research-article

DEA cross-efficiency models with prospect theory and distance entropy: : An empirical study on high-tech industries

Authors:

Zhiwei WangAuthors Info & Claims

Volume 244, Issue C

https://doi.org/10.1016/j.eswa.2023.122941

Published: 02 July 2024 Publication History

Highlights

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An evaluation model is proposed by considering risk attitudes and aggregation method.

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Our distance entropy function reduces the inconsistent degree of evaluation results.

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Empirical example is performed to validate the applicability of the proposed model.

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Sensitivity analysis is conducted to test the effect of parameter changes on results.

Abstract

Cross-efficiency evaluation with the data envelopment analysis (DEA) model is an effective way to assess performance and provide a complete ranking of decision-making units. However, it is generally assumed that decision makers are perfectly rational in the cross-efficiency model, which fails to consider the subjective preferences of decision-makers. Moreover, the arithmetic average method is usually adopted to aggregate efficiency scores in traditional cross-efficiency methods, which underestimates the importance of self-evaluation. To address these issues, we extend cross-efficiency with the DEA model by incorporating prospect theory and the distance entropy function. First, we calculate the prospect values of decision-making units to describe the non-rational subjective preferences under the risk of decision-makers. Second, based on prospect cross-efficiency, a new distance entropy function is developed to aggregate the ultimate prospect cross-efficiency values. More specifically, some traditional cross-efficiency evaluation models can be considered special cases of prospect cross-efficiency models with appropriate adjustments to the parameters. Finally, an empirical example is used to evaluate the prospect cross-efficiency results with the high-tech industries of 29 provinces in China to illustrate the applicability and effectiveness of the proposed model in ranking observations.

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Published In

cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 244, Issue C

Jun 2024

1583 pages

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Elsevier Ltd.

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Pergamon Press, Inc.

United States

Publication History

Published: 02 July 2024

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