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Two-stage cross-efficiency evaluation based on prospect theory

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  • Xing Shao
  • Meiqiang Wang

Abstract

Cross-efficiency evaluation in data envelopment analysis (DEA) is effective for evaluating the efficiency of decision-making units (DMUs). The use of cross-efficiency evaluation methods based on prospect theory has recently increased. However, the internal structure of DMUs is often ignored in efficiency evaluation; further, a fixed status quo is often selected as the reference point to calculate relative gains and losses, which is not ideal in the context of prospect theory. To address these issues, we investigate the basic two-stage cross-efficiency evaluation in DEA based on prospect theory. An optimism coefficient is introduced to formulate parameterised dynamic reference points, and a target identification model is developed to obtain target efficiency values that are attainable for all DMUs. Based on the prospect value and target efficiency values, we propose multiple novel aggressive, benevolent, and neutral two-stage cross-efficiency evaluation models. The models proposed herein can be applied to various decision environments and arbitrarily extended to other network system structures. A case study in sustainable supplier selection is performed to demonstrate the effectiveness of the proposed models for DMU ranking. The sensitivity analysis results show that the psychological characteristics of the decision maker under risk affect the evaluation results.

Suggested Citation

  • Xing Shao & Meiqiang Wang, 2022. "Two-stage cross-efficiency evaluation based on prospect theory," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(7), pages 1620-1632, July.
  • Handle: RePEc:taf:tjorxx:v:73:y:2022:i:7:p:1620-1632
    DOI: 10.1080/01605682.2021.1918587
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    Cited by:

    1. Sweksha Srivastava & Abha Aggarwal & Pooja Bansal, 2024. "Efficiency Evaluation of Assets and Optimal Portfolio Generation by Cross Efficiency and Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 129-158, January.
    2. Cui, Yuan & Pan, Hao & Huang, Yi-Di & Yang, Guo-liang, 2024. "How can sociological theories provide legitimacy to eco-efficiency evaluations? Embark on a journey toward understanding," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).

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