Abstract

This paper deals with inverse DEA from both theoretical and applied viewpoints. First, some methodological approaches and theoretical results are outlined; and then an application of DEA with real-world data (for assessing educational departments in a university) is addressed. Afterwards, possible extensions and applications of the existing approaches in the presence of fuzzy data are developed. The final theoretical part of the paper contains a main theorem which provides a sufficient condition for efficiency maintaining in the presence of fuzzy data. To do this, we have used some notions/results from multi-objective decision-making theory.

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