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DEA production games

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  • Lozano, S.

Abstract

In this paper, linear production games are extended so that instead of assuming a linear production technology with fixed technological coefficients, the more general, non-parametric, DEA production technology is considered. Different organizations are assumed to possess their own technology and the cooperative game arises from the possibility of pooling their available inputs, collectively processing them and sharing the revenues. Two possibilities are considered: using a joint production technology that results from merging their respective technologies or each cooperating organization keeping its own technology. This gives rise to two different DEA production games, both of which are totally balanced and have a non-empty core. A simple way of computing a stable solution, using the optimal dual solution for the grand coalition, is presented. The full cooperation scenario clearly produces more benefits for the organizations involved although the implied technology sharing is not always possible. Examples of applications of the proposed approach are given.

Suggested Citation

  • Lozano, S., 2013. "DEA production games," European Journal of Operational Research, Elsevier, vol. 231(2), pages 405-413.
  • Handle: RePEc:eee:ejores:v:231:y:2013:i:2:p:405-413
    DOI: 10.1016/j.ejor.2013.06.004
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    2. Phuoc Hoang Le & Tri-Dung Nguyen & Tolga Bektaş, 2020. "Efficient computation of the Shapley value for large-scale linear production games," Annals of Operations Research, Springer, vol. 287(2), pages 761-781, April.
    3. Briec, Walter & Mussard, Stéphane, 2020. "Improvement of technical efficiency of firm groups," European Journal of Operational Research, Elsevier, vol. 283(3), pages 991-1001.
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    5. Lee, Chia-Yen, 2018. "Mixed-strategy Nash equilibrium in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1013-1024.
    6. Walter Briec & Marc Dubois & Stéphane Mussard, 2021. "Technical efficiency in firm games with constant returns to scale and $$\alpha $$ α -returns to scale," Annals of Operations Research, Springer, vol. 304(1), pages 35-62, September.
    7. Zhang, Ganggang & Wu, Jie & Zhu, Qingyuan, 2020. "Performance evaluation and enrollment quota allocation for higher education institutions in China," Evaluation and Program Planning, Elsevier, vol. 81(C).
    8. Walter Briec & Marc Dubois & Stéphane Mussard, 2019. "Technical Efficiency in Firm Games with Constant Returns to Scale and α-Returns to Scale," Working Papers hal-02344310, HAL.
    9. Aparicio, Juan & Pastor, Jesús T. & Vidal, Fernando & Zofío, José L., 2017. "Evaluating productive performance: A new approach based on the product-mix problem consistent with Data Envelopment Analysis," Omega, Elsevier, vol. 67(C), pages 134-144.
    10. Borrero, D.V. & Hinojosa, M.A. & Mármol, A.M., 2016. "DEA production games and Owen allocations," European Journal of Operational Research, Elsevier, vol. 252(3), pages 921-930.
    11. Yu, Anyu & You, Jianxin & Rudkin, Simon & Zhang, Hao, 2019. "Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis," Applied Energy, Elsevier, vol. 233, pages 232-243.
    12. Jie Wu & Qingyuan Zhu & Junfei Chu & Qingxian An & Liang Liang, 2016. "A DEA-based approach for allocation of emission reduction tasks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(18), pages 5618-5633, September.
    13. An, Qingxian & Tao, Xiangyang & Xiong, Beibei, 2021. "Benchmarking with data envelopment analysis: An agency perspective," Omega, Elsevier, vol. 101(C).
    14. Lozano, S. & Hinojosa, M.A. & Mármol, A.M., 2015. "Set-valued DEA production games," Omega, Elsevier, vol. 52(C), pages 92-100.
    15. An, Qingxian & Wen, Yao & Ding, Tao & Li, Yongli, 2019. "Resource sharing and payoff allocation in a three-stage system: Integrating network DEA with the Shapley value method," Omega, Elsevier, vol. 85(C), pages 16-25.
    16. Li, Yongjun & Xie, Jianhui & Wang, Meiqiang & Liang, Liang, 2016. "Super efficiency evaluation using a common platform on a cooperative game," European Journal of Operational Research, Elsevier, vol. 255(3), pages 884-892.
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    18. M. A. Hinojosa & S. Lozano & A. M. Mármol, 2018. "DEA production games with fuzzy output prices," Fuzzy Optimization and Decision Making, Springer, vol. 17(4), pages 401-419, December.

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