Two-stage network data envelopment analysis model with Z-numbers: An application to mutual funds

This research paper presents a novel Network Data Envelopment Analysis (NDEA) model incorporating Z-numbers for evaluating the performance of two-stage Decision-Making Units (DMUs) under data ambiguity. The proposed model integrates the principles of NDEA, Production Possibility Set (PPS), Z-number theory, and fuzzy optimization techniques to provide a comprehensive framework for performance evaluation. Notably, the Z-number data is processed by converting it into equivalent fuzzy numbers to facilitate computation within the Data Envelopment Analysis (DEA) framework. By considering the complex interactions among DMUs and incorporating uncertainty using Z-numbers, the proposed model offers an effective approach to efficiency analysis. The two-stage structure of the model allows for a detailed examination of the PPS, while Z-number theory and possibilistic programming techniques are employed to handle imprecise data and enhance decision-making processes. The proposed model's effectiveness and applicability are showcased through empirical validation and case studies within the mutual funds industry. By utilizing the Z-number two-stage network DEA approach, this research endeavors to establish an effective framework for evaluating mutual funds’ performance. This framework aims to address the complexities and ambiguities commonly encountered in financial decision-making processes, offering a comprehensive methodology for assessing mutual funds’ performance.

کلیدواژه ها:

Network Data Envelopment Analysis ، Z-Number Theory ، fuzzy optimization ، Possibilistic programming ، Adjustable Fuzzy Measure