A Novel Improved Data Envelopment Analysis Model Based on SBM and FDH Models

A Novel Improved Data Envelopment Analysis Model Based on SBM and FDH Models

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Submitted May 4, 2020
Published May 21, 2020
DOI https://doi.org/10.24018/ejece.2020.4.3.214
Abstract viewed = 521 times
Issue
Vol. 4 No. 3 (2020)
Section
Articles

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  •   Mirpouya Mirmozaffari

    •    The University of Texas at Arlington, USA.
  •   Gohar Azeem

    •    The University of Texas at Arlington, USA.
  •   Azam Boskabadi

    •    The University of Texas at Arlington, USA.
  •   Ali Aranizadeh

    •    Amirkabir University of Technology, Iran.
  •   Aditya Vaishnav

    •    The University of Texas at Arlington, USA.
  •   Jithin John

    •    The University of Texas at Arlington, USA.

Abstract

During the past decade, applying nonparametric operation research problems such as Data Envelopment Analysis(DEA) has received significant consideration among researchers. In this paper, a new DEA-based SBM-FDH model is introduced. Finally, productivity evaluation for banking systems in Malmquist Productivity Index (MPI) based on the proposed model has been compared with Slack Based Measurement (SBM) and Free Disposal Hull (FDH). The obtained results confirm the high performance of the proposed model in comparison to the other models used in this paper.                                                                                                                                                                                                                                                                                                                           


Keywords: Data Envelopment Analysis; Slack Based Measurement; Free Disposal Hull; Malmquist Productivity Index; SBM-FDH

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How to Cite
[1]
Mirmozaffari, M., Azeem, G., Boskabadi, A., Aranizadeh, A., Vaishnav, A. and John, J. 2020. A Novel Improved Data Envelopment Analysis Model Based on SBM and FDH Models. European Journal of Electrical Engineering and Computer Science. 4, 3 (May 2020). DOI:https://doi.org/10.24018/ejece.2020.4.3.214.