DEA models for minimizing weight disparity in cross-efficiency evaluation

被引：49

作者：

Wang, Y-M ^{[1
]}

Chin, K-S ^{[2
]}

Wang, S. ^{[3
]}

机构：

[1] Fuzhou Univ, Inst Decis Sci, Sch Publ Adm, Fuzhou 350108, Peoples R China

[2] City Univ Hong Kong, Kowloon Tong, Hong Kong, Peoples R China

[3] Univ Manchester, Manchester, Lancs, England

来源：

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY | 2012年 / 63卷 / 08期

基金：

中国国家自然科学基金;

关键词：

data envelopment analysis; cross-efficiency evaluation; virtual disparity; DEA ranking; DATA ENVELOPMENT ANALYSIS; DISCRIMINATION; SELECTION;

D O I：

10.1057/jors.2011.116

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

Cross-efficiency evaluation is a commonly used approach for ranking decision-making units (DMUs) in data envelopment analysis (DEA). The weights used in the cross-efficiency evaluation may sometimes differ significantly among the inputs and outputs. This paper proposes some alternative DEA models to minimize the virtual disparity in the cross-efficiency evaluation. The proposed DEA models determine the input and output weights of each DMU in a neutral way without being aggressive or benevolent to the other DMUs. Numerical examples are tested to show the validity and effectiveness of the proposed DEA models and illustrate their significant role in reducing the number of zero weights. Journal of the Operational Research Society (2012) 63, 1079-1088. doi: 10.1057/jors.2011.116 Published online 9 November 2011

引用

页码：1079 / 1088

页数：10

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