Inverse DEA based on cost and revenue efficiency in the absence of price information

Abstract

Inverse data envelopment analysis (DEA) models are supplementary techniques for performance evaluation and further performance analysis. Cost and revenue efficiency give decision makers valuable information, yet in many real-world issues, we only have cost information rather than full price information. The literature on the inverse DEA suffers from a theoretical gap in dealing with the cost and revenue efficiency when there is no information about the prices. In this research, new inverse DEA models based on revenue and cost efficiency without pricing information are developed. The proposed models are applied to a real-world problem and they are used for the performance assessment and cost analysis of 154 public hospitals.