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Cost efficiency in an Indian bank branch network: A centralized resource allocation model

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  • Ray, Subhash

Abstract

In the present study we evaluate the overall cost efficiency of a network of branches of a single large public sector bank in India within the city of Calcutta using the data for the year 2012. Our objective is to determine the optimal number of branches within a postal district that could provide the observed amounts of banking services to the customers in that area at the minimum operating cost. Our DEA results show that there is an evidence of ‘over-branching’ and for the entire network reducing the total number of branches would be more cost efficient. However, there are numerous instances, where increasing the number of branches within a market area would be optimal.

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  • Ray, Subhash, 2016. "Cost efficiency in an Indian bank branch network: A centralized resource allocation model," Omega, Elsevier, vol. 65(C), pages 69-81.
    • Handle: RePEc:eee:jomega:v:65:y:2016:i:c:p:69-81
    DOI: 10.1016/j.omega.2015.12.009
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    Cited by:

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    2. Fang, Lei, 2022. "Measuring and decomposing group performance under centralized management," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1006-1013.
    3. Camanho, Ana Santos & Silva, Maria Conceicao & Piran, Fabio Sartori & Lacerda, Daniel Pacheco, 2024. "A literature review of economic efficiency assessments using Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 315(1), pages 1-18.
    4. Cesaroni, Giovanni, 2020. "Technically and cost-efficient centralized allocations in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    5. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    6. Yingying Shao & Gongbing Bi & Feng Yang & Qiong Xia, 2018. "Resource allocation for branch network system with considering heterogeneity based on DEA method," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 1005-1025, December.
    7. Aggelopoulos, Eleftherios & Georgopoulos, Antonios, 2017. "Bank branch efficiency under environmental change: A bootstrap DEA on monthly profit and loss accounting statements of Greek retail branches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1170-1188.
    8. Subhash C. Ray & Abhiman Das & Kankana Mukherjee, 2018. "Measures of Labor Use Efficiency from a Cost-Based Dual Representation of the Technology: A Study of Indian Bank Branches," Working papers 2018-17, University of Connecticut, Department of Economics.
    9. Subhash C. Ray & Abhiman Das & Kankana Mukherjee, 2017. "Labor-Cost Efficiency with Indivisible Outputs and Inputs: A Study of Indian Bank Branches," Working papers 2017-04, University of Connecticut, Department of Economics.
    10. Liesiö, Juuso & Andelmin, Juho & Salo, Ahti, 2020. "Efficient allocation of resources to a portfolio of decision making units," European Journal of Operational Research, Elsevier, vol. 286(2), pages 619-636.
    11. Garg, Poonam & Gupta, Bhumika & Chauhan, Ajay Kumar & Sivarajah, Uthayasankar & Gupta, Shivam & Modgil, Sachin, 2021. "Measuring the perceived benefits of implementing blockchain technology in the banking sector," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    12. Fukuyama, Hirofumi & Matousek, Roman & Tzeremes, Nickolaos G., 2020. "A Nerlovian cost inefficiency two-stage DEA model for modeling banks’ production process: Evidence from the Turkish banking system," Omega, Elsevier, vol. 95(C).
    13. Zhou, Xiaoyang & Luo, Rui & Tu, Yan & Lev, Benjamin & Pedrycz, Witold, 2018. "Data envelopment analysis for bi-level systems with multiple followers," Omega, Elsevier, vol. 77(C), pages 180-188.
    14. Ahmad, Wasim & Tiwari, Shiv Ratan & Wadhwani, Akshay & Khan, Mohammad Azeem & Bekiros, Stelios, 2023. "Financial networks and systemic risk vulnerabilities: A tale of Indian banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    15. Subhash C. Ray & Shilpa Sethia, 2023. "A State-Level Resource Allocation Model for Emission Reduction and Efficiency Improvement in Thermal Power Plants," Working papers 2023-08, University of Connecticut, Department of Economics.
    16. Sheng Dai & Natalia Kuosmanen & Timo Kuosmanen & Juuso Liesio, 2023. "Optimal resource allocation: Convex quantile regression approach," Papers 2311.06590, arXiv.org.

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