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Performance Evaluation by SBM DEA Model Under Fuzzy Environments Using Expected Credits

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dc.contributor.author Agarwal, Shivi
dc.contributor.author Mathur, Trilok
dc.date.accessioned 2023-08-09T08:46:28Z
dc.date.available 2023-08-09T08:46:28Z
dc.date.issued 2023-03
dc.identifier.uri https://link.springer.com/chapter/10.1007/978-981-19-6525-8_43
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11250
dc.description.abstract Performance evaluation is always the interest of the manager in every sector like banks, supply chain management, etc. Data envelopment analysis (DEA) is an operations research methodology based on linear programming, which is used to evaluate the performance of decision-making units (DMUs). The available data in real-life scenarios may be present in the vague form. Therefore, the crisp DEA model cannot be used for efficiency evaluation. In the present study, the slacks based model (SBM) DEA model is integrated with the fuzzy set theory to overcome the problem. The expected credits approach is used to solve the fuzzy SBM DEA model in the proposed study. The relative efficiency of the Indian oil refineries is calculated using this methodology, and the rank of the companies is computed from their relative efficiency. en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject Mathematics en_US
dc.subject Data Envelopment Analysis (DEA) en_US
dc.subject Uncertainty en_US
dc.subject SBM model en_US
dc.subject Credibility measure en_US
dc.subject Decision-making units en_US
dc.title Performance Evaluation by SBM DEA Model Under Fuzzy Environments Using Expected Credits en_US
dc.type Article en_US


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