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Data Envelopment Analysis on Relative Efficiency Assessment and Improvement: Evidence from Chinese Bank Branches

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Eurasian Business and Economics Perspectives

Part of the book series: Eurasian Studies in Business and Economics ((EBES,volume 21))

Abstract

By creating credits commercial banks contribute to the national economy and their branches are the catalysts of depositing, lending, and other associated activities. To comprehend the efficiency of commercial banks their branches must be brought under the microscope. The purpose of this chapter is to analyze the comparative efficiency of the bank branches from a micro point of view by introducing environmental changes. Firstly, we utilize Data Envelopment Analysis (DEA) to micro-analyze 18 bank branches of a Chinese commercial bank. Secondly, we decompose the effectiveness into efficiency and productivity to estimate the bank branches’ relative efficiency and productivity. To add, we also examine overall productivity along with average efficiency that assists in understanding each staff’s performance; this is a rarely investigated territory. Thirdly, we employ operating environment factors—a novel approach—with three dimensions (business conditions, competitiveness, and future development) to further detect and rank bank branches efficiency. We found that some branches performed efficiently (inefficiently) even in lower (higher) external environments; hence, locations and individual performance are vital influencers of bank branches’ efficiency. We recommend practical measures to improve the efficiency of inefficient branches in the areas of expense, revenue, and management; this will be beneficial for any commercial bank’s policy-making efforts.

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References

  • Antunes, J., Hadi-Vencheh, A., Jamshidi, A., Tan, Y., & Wanke, P. (2021). Bank efficiency estimation in China: DEA-RENNA approach. Annals of Operations Research, 2021. https://doi.org/10.1007/s10479-021-04111-2

  • Chan, S. G., & Karim, M. Z. A. (2010). Bank efficiency and macro-economic factors: The case of developing countries. Global Economic Review, 39(3), 269–289.

    Article  Google Scholar 

  • Chames, A., Cooper, W. W., & Rhodes, E. (1978). A data envelopment analysis approach to evaluation of the program follow through experiments in U.S. public school education, management science research report (Vol. No. 432). Carnegie-Mellon University, School of Urban and Public Affairs.

    Google Scholar 

  • Chen, X. (2020). Exploring the sources of financial performance in Chinese banks: A comparative analysis of different types of banks. The North American Journal of Economics and Finance, 51, 101076. https://doi.org/10.1016/j.najef.2019.101076

    Article  Google Scholar 

  • Chi, G., Yang, D., & Wu, S. (2006). China commercial Bank comprehensive efficiency research-based on the DEA method. Chinese Journal of Management Science, 5, 52–61.

    Google Scholar 

  • Dong, Y., Firth, M., Hou, W., & Yang, W. (2016). Evaluating the performance of Chinese commercial banks: A comparative analysis of different types of banks. European Journal of Operational Research, 252(1), 280–295.

    Article  Google Scholar 

  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A (General), 120, 253–290.

    Article  Google Scholar 

  • Golany, B., & Storbeck, J. E. (1999). A data envelopment analysis of the operational efficiency of bank branches. Economics of Education Review, 25(9), 273–288.

    Google Scholar 

  • Haag, S. E., & Jaska, P. V. (1995). Interpreting inefficiency ratings: An application of bank branch operating efficiencies. Managerial and Decision Economics, 16(1), 7–14.

    Article  Google Scholar 

  • Liu, X., Yang, F., & Wu, J. (2020). DEA considering technological heterogeneity and intermediate output target setting: The performance analysis of Chinese commercial banks. Annals of Operations Research, 291, 605–626.

    Article  Google Scholar 

  • Luo, Y., Bi, G., & Liang, L. (2012). Input/output indicator selection for DEA efficiency evaluation: An empirical study of Chinese commercial banks. Expert Systems with Applications, 39, 1118–1123.

    Article  Google Scholar 

  • Matousek, R., Rughoo, A., Sarantis, N., & Assa, A. G. (2015). Bank performance and convergence during the financial crisis: Evidence from the ‘old’ European Union and Eurozone. Journal of Banking and Finance, 52(C), 208–216.

    Article  Google Scholar 

  • McEachern, D., & Paradi, J. C. (2007). Intra-and inter-country bank branch assessment using DEA. Journal of Productivity Analysis, 27(2), 123–126.

    Article  Google Scholar 

  • Niknafs, J., Keramati, M. A., & Monfared, J. H. (2020). Estimating efficiency of Bank branches by dynamic network data envelopment analysis and artificial neural network. Advances in Mathematical Finance and Applications, 5(3), 377–390. https://doi.org/10.22034/amfa.2019.1585957.1192

    Article  Google Scholar 

  • Paradi, J. C., Vela, S. A., & Zhu, H. (2010). Adjusting for cultural differences, a new DEA model applied to a merged bank. Journal of Productivity Analysis, 33(2), 109–123.

    Article  Google Scholar 

  • Paradi, J. C., Rouatt, S., & Zhu, H. (2011). Two-stage evaluation of bank branch efficiency using data envelopment analysis. Omega, 39(1), 99–109.

    Article  Google Scholar 

  • Paradi, J. C., & Schaffnit, C. (2004). Commercial branch performance evaluation and results communication in a Canadian bank–A DEA application. European Journal of Operational Research, 156(3), 719–735.

    Article  Google Scholar 

  • Shokrollahpour, E., Lotfi, F. H., & Zandieh, M. (2016). An integrated data envelopment analysis–artificial neural network approach for benchmarking of bank branches. Journal of Industrial Engineering International, 12, 137–143.

    Article  Google Scholar 

  • Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 U.S. commercial banks. Management Science, 45(9), 1270–1288.

    Article  Google Scholar 

  • Sherman, H. D., & Gold, F. (1985). Bank branch operating efficiency: Evaluation with data envelopment analysis. Journal of Banking & Finance, 9 2, 297–315.

    Article  Google Scholar 

  • Sherman, H. D., & Ladino, G. (1995). Managing bank productivity using data envelopment analysis (DEA). Interfaces, 25(2), 60–73.

    Article  Google Scholar 

  • Song, Z., Zhang, Z., & Yuan, M. (2009). An empirical DEA efficiency research of China Bank industry. Journal of Systems Science and Information, 12, 105–110.

    Google Scholar 

  • Vassiloglou, M., & Giokas, D. (1990). A study of the relative efficiency of bank branches: An application of data envelopment analysis. Journal of the Operational Research Society, 41(7), 591–597.

    Article  Google Scholar 

  • Vu, L. T., Nguyen, N. T., & Dinh, L. H. (2019). Measuring banking efficiency in Vietnam: Parametric and non-parametric methods. Banks and Bank Systems, 14(1), 55–64. https://doi.org/10.21511/bbs.14(1).2019.06

    Article  Google Scholar 

  • Wang, J., Jin, H., & Liang, H. (2011). Analysis on efficiency of China commercial banks - based on SE-DEA and Malmquist index. Techno-economics & Management Research, 4, 124–127.

    Google Scholar 

  • Wei, L., & Wang, L. (2000). The non-parametric approach to the measurement of efficiency: The case of China commercial banks. Journal of Financial Research, 3, 88–96.

    Google Scholar 

  • Wei, J., Ye, T., & Zhang, Z. (2021). A machine learning approach to evaluate the performance of rural Bank. Hindawi Complexity, 2021. https://doi.org/10.1155/2021/6649605

  • Wu, D. S., Yang, Z. J., & Liang, L. A. (2006). