A Review of Ranking Models in Data Envelopment Analysis

In the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existingmethods can be viewed fromdifferent aspects, it is possible that somewhat these groups have an overlappingwith the others. The first group conducts the evaluation by a cross-efficiency matrix where the units are selfand peer-evaluated. In the second one, the ranking units are based on the optimal weights obtained from multiplier model of DEA technique. In the third group, superefficiency methods are dealt with which are based on the idea of excluding the unit under evaluation and analyzing the changes of frontier.The fourth group involvesmethods based on benchmarking, which adopts the idea of being a useful target for the inefficient units.The fourth group uses themultivariate statistical techniques, usually applied after conducting the DEA classification.The fifth research area ranks inefficient units through proportional measures of inefficiency. The sixth approach involves multiple-criteria decision methodologies with the DEA technique. In the last group, some different methods of ranking units are mentioned.