Integrating fuzzy goal programming and data envelopment analysis to incorporate preferred decision-maker targets in efficiency measurement

Debora Di Caprio (), Ali Ebrahimnejad (), Mojtaba Ghiyasi () and Francisco J. Santos-Arteaga ()
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Debora Di Caprio: University of Trento
Ali Ebrahimnejad: Islamic Azad University
Mojtaba Ghiyasi: Shahrood University of Technology
Francisco J. Santos-Arteaga: Free University of Bolzano

Decisions in Economics and Finance, 2020, vol. 43, issue 2, No 14, 673-690

Abstract: Abstract Data envelopment analysis (DEA) is a nonparametric frontier assessment method used to evaluate the relative efficiency of similar decision-making units (DMUs). This method provides benchmarking information regarding the removal of inefficiency. In conventional DEA models, the view of the decision maker (DM) is ignored and the performance of each DMU is solely determined by the observations retrieved. The current paper exploits the structural similarity existing between DEA and multiple objective programming to define a model that incorporates the preferences of DMs in the evaluation process of DMUs. Given the potential unfeasibility of the input and output targets selected by the DM, the model defines an interactive procedure that considers minimum and maximum acceptable objective levels. Given the feasible levels located closer to the targets selected by the DM, a program improving upon the feasible allocations is designed so that the suggested benchmark approximates the requirements fixed by the DM as much as possible. A real-life case study is included to illustrate the efficacy and applicability of the proposed hybrid procedure.

Keywords: Data envelopment analysis; Fuzzy goal programming; Multiple objective linear programming; Subjective preferences; Target setting; Efficiency (search for similar items in EconPapers)
JEL-codes: C61 D81 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10203-020-00297-5

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