Abstract
We consider a two-stage parallel-series system having three sub-systems. The independent two sub-systems of the first stage are linked in parallel and then linked to the third sub-system of the second stage in series. The deterministic two-stage parallel-series system approach is extended to uncertain/imprecise environment where the data are represented as fuzzy numbers. Using the Zadeh extension principle, we develop a fuzzy two-stage parallel-series system to determine the lower and upper bound fuzzy efficiencies of the decision-making units with the help of \(\alpha -\) cut and rank the DMUs using the ranking index approach. The proposed methodology is illustrated using the case of Taiwan’s non-life insurance companies.
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Acknowledgements
The authors wish to express their sincere thanks to the anonymous reviewers for their insightful comments which have significantly improved the quality of the work. We also express our gratitude to the Editor-in-Chief and Associate Editor for coordinating the entire process and ensuring the timely reviews. This study was funded by Indian Institute of Management Calcutta, India, with Grant number RP:DFPADEAMUD /3777/2018-19.
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Alka Arya and Sanjeet Singh have received research grant from Indian Institute of Management Calcutta, India.
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Arya, A., Singh, S. Development of two-stage parallel-series system with fuzzy data: A fuzzy DEA approach. Soft Comput 25, 3225–3245 (2021). https://doi.org/10.1007/s00500-020-05374-w
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DOI: https://doi.org/10.1007/s00500-020-05374-w