A Unified Mathematical Model for Stochastic Data Envelopment Analysis

Basma E. El-Demerdash, Assem A. Tharwat and Ihab A. A. El-Khodary
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Basma E. El-Demerdash: Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt
Assem A. Tharwat: College of Business Administration, American University in the Emirates, UAE
Ihab A. A. El-Khodary: Faculty of Computers and Artificial Intelligence, Cairo University, Egypt

International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 2021, vol. 12, issue 1, 127-141

Abstract: Efficiency measurement is one aspect of organizational performance that managers are usually interested in determining. Data envelopment analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about the efficiency and performance of organizations and all sorts of functionally similar, relatively autonomous operating units. DEA models are either with a constant rate of return (CRS) or variable return to scale (VRS). Furthermore, the models could be input-oriented or output-oriented. In many real-life applications, observations are usually random in nature; as a result, DEA efficiency measurement may be sensitive to such variations. The purpose of this study was to develop a unified stochastic DEA model that handles different natures of variables independently (random and deterministic) and can be adapted to model both input/output-oriented problems, whether it is CRS or VRS. The chance-constrained approach was adopted to handle the stochastic variables that exist in the model. The developed model is implemented through an illustrative example.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jssmet:v:12:y:2021:i:1:p:127-141

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