A new probabilistic approach for ranking grouped DMUs

Data Envelopment Analysis (DEA) is a widely used non-parametric method for ranking of Decision-Making Units (DMU). Despite the fact that DEA method does not require numerous prerequisites, but the necessity of the DMUs to be homogeneous is one of the most important rules in applying this technique. On the other hand, in real world problems, due to the nature of DMUs, the need for ranking the grouped data has gain significant importance. Credit rating of the financial facilities applicants is considered by the banks and financial institutes as one of the most important management issues and significant budget is allocated to develop and implement an effective rating system. Since the applicant organizations operate in different businesses and industries, and simultaneous rating of these companies using the DEA method leads to the violation of the homogeneity rule, thus, application of this powerful tool is restricted. The purpose of this paper is to resolve this key weakness in such a way that makes it possible to simultaneously consider the heterogeneous companies (DMUs). The results of the proposed method have been shown for a well-known and large bank in Iran which implies an enhanced capability for rating the decision-making units.

Keywords:

Data envelopment analysis , development , Grouped data , Credit rating