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Efficiency evaluation for banking systems under uncertainty: A multi-period three-stage DEA model

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  • Zhou, Xiaoyang
  • Xu, Zhongwen
  • Chai, Jian
  • Yao, Liming
  • Wang, Shouyang
  • Lev, Benjamin

Abstract

Efficiency evaluations are vital for banks so that they can determine their future development and enhance their competitiveness. To comprehensively explore a bank’s internal structures and identify the specific reasons for any inefficiencies, three stages of banking systems need to be examined; capital organization, capital allocation, and profitability. To measure the efficiencies over consecutive periods, this paper developed a multi-period, multi-stage DEA model, in which unused assets were carried over to subsequent periods, fixed assets and employee salaries were regarded as shared inputs for all three stages, and non-performing loans, which were characterized using triangular type-2 fuzzy numbers, were introduced as undesirable outputs to reflect credit risk. The developed model was applied to a case study to evaluate the efficiencies of listed Chinese commercial banks from 2014 to 2016, from which a disparity in efficiencies was found; that is all banks were found to be generally inefficient; however, the inefficiencies occurred in different stages for different types of banks. Varying optimistic-pessimistic attitudes were applied to identify the overly sensitive banks and comparisons were conducted to provide managerial insights and verify the superiority of the proposed model. It was concluded that to enhance overall efficiency, banks need to have a reasonable business scale, that adopting a three-stage analytical framework can better identify efficiencies and the weaker stages, and that neglecting carryovers can overestimate bank performance.

