The New Method for Ranking Grouped Credit Customer Based on DEA Method

Data envelopment analysis (dea) is a widely used non-parametric method for ranking by decision-making units (dmu). despite the fact that dea method does not require numerous preconditions, the necessity of the dmus to be homogeneous is one of the most important rules in applying this technique. moreover, in real world problems, due to the nature of dmus, the need for ranking the grouped data has gained significant importance. credit rating of the financial facility applicants is considered by the banks and financial institutions as one of the most important management issues and significant budget is allocated to develop and imply an effective rating system. since the applicant organizations operate in different businesses andindustries, and simultaneous rating of these companies using the dea method leads to violation of 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. the results of the proposed method have shown an enhanced capability for rating the decision-making units.