A Stochastic Data Envelopment Analysis Model Considering Variation in Input and Output Variables

Basma E. El-Demerdash^1, , Ihab A. El-Khodary¹ and Assem A. Tharwat²

¹Department of Operations Research and Decision Support, Faculty of Computers and Information, Cairo University, Egypt

²College of Business Administration, American University in the Emirates, United Arab Emirates

Cite this paper:
Basma E. El-Demerdash, Ihab A. El-Khodary and Assem A. Tharwat. A Stochastic Data Envelopment Analysis Model Considering Variation in Input and Output Variables. International Journal of Data Envelopment Analysis and *Operations Research*. 2016; 2(1):1-6. doi: 10.12691/ijdeaor-2-1-1

Abstract

Data envelopment analysis (DEA) is a nonparametric method in is used to measure the relative efficiency of comparable institutions and also used for benchmarking in operations management. There is a weakness in conventional DEA models that it does not allow uncertainty variations in input and output variables however, in many real life applications variables are usually vague. As a result, DEA efficiency measurement may be sensitive to such variations. Therefore, in this paper, input oriented model is one of the classic models in DEA going to develop in stochastic DEA that allow some of input and output variables have random in nature. Finally, an illustrative example has been presented.

Keywords:
stochastic data envelopment analysis stochastic variables stochastic efficiency chance constraint programming efficiency evaluation

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