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A Novel Pythagorean Approach Based Sine-Shaped Fuzzy Data Envelopment Analysis Model: An Assessment of Indian Public Sector Banks

Author

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  • Mohammad Aqil Sahil

    (South Asian University)

  • Meenakshi Kaushal

    (South Asian University)

  • Q. M. Danish Lohani

    (South Asian University)

Abstract

Fuzzy Data Envelopment Analysis is a modeling technique that efficiently ranks decision-making units (DMUs) based on imprecise inputs and outputs. The method constructs an efficient frontier line that separates efficient and inefficient DMUs. The goal is to improve the efficiency score of each inefficient DMU by moving them to the efficient frontier. In this study, we introduce a new approach, called the Pythagorean approach, which considers both the input and the output aspects. The approach is applied to the CCR model, and a new version of the BCC model is introduced, known as the Pythagorean approach-based BCC model. To handle the vagueness of the data set, the Pythagorean approach-based BCC model is extended to a fuzzy environment using a new type of fuzzy number called a sine-shaped fuzzy number. Finally, the efficacy of the model is tested in Indian public sector banks.

Suggested Citation

  • Mohammad Aqil Sahil & Meenakshi Kaushal & Q. M. Danish Lohani, 2025. "A Novel Pythagorean Approach Based Sine-Shaped Fuzzy Data Envelopment Analysis Model: An Assessment of Indian Public Sector Banks," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1373-1395, March.
  • Handle: RePEc:kap:compec:v:65:y:2025:i:3:d:10.1007_s10614-024-10603-7
    DOI: 10.1007/s10614-024-10603-7
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    References listed on IDEAS

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    1. Jolly Puri & Shiv Prasad Yadav, 2013. "Performance evaluation of public and private sector banks in India using DEA approach," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 18(1), pages 91-121.
    2. Hatami-Marbini, Adel & Emrouznejad, Ali & Tavana, Madjid, 2011. "A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making," European Journal of Operational Research, Elsevier, vol. 214(3), pages 457-472, November.
    3. Amin Mahmoudi & Saad Ahmed Javed & Abbas Mardani, 2022. "Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era," Operations Management Research, Springer, vol. 15(1), pages 208-232, June.
    4. Bana e Costa, Carlos A. & Soares de Mello, João Carlos C.B. & Angulo Meza, Lidia, 2016. "A new approach to the bi-dimensional representation of the DEA efficient frontier with multiple inputs and outputs," European Journal of Operational Research, Elsevier, vol. 255(1), pages 175-186.
    5. Kao, Chiang & Liu, Shiang-Tai, 2004. "Predicting bank performance with financial forecasts: A case of Taiwan commercial banks," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2353-2368, October.
    6. EMROUZNEJAD, Ali & TAVANA, Madjid & HATAMI-MARBINI, Adel, 2014. "The state of the art in fuzzy data envelopment analysis," LIDAM Reprints CORE 2543, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, January.
    8. Jolly Puri & Shiv Prasad Yadav, 2017. "Improved DEA models in the presence of undesirable outputs and imprecise data: an application to banking industry in India," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1608-1629, November.
    9. Bauer, Paul W. & Berger, Allen N. & Ferrier, Gary D. & Humphrey, David B., 1998. "Consistency Conditions for Regulatory Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods," Journal of Economics and Business, Elsevier, vol. 50(2), pages 85-114, March.
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