A new approach for ranking efficient DMUs in Data Envelopment Analysis by using cooperativegame theory
Ranking of decision making units (DMU) is an important issue in data envelopment analysis (DEA). When efficient DMUs have the same efficiency scores, traditional DEA models usually fail to rank efficient DMUs. In recent years, cooperative game theory has been used to compare and improve the discrimination power of efficient DMUs. In this research, a new method of cooperative game is proposed. The idea of this method is that first, by removing a certain subset of efficientDMUs from the set of units, the efficiency of all units is calculated, and then, using the Shepley value in cooperative game theory, the efficient units are ranked. A numerical example is presented to show the performance of the proposed method and its comparison with recent ranking methods. In the empirical study, the ranking of efficient DMUs is useful and reasonable.
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