Preserving cost and revenue efficiency through inverse data envelopment analysis models

Abstract

Abstract Data envelopment analysis (DEA) models are applied in commercial firms to evaluate their technical, cost and revenue efficiencies. The new models introduced here are based on inverse DEA for preserving cost/revenue efficiency. The commercial institution management seeks to minimize the input costs for a given level of outputs or maximize the revenue of outputs for a specified level of inputs. It is important to preserve cost/revenue efficiency when data are changed. In this method, we determine the cost efficiency score of decision-making units (DMUs). Then, for each one of them, the outputs are increased and the values of the required increment of inputs are obtained, while the cost efficiency of the unit under evaluation remains unchanged. For practical application, one of these introduced models is applied to a real data set of European and American banks for cost efficiency preservation.