期刊
ANNALS OF OPERATIONS RESEARCH
卷 197, 期 1, 页码 191-200出版社
SPRINGER
DOI: 10.1007/s10479-010-0817-8
关键词
MCDM; DEA; Self-evaluation; Cross-evaluation; Nash equilibrium
资金
- National Natural Science Funds of China for Innovative Research Groups [70821001]
- National Natural Science Funds of China [70901069]
- Special Fund for the Gainers of Excellent Ph.D.'s Dissertations and Dean's Scholarships of Chinese Academy of Sciences
- Research Fund for the Doctoral Program of Higher Education of China for New Teachers [20093402120013]
- Research Fund for the Excellent Youth Scholars of Higher School of Anhui Province of China [2010SQRW001ZD]
- Social Science Research Fund for Higher School of Anhui Province of China [2010SK004]
- Philosophy and Social Science Research Fund of Anhui Province of China [AHSKF09-10D116]
The application of Data Envelopment Analysis (DEA) as an alternative multiple criteria decision making (MCDM) tool has been gaining more attentions in the literatures. Doyle (Organ. Behav. Hum. Decis. Process. 62(1):87-100, 1995) presents a method of multi-attribute choice based on an application of DEA. In the first part of his method, the straightforward DEA is considered as an idealized process of self-evaluation in which each alternative weighs the attributes in order to maximize its own score (or desirability) relative to the other alternatives. Then, in the second step, each alternative applies its own DEA-derived best weights to each of the other alternatives (i.e., cross-evaluation), then the average of the cross-evaluations that get placed on an alternative is taken as an index of its overall score. In some cases of multiple criteria decision making, direct or indirect competitions exist among the alternatives, while the factor of competition is usually ignored in most of MCDM settings. This paper proposes an approach to evaluate and rank alternatives in MCDM via an extension of DEA method, namely DEA game cross-efficiency model in Liang, Wu, Cook and Zhu (Oper. Res. 56(5):1278-1288, 2008b), in which each alternative is viewed as a player who seeks to maximize its own score (or desirability), under the condition that the cross-evaluation scores of each of other alternatives does not deteriorate. The game cross-evaluation score is obtained when the alternative's own maximized scores are averaged. The obtained game cross-evaluation scores are unique and constitute a Nash equilibrium point. Therefore, the results and rankings based upon game cross-evaluation score analysis are more reliable and will benefit the decision makers.
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