a new three-stage DEA model is developed using the concept of three-player Nash bargaining game for PSTS processes. In this model, all of the stages cooperate together to improve the overall efficiency of main decision-making unit (DMU). In contrast to the centralized DEA models, the proposed model of this study provides a unique and fair decomposition of the overall efficiency among all three stages and eliminates probable confusion of centralized models for decomposing the overall efficiency score. Some theoretical aspects of proposed model, including convexity and compactness of feasible region, are discussed. Since the proposed bargaining model is a nonlinear mathematical programming, a heuristic linearization approach is also provided. A numerical example and a real-life case study in supply chain are provided to check the efficacy and applicability of the proposed model. The results of proposed model on both numerical example and real case study are compared with those of existing centralized DEA models in the literature. The comparison reveals the efficacy and suitability of proposed model while the pitfalls of centralized DEA model are also resolved. A comprehensive sensitivity analysis is also conducted on the breakdown point associated with each stage.

Suggested Citation

  • Mohammad Amirkhan & Hosein Didehkhani & Kaveh Khalili-Damghani & Ashkan Hafezalkotob, 2018. "Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(05), pages 1429-1467, September.
  • Handle: RePEc:wsi:ijitdm:v:17:y:2018:i:05:n:s0219622018500426
    DOI: 10.1142/S0219622018500426
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    1. Wu, Jie & Zhu, Qingyuan & Ji, Xiang & Chu, Junfei & Liang, Liang, 2016. "Two-stage network processes with shared resources and resources recovered from undesirable outputs," European Journal of Operational Research, Elsevier, vol. 251(1), pages 182-197.
    2. Wei-Hsin Kong & Tsu-Tan Fu & Ming-Miin Yu, 2017. "Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1043-1068, July.
    3. Kao, Chiang, 2009. "Efficiency decomposition in network data envelopment analysis: A relational model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 949-962, February.
    4. Rolf Färe & Gerald Whittaker, 1995. "An Intermediate Input Model Of Dairy Production Using Complex Survey Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(2), pages 201-213, May.
    5. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Allocation of emission permits for China’s power plants: A systemic Pareto optimal method," Applied Energy, Elsevier, vol. 204(C), pages 607-619.
    6. Du, Juan & Liang, Liang & Chen, Yao & Cook, Wade D. & Zhu, Joe, 2011. "A bargaining game model for measuring performance of two-stage network structures," European Journal of Operational Research, Elsevier, vol. 210(2), pages 390-397, April.
    7. Kaveh Khalili-Damghani & Behnam Taghavifard, 2013. "Sensitivity and stability analysis in two-stage DEA models with fuzzy data," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 17(1), pages 1-37.
    8. Zhu, Joe, 2000. "Multi-factor performance measure model with an application to Fortune 500 companies," European Journal of Operational Research, Elsevier, vol. 123(1), pages 105-124, May.
    9. Chien Wang & Ram Gopal & Stanley Zionts, 1997. "Use of Data Envelopment Analysis in assessing Information Technology impact on firm performance," Annals of Operations Research, Springer, vol. 73(0), pages 191-213, October.
    10. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    11. Galagedera, Don U.A. & Roshdi, Israfil & Fukuyama, Hirofumi & Zhu, Joe, 2018. "A new network DEA model for mutual fund performance appraisal: An application to U.S. equity mutual funds," Omega, Elsevier, vol. 77(C), pages 168-179.
    12. Despotis, Dimitris K. & Sotiros, Dimitris & Koronakos, Gregory, 2016. "A network DEA approach for series multi-stage processes," Omega, Elsevier, vol. 61(C), pages 35-48.
    13. Li, Haitao & Chen, Chialin & Cook, Wade D. & Zhang, Jinlong & Zhu, Joe, 2018. "Two-stage network DEA: Who is the leader?," Omega, Elsevier, vol. 74(C), pages 15-19.
    14. Nash, John, 1950. "The Bargaining Problem," Econometrica, Econometric Society, vol. 18(2), pages 155-162, April.
    15. Gang Kou & Yanqun Lu & Yi Peng & Yong Shi, 2012. "Evaluation Of Classification Algorithms Using Mcdm And Rank Correlation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 197-225.
    16. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    17. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    18. Wenshuai Wu & Gang Kou, 2016. "A group consensus model for evaluating real estate investment alternatives," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-10, December.
    19. Thomas Sexton & Herbert Lewis, 2003. "Two-Stage DEA: An Application to Major League Baseball," Journal of Productivity Analysis, Springer, vol. 19(2), pages 227-249, April.
    20. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    21. 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.
    22. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures using a Dynamic Epsilon-Based Measure model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 121-134.
    23. Zhu, Qingyuan & Wu, Jie & Ji, Xiang & Li, Feng, 2018. "A simple MILP to determine closest targets in non-oriented DEA model satisfying strong monotonicity," Omega, Elsevier, vol. 79(C), pages 1-8.
    24. Kou, Gang & Ergu, Daji & Shang, Jennifer, 2014. "Enhancing data consistency in decision matrix: Adapting Hadamard model to mitigate judgment contradiction," European Journal of Operational Research, Elsevier, vol. 236(1), pages 261-271.
    25. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    26. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    27. Kou, Gang & Lin, Changsheng, 2014. "A cosine maximization method for the priority vector derivation in AHP," European Journal of Operational Research, Elsevier, vol. 235(1), pages 225-232.
    28. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
    29. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    30. 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.
    31. Kaveh Khalili-Damghani & Mohammad Taghavifard, 2012. "A three-stage fuzzy DEA approach to measure performance of a serial process including JIT practices, agility indices, and goals in supply chains," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 13(2), pages 147-188.
    32. K. Khalili-Damghani & M. Taghavifard & L. Olfat & K. Feizi, 2012. "Measuring agility performance in fresh food supply chains: an ordinal two-stage data envelopment analysis," International Journal of Business Performance and Supply Chain Modelling, Inderscience Enterprises Ltd, vol. 4(3/4), pages 206-232.
    33. 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.
    34. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures under CNG2020 strategy: An application of a Dynamic By-production model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 130-143.
    35. Shih-Liang Chao, 2017. "Integrating multi-stage data envelopment analysis and a fuzzy analytical hierarchical process to evaluate the efficiency of major global liner shipping companies," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(4), pages 496-511, May.
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    2. Wöhlert, Lydia, 2021. "Fairness bei der Performancebewertung in Supply Chains: Eine mehrstufige Literaturanalyse zum State of the Art," Ilmenauer Schriften zur Betriebswirtschaftslehre, Technische Universität Ilmenau, Institut für Betriebswirtschaftslehre, volume 1, number 12021.
    3. Jianhui Xie & Qiwei Xie & Yongjun Li & Liang Liang, 2021. "Solving data envelopment analysis models with sum-of-fractional objectives: a global optimal approach based on the multiparametric disaggregation technique," Annals of Operations Research, Springer, vol. 304(1), pages 453-480, September.

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