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An aggressive game cross-efficiency evaluation in data envelopment analysis

Wenli Liu (), Ying-Ming Wang () and Shulong Lv ()
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Wenli Liu: Fuzhou University
Ying-Ming Wang: Fuzhou University
Shulong Lv: Fuzhou University

Annals of Operations Research, 2017, vol. 259, issue 1, No 11, 258 pages

Abstract: Abstract Cross-efficiency evaluation is an effective method for ranking decision making units (DMUs) in data envelopment analysis, which is performed with peer-evaluation and self-evaluation. From different points of view, various cross-efficiency evaluations have been proposed with different secondary goals. Yet they usually lead to different average cross-efficiencies and different rankings. In this paper, we develop a concept of the aggressive game cross-efficiency, and propose an aggressive secondary model to minimize the cross-efficiencies of other DMUs under the constraints that the aggressive game cross-efficiency of the evaluated DMU is guaranteed. To achieve the aggressive game cross-efficiency, we develop an iterative algorithm. Mathematically, it is proved that all conventional average cross-efficiencies are sure to converge to the same aggressive game cross-efficiency by the iterative algorithm. Finally, numerical examples are presented to show the effectiveness of our approach in evaluating and ranking DMUs.

Keywords: Data envelopment analysis; Cross-efficiency evaluation; Ranking DMUs (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10479-017-2524-1

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