Abstract
Abstract
The aim of this paper is to evaluate the performance of decision making units (DMUs) with fuzzy data by using the common set of weights (CSW) method in data envelopment analysis (DEA). The CSW, which provides a more accurate assessment and less computation than DEA, has interested researchers. In contrast, classic DEA requires that all data values are known exactly, and imprecise DEA has vague data (fuzzy, stochastic, interval, etc.). The credibility measure, which has its advantages such as support for the imprecise nature of the data, self-duality, and low computation related to other fuzzy methods, is applied to solve the proposed fuzzy CSW model. In particular, when data are triangular fuzzy numbers, the fuzzy model is transformed into a deterministic linear model. The optimal solution to this problem is the CSW, and the fuzzy efficiency of DMUs is then acquired. A fuzzy ranking approach is extended to compare and rank the DMUs. A numerical example is then presented to compare the proposed method with the method in the literature. The proposed method is also applied to evaluate the performances of chief executive officers of U.S. public banks and thrifts.
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