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Information Journal Paper

Title

Uncertain BCC Data Envelopment Analysis Model with Belief Degree: A case study in Iranian Banks

Pages

  239-249

Abstract

Data envelopment analysis (DEA) is recognized as a robust analytical tool extensively utilized in measuring the relative e ciency of a group of Decision Making Units (DMUs) with multiple inputs and outputs. The DEA models require inputs and outputs equipped with precise information. However in real-world situations inputs and outputs may be unstable and complicated thus unable to be accurately measured. This problem resulted in the investigation of uncertain DEA models. The BCC model is studied in this paper in an uncertain environment where uncertain inputs and outputs were Belief degree-based Uncertainty useful for the cases for which no historical information of an uncertain event is available. As the solution method the uncertain BCC model was converted to a crisp form using two approaches of expected value method (EV) and expected value and chance-constrained method (EVCC) separately. Finally, an applied example regarding the Iranian Banking system is presented to document the proposed models.

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  • Cite

    APA: Copy

    JAMSHIDI, M., SANEI, M., MAHMOODIRAD, A., TOHIDI, G., & HOSEINZADEH LOTFI, F.. (2021). Uncertain BCC Data Envelopment Analysis Model with Belief Degree: A case study in Iranian Banks. INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS, 13(3 ), 239-249. SID. https://sid.ir/paper/964303/en

    Vancouver: Copy

    JAMSHIDI M., SANEI M., MAHMOODIRAD A., TOHIDI G., HOSEINZADEH LOTFI F.. Uncertain BCC Data Envelopment Analysis Model with Belief Degree: A case study in Iranian Banks. INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS[Internet]. 2021;13(3 ):239-249. Available from: https://sid.ir/paper/964303/en

    IEEE: Copy

    M. JAMSHIDI, M. SANEI, A. MAHMOODIRAD, G. TOHIDI, and F. HOSEINZADEH LOTFI, “Uncertain BCC Data Envelopment Analysis Model with Belief Degree: A case study in Iranian Banks,” INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS, vol. 13, no. 3 , pp. 239–249, 2021, [Online]. Available: https://sid.ir/paper/964303/en

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