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Inverse Network DEA Incorporating Cost and Revenue Efficiencies Under Fuzzy Uncertainty

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  • Fatemeh Gholami Golsefid
  • Monireh Jahani Sayyad Noveiri
  • Sohrab Kordrostami
  • Jun Ye

Abstract

The study of network cost and revenue efficiency and changes related to performance measures in uncertain environments is an important area of research in decision-making analysis. A generalized inverse data envelopment analysis (DEA) approach is advanced in this examination for addressing the complexities associated with imprecise inputs and outputs within two-stage networks. Additionally, the second stage of the network is evaluated for the existence of unwanted outputs. The proposed methodology focuses on estimating fuzzy performance measures in two-stage processes while maintaining consistent fuzzy technical efficiency and cost efficiency (revenue efficiency). To demonstrate the practical application of this approach, data from various branches of a bank in Iran, which are characterized by inaccurate data and undesirable outputs, is analyzed, yielding logical and insightful results.

Suggested Citation

  • Fatemeh Gholami Golsefid & Monireh Jahani Sayyad Noveiri & Sohrab Kordrostami & Jun Ye, 2024. "Inverse Network DEA Incorporating Cost and Revenue Efficiencies Under Fuzzy Uncertainty," Journal of Mathematics, Hindawi, vol. 2024, pages 1-26, November.
    • Handle: RePEc:hin:jjmath:8719643
    DOI: 10.1155/2024/8719643
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