Inverse Network DEA Incorporating Cost and Revenue Efficiencies Under Fuzzy Uncertainty

Fatemeh Gholami Golsefid, Monireh Jahani Sayyad Noveiri, Sohrab Kordrostami and Jun Ye

Journal of Mathematics, 2024, vol. 2024, 1-26

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.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:8719643

DOI: 10.1155/2024/8719643

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