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  • Zhou, Xiaoyang & Xu, Zhongwen & Chai, Jian & Yao, Liming & Wang, Shouyang & Lev, Benjamin, 2019. "Efficiency evaluation for banking systems under uncertainty: A multi-period three-stage DEA model," Omega, Elsevier, vol. 85(C), pages 68-82.
  • Handle: RePEc:eee:jomega:v:85:y:2019:i:c:p:68-82
    DOI: 10.1016/j.omega.2018.05.012
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    as
    1. Wei-Hsin Kong & Tsu-Tan Fu & Ming-Miin Yu, 2017. "Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1043-1068, July.
    2. Jie Wu & Yafei Yu & Qingyuan Zhu & Qingxian An & Liang Liang, 2018. "Closest target for the orientation-free context-dependent DEA under variable returns to scale," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(11), pages 1819-1833, November.
    3. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    4. Galagedera, Don U.A. & Roshdi, Israfil & Fukuyama, Hirofumi & Zhu, Joe, 2018. "A new network DEA model for mutual fund performance appraisal: An application to U.S. equity mutual funds," Omega, Elsevier, vol. 77(C), pages 168-179.
    5. Brian W. Jacobs & Richard Kraude & Sriram Narayanan, 2016. "Operational Productivity, Corporate Social Performance, Financial Performance, and Risk in Manufacturing Firms," Production and Operations Management, Production and Operations Management Society, vol. 25(12), pages 2065-2085, December.
    6. Chen, Kaihua & Kou, Mingting & Fu, Xiaolan, 2018. "Evaluation of multi-period regional R&D efficiency: An application of dynamic DEA to China's regional R&D systems," Omega, Elsevier, vol. 74(C), pages 103-114.
    7. Kaoru Tone & Miki Tsutsui, 2014. "Slacks-Based Network DEA," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 231-259, Springer.
    8. Tsan-Ming Choi & T. C. E. Cheng & Xiande Zhao & Desheng Dash Wu & Cuicui Luo & Haofei Wang & John R. Birge, 2016. "Bi-level Programing Merger Evaluation and Application to Banking Operations," Production and Operations Management, Production and Operations Management Society, vol. 25(3), pages 498-515, March.
    9. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    10. Huang, Tai-Hsin & Lin, Chung-I & Chen, Kuan-Chen, 2017. "Evaluating efficiencies of Chinese commercial banks in the context of stochastic multistage technologies," Pacific-Basin Finance Journal, Elsevier, vol. 41(C), pages 93-110.
    11. Juo, Jia-Ching & Fu, Tsu-Tan & Yu, Ming-Miin & Lin, Yu-Hui, 2016. "Non-radial profit performance: An application to Taiwanese banks," Omega, Elsevier, vol. 65(C), pages 111-121.
    12. Azadi, Majid & Shabani, Amir & Khodakarami, Mohsen & Farzipoor Saen, Reza, 2015. "Reprint of “Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 74(C), pages 22-36.
    13. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    14. GHASEMI, M.R. & IGNATIUS, J. & LOZANO, S. & EMROUZNEJAD, A. & HATAMI-MARBINI, Adel, 2015. "A fuzzy expected value approach under generalized data envelopment analysis," LIDAM Reprints CORE 2716, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    16. Chiou, Yu-Chiun & Lan, Lawrence W. & Yen, Barbara T.H., 2010. "A joint measurement of efficiency and effectiveness for non-storable commodities: Integrated data envelopment analysis approaches," European Journal of Operational Research, Elsevier, vol. 201(2), pages 477-489, March.
    17. Desheng Wu & Zhaoxin Zhou & John Birge, 2011. "Estimation of potential gains from mergers in multiple periods: a comparison of stochastic frontier analysis and Data Envelopment Analysis," Annals of Operations Research, Springer, vol. 186(1), pages 357-381, June.
    18. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    19. Akther, Syed & Fukuyama, Hirofumi & Weber, William L., 2013. "Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking," Omega, Elsevier, vol. 41(1), pages 88-96.
    20. Chia-Hsuan Wu & Ching-Cheng Chang & Ken N. Kuo, 2008. "Evaluating the resource allocation efficiency of the healthcare system in Taiwan," International Journal of Public Policy, Inderscience Enterprises Ltd, vol. 3(5/6), pages 403-418.
    21. Ghahraman, Abaghan & Prior, Diego, 2016. "A learning ladder toward efficiency: Proposing network-based stepwise benchmark selection," Omega, Elsevier, vol. 63(C), pages 83-93.
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    5. M.V. Leonov, 2021. "Review of Modern Approaches for Assessing the Effectiveness of Banking," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(2), pages 294-326.
    6. Andrey V. Lychev & Svetlana V. Ratner & Vladimir E. Krivonozhko, 2023. "Two-Stage Data Envelopment Analysis Models with Negative System Outputs for the Efficiency Evaluation of Government Financial Policies," Mathematics, MDPI, vol. 11(24), pages 1-21, December.
    7. Toloo, Mehdi & Mensah, Emmanuel Kwasi & Salahi, Maziar, 2022. "Robust optimization and its duality in data envelopment analysis," Omega, Elsevier, vol. 108(C).
    8. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2023. "Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1360-1373.
    9. Bao-Ngoc Tong & Cheng-Ping Cheng & Lien-Wen Liang & Yi-Jun Liu, 2023. "Using Network DEA to Explore the Effect of Mobile Payment on Taiwanese Bank Efficiency," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
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    11. Yong Tan & Mike G. Tsionas, 2022. "Modelling sustainability efficiency in banking," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3754-3772, July.
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    13. Sheng-Hsiung Chiu & Tzu-Yu Lin & Wei-Ching Wang, 2024. "Investigating the spatial effect of operational performance in China’s regional tourism system," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    14. Lartey, Theophilus & James, Gregory A. & Danso, Albert, 2021. "Interbank funding, bank risk exposure and performance in the UK: A three-stage network DEA approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
    15. Arezoo Mohammadi & Mehrzad Minnoei & Zadollah Fathi & Mohamamd Ali Keramati & Hossein Baktiari, 2022. "Optimal allocation of bank resources and risk reduction through portfolio decentralization," International Journal of Economic Sciences, European Research Center, vol. 11(2), pages 92-143, November.
    16. Ather Hassan Dar & Somesh Kumar Mathur & Sila Mishra, 2021. "The Efficiency of Indian Banks: A DEA, Malmquist and SFA Analysis with Bad Output," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 653-701, December.
    17. Zhao, Linlin & Zhu, Qingyuan & Zhang, Lin, 2021. "Regulation adaptive strategy and bank efficiency: A network slacks-based measure with shared resources," European Journal of Operational Research, Elsevier, vol. 295(1), pages 348-362.
    18. Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.
    19. Lívia Torres & Francisco S. Ramos, 2024. "Allocating Benefits Due to Shared Resources Using Shapley Value and Nucleolus in Dynamic Network Data Envelopment Analysis," Mathematics, MDPI, vol. 12(5), pages 1-23, February.
    20. Jorge Antunes & Abdollah Hadi-Vencheh & Ali Jamshidi & Yong Tan & Peter Wanke, 2022. "Bank efficiency estimation in China: DEA-RENNA approach," Annals of Operations Research, Springer, vol. 315(2), pages 1373-1398, August.
    21. Zhengxiao Yan & Wei Zhou & Yuyi Wang & Xi Chen, 2022. "Comprehensive Analysis of Grain Production Based on Three-Stage Super-SBM DEA and Machine Learning in Hexi Corridor, China," Sustainability, MDPI, vol. 14(14), pages 1-21, July.

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