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Abstract：
The main aim of this research is to present an innovative method known as fuzzy network data envelopment analysis (FNDEA) in order to assess the performance of network decision-making units (DMUs) that possess a two-stage structure while taking into account the uncertainty of data. To attain this goal, we utilize various methodologies including the non-cooperative game (leader-follower) NDEA method, the concept of Z-number, credibility theory, and chance-constrained programming (CCP) to develop a model for the fuzzy NDEA approach. The FNDEA approach offers several advantages, such as the linearity of the presented FNDEA models, the ability to rank two-stage DMUs in situations of ambiguity, the provision of a unique efficiency decomposition method in an uncertain environment, and the capability to handle Z-information. To demonstrate the applicability and effectiveness of the proposed approach, we implement the Z-number network data envelopment analysis (ZNDEA) approach in assessing the performance of Iranian private insurance companies. The results of this implementation reveal that the proposed ZNDEA method is suitable and effective for measuring and ranking insurance companies in situations where data ambiguity is present.
摘要：
本研究的主要目的是提出一种称为模糊网络数据包络分析（FNDEA）的创新方法，以评估具有两阶段结构的网络决策单元（DMU）的性能，同时考虑到数据的不确定性。为了实现这一目标,我们利用各种方法，包括非合作博弈(领导者-追随者)NDEA方法，Z数的概念,可信性理论，和机会约束规划(CCP)来建立模糊NDEA方法的模型。FNDEA方法提供了几个优点，例如所提出的FNDEA模型的线性，在模糊的情况下对两级DMU进行排名的能力，在不确定环境中提供独特的效率分解方法，以及处理Z信息的能力。为了证明所提出方法的适用性和有效性，在评估伊朗私人保险公司的绩效时，我们采用了Z-number网络数据包络分析（ZNDEA）方法。该实施的结果表明，所提出的ZNDEA方法适用于在存在数据歧义的情况下对保险公司进行测量和排名是有效的。
