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Title

RANKING EFFICIENT DMUS WITH STOCHASTIC DATA BY CONSIDERING INEFFICIENT FRONTIER

Pages

 Start Page 219 | End Page 226

Abstract

DATA ENVELOPMENT ANALYSIS (DEA) models which evaluate the efficiency of a set of decision making units (DMUs) are unable to discriminate between efficient DMUs. The problem of discriminating between these efficient DMUs is an interesting subject. A large number of methods for fully RANKING both efficient and inefficient DMUs have been proposed.Through real world applications, analysis may encounter data that are not deterministic or on have a stochastic essence but whose distribution can be defined by collecting data in successive periods and by statistical methods. In this paper, a method for RANKING stochastic efficient DMUs is suggested which is based on the full inefficient frontier method. Using a numerical example, we will demonstrate how to use the result.

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