RANKING THE EFFICIENCY PERFORMANCE WITHIN A SET OF DECISION MAKING UNITS BY DATA ENVELOPMENT ANALYSIS

Abstract

In contrast to parametric approaches which try to optimize a single regression function through the observed data set, DEA optimizes on each individual observation with a objective of calculating a discrete piece-wise linear frontier. In the so-called preliminary DEA efficiency evaluation, whether or not a DMU is efficient is solely determined by the solution of the linear programming problem constructed for this particular DMU. In our proposed ranking method, we assess the efficiency performance of a particular DMU based not only on its efficiency score when the DMU is standing out in the objective function of the linear problem but also its efficiency ratios under the optimal solutions of other n-1 linear programming problems. This constitutes the overall efficiency performance of a DMU. A ranking procedure is developed to rank the n DMUs in terms of the overall efficiency performance.