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.
Published Version
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