Developing a stochastic DEA model for considering non-discretionary inputs

Sina Saeid Taleshi and Reza Kiani Mavi

International Journal of Decision Sciences, Risk and Management, 2011, vol. 3, issue 1/2, 70-80

Abstract: Formal statistical inference on efficiency measures is not possible. Stochastic DEA can deal effectively with noise in the non-parametric measurement of efficiency. In any realistic situation, however, there may be exogenously fixed or non-discretionary inputs or outputs that are beyond the control of a DMU's management. The objective of this paper is to present a methodology for treating non-discretionary variables in stochastic formulation. Based on the proposed method, an effective performance measurement tool is developed to provide a basis for understanding the efficiency in stochastic situations. A numerical example is presented. In short, the main contributions of this work are as follows: an stochastic DEA model is extended to encompass non-discretionary variables and stochastic data, thus a typical model for efficiency analysis is developed as an effective performance measurement tool that is the contribution of the paper.

Keywords: data envelopment analysis; Malmquist DEA; stochastic DEA; non-discretionary inputs; statistical inference; non-parametric measurements; exogenously fixed inputs; exogenously fixed outputs; non-discretionary outputs; decision making units; DMUs; non-discretionary variables; stochastic formulations; performance measurement; stochastic data; efficiency analysis; decision sciences. (search for similar items in EconPapers)
Date: 2011
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