The family of optimization models of Data Envelopment Analysis (DEA) has been shown to be very useful performance analytics tools that support benchmarking systems in measuring, comparing, and enhancing various notations of efficiency. It has also been extensively used as an advanced analytical...

Benchmarking, in many cases by means of Data Envelopment Analysis, is one of the main strategies of regulatory agencies to control the costs of monopolistic companies. In such cases, the determination of inputs and outputs as performance criteria is often an issue. Against this background, we...

After 40 years of research with thousands of application-oriented scientific papers, empirical evidence that data envelopment analysis (DEA) has really improved the practice of performance measurement and benchmarking in real-life non-production contexts is rare. The main reason for this deficit...

After 40 years of research with thousands of application-oriented scientific papers, empirical evidence that data envelopment analysis (DEA) has really improved the practice of performance measurement and benchmarking in real-life non-production contexts is rare. The main reason for this deficit...

Purpose The determination of input and output factors is a well-known source of pitfalls when applying data envelopment analysis (DEA). The purpose of this paper is to contribute to overcome the respective problems of input/output factor determination related to factor selection, dual-role...