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An Uncertain DEA Model for Scale Efficiency Evaluation
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DOI：10.1109/TFUZZ.2018.2883546.png)
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Abstract
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Data envelopment analysis (DEA) is widely used to estimate efficiency, particularly with respect to firm performance in economics. When the observed data are imprecise, as in the cases involving carbon emissions or social benefits, an uncertain DEA model can provide a reasonable solution. However, current uncertain DEA models only consider technical efficiency and not scale efficiency. This leads to information scarcity during decision making processes. This paper proposes an uncertain DEA model for scale efficiency evaluations using imprecise inputs and outputs. Additionally, we provide a sensitivity and stability analysis of the uncertain DEA model for scale efficiency, and document a numerical example of the uncertain DEA model for scale efficiency.
Keywords:
Uncertain calculus
uncertain integral
uncertain process
uncertainty theory
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