Regret cross-efficiency evaluation using attitudinal entropy approach

Bibliographic Data

ID22232821
AuthorsHao Pan (0000-0003-4561-3911, Chinese Academy of Sciences), Guo-liang Yang (0000-0001-9781-4446, Chinese Academy of Sciences), Xiaolei Chen (0000-0003-1908-8789, Chinese Academy of Sciences), Xiao-Lei Chen (0000-0002-3832-1219), Yuan-yu Lou (Chinese Academy of Sciences), Teng Wang (0000-0003-2545-8619, Chinese Academy of Sciences), Zhong-cheng Guan (Chinese Academy of Sciences, corresponding author)
Year2024
Volume11
Issue1
Publication date2024-09-30
Open AccessYes
TypeARTICLE
VenueHumanities and Social Sciences Communications (JOURNAL)
Journal identifiersISSN: 2662-9992 • E-ISSN: 2662-9992
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1057/s41599-024-03817-5
OpenAlexW4402975048
LanguageEN
References cited75

Data envelopment analysis (DEA) is a popular nonparametric tool for measuring the performance of decision making unit (DMU). Cross-efficiency evaluation is an efficient means to rank DMUs, which compensates for efficiency overestimation and incomplete ranking of conventional DEA models. With respect to incomplete rational cross-efficiency evaluation, the common methods construct models with two extreme efficiencies as reference, such as efficiency values of the aggressive and benevolent models. In addition, they only explore the irrational preferences of decision maker (DM) at a certain stage in the evaluation process. They fail to investigate the cross-efficiency evaluation synthetically under incomplete rationality and characterize the complexity of the individuals’ decision making. To fill this gap, a new method must be proposed. This paper proposes a new cross-efficiency termed regret cross-efficiency model using attitudinal entropy approach (RACE), which constructs a secondary goal model from a comprehensive perspective under the framework of regret theory, and introduces attitudinal entropy to aggregate the cross-efficiencies. Besides, this paper presents some empirical examples to illustrate the validity and robustness of the RACE method

Physics · Regret · Statistics · Thermodynamics · Computer Science · Economic and Environmental Valuation · Efficiency Analysis Using DEA · Forecasting Techniques and Applications · Mathematics · Psychology · Social Psychology

Tools

Open DOIOpen Access