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DEA and Cooperative Game Theory

In: Handbook of Operations Analytics Using Data Envelopment Analysis

Author

Listed:
  • Sebastián Lozano

    (Sevilla University)

  • Miguel Ángel Hinojosa

    (Pablo de Olavide University)

  • Amparo María Mármol

    (Sevilla University)

  • Diego Vicente Borrero

    (Pablo de Olavide University)

Abstract

In this chapter the possibilities of hybridizing data envelopment analysis (DEA) and cooperative games are studied. Specifically, bargaining games and transferable utility games (TU games) are considered. There are already a number of different DEA approaches that are based on these types of cooperative games but, more importantly, there is the potential for further cooperation from both techniques.

Suggested Citation

  • Sebastián Lozano & Miguel Ángel Hinojosa & Amparo María Mármol & Diego Vicente Borrero, 2016. "DEA and Cooperative Game Theory," International Series in Operations Research & Management Science, in: Shiuh-Nan Hwang & Hsuan-Shih Lee & Joe Zhu (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 0, pages 215-239, Springer.
    • Handle: RePEc:spr:isochp:978-1-4899-7705-2_9
    DOI: 10.1007/978-1-4899-7705-2_9
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    Citations

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    Cited by:

    1. Hashem Omrani & Mohaddeseh Amini & Mahdieh Babaei & Khatereh Shafaat, 2020. "Use Shapley value for increasing power distinguish of data envelopment analysis model: An application for estimating environmental efficiency of industrial producers in Iran," Energy & Environment, , vol. 31(4), pages 656-675, June.
    2. Valentin Zelenyuk, 2018. "Some Mathematical and Historical Clarifications on Aggregation in Efficiency and Productivity Analysis and Connection to Economic Theory," CEPA Working Papers Series WP032018, School of Economics, University of Queensland, Australia.
    3. Chang, Tsung-Sheng & Lin, Ji-Gang & Ouenniche, Jamal, 2023. "DEA-based Nash bargaining approach to merger target selection," European Journal of Operational Research, Elsevier, vol. 305(2), pages 930-945.
    4. I. Contreras & S. Lozano & M. A. Hinojosa, 2021. "A bargaining approach to determine common weights in DEA," Operational Research, Springer, vol. 21(3), pages 2181-2201, September.
    5. Lozano, S. & Hinojosa, M.A. & Mármol, A.M., 2019. "Extending the bargaining approach to DEA target setting," Omega, Elsevier, vol. 85(C), pages 94-102.
    6. 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.

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