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An epsilon-based data envelopment analysis approach for solving performance measurement problems with interval and ordinal dual-role factors

Author

Listed:
  • Bohlool Ebrahimi

    (FernUniversität in Hagen)

  • Madjid Tavana

    (La Salle University
    University of Paderborn)

  • Andreas Kleine

    (FernUniversität in Hagen)

  • Andreas Dellnitz

    (Leibniz-Fachhochschule School of Business)

Abstract

Data envelopment analysis (DEA) is a linear programming method for measuring the performance and efficiency of units called decision-making units (DMUs). In many real-world performance measurement problems, the input and output data are not precisely known. Furthermore, the data may include dual-role factors that can be considered an input and output factor simultaneously. We propose a novel DEA model in the presence of imprecise data and imprecise dual-role factors by developing a new pair of mixed binary linear epsilon-based DEA models. The proposed models estimate the lower and upper bound efficiency scores in the presence of interval input, output, and dual-role factors by considering a fixed and unified production frontier for all DMUs. We then extend our models by including the weak ordinal dual-role factors. In contrast to the existing methods that exclude the dual-role factors, we include the dual-role factors and find a strictly positive value for the lower bound of the weights of inputs, outputs, and dual-role factors. We present a case study to demonstrate the applicability and exhibit the superiority of our approach over the existing methods.

Suggested Citation

  • Bohlool Ebrahimi & Madjid Tavana & Andreas Kleine & Andreas Dellnitz, 2021. "An epsilon-based data envelopment analysis approach for solving performance measurement problems with interval and ordinal dual-role factors," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 1103-1124, December.
  • Handle: RePEc:spr:orspec:v:43:y:2021:i:4:d:10.1007_s00291-021-00649-6
    DOI: 10.1007/s00291-021-00649-6
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    2. Papaioannou, Grammatoula & Podinovski, Victor V., 2024. "A single-stage optimization procedure for data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1119-1128.

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