CI-DEA: A Way to Improve the Discriminatory Power of DEA—Using the Example of the Efficiency Assessment of the Digitalization in the Life of the Generation 50+

Abstract

Data envelopment analysis (DEA) is a popular and universal method for examining the efficiency with which decision-making units (DMUs) transform multiple inputs into multiple outputs. However, DEA has its limitations, one of them being its decreasing discriminatory power when the number of analyzed DMUs is insufficient or when there are too many variables (inputs/outputs) describing them. When resigning from any of the variables is impossible or undesired, or when the number of units cannot be increased, CI-DEA, a method proposed in this article, proves to be helpful. It consists of replacing the inputs and/or outputs of the studied DMUs with a smaller number of composite indicators. The aggregation of variables is not based on subjective decisions of the analyst, but depends solely on correlations that exist among variables. The construction of the CI-DEA model makes the interpretation of the results unambiguous and easy. The reliability of the results obtained with CI-DEA have been confirmed by extensive simulation studies performed under conditions of predetermined real-efficiency of DMUs. The usefulness of CI-DEA on real data has been demonstrated on the example of the efficiency assessment of the digitalization in the life of the Generation 50+ in 32 European countries.

Optimizing Cross-Dock Terminal Location Selection: A Multi-Step Approach Based on CI-DEA–IDOCRIW–MABAC for Enhanced Supply Chain Efficiency—A Case Study

“…CI-DEA was proposed in [7] to reduce the number of observed input/output indicators, which is especially significant in a situation when there is a large number of inputs/outputs and a smaller number of DMUs. This reduction is achieved by taking into account the correlation that exists among indicators.…”

“…This reduction is achieved by taking into account the correlation that exists among indicators. The input-oriented CI-DEA model can be defined using Equations ( 1)-(4) as follows [7]. max…”

“…Step 4. Determining every alternative's uncertainty or degree of deviation by applying Equation (7).…”

“…The reason for implementing this method in the paper is reflected by the fact that the implementation of the CI-DEA model results in an unambiguous and easy interpretation of the obtained results. Also, another reason for its implementation is the fact that, based on the simulation results [7], it was determined that this method assessed the DMU efficiency better than the standard DEA, and the results seemed to be more reliable. The IDOCRIW method was applied since the goal of this paper was to determine criteria weights objectively.…”

The determinants of municipal solid waste management efficiency in EU countries

“…The basic DEA model is the input-oriented, radial DEA-CCR model proposed by Charnes et al (1978), which has undergone numerous modifications (Łozowicka & Lach, 2022). The DEA-CCR model does not make any assumptions about the weights (except being non-negative) in the linear combination.…”