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Abstract
This paper proposes a new cross-efficiency model called Regret Cross-Efficiency Model using Attitudinal Entropy Approach (RACE) to address limitations of existing Data Envelopment Analysis (DEA) methods. RACE incorporates regret theory and attitudinal entropy to synthesize cross-efficiencies under incomplete rationality, providing a more comprehensive and robust ranking of Decision Making Units (DMUs). Empirical examples demonstrate the validity and robustness of the RACE method.
Publisher
Humanities and Social Sciences Communications
Published On
Sep 30, 2024
Authors
Hao Pan, Guo-liang Yang, Xiao-lei Chen, Yuan-yu Lou, Teng Wang, Zhong-cheng Guan
Tags
Data Envelopment Analysis
cross-efficiency
regret theory
attitudinal entropy
Decision Making Units
model synthesis
empirical examples
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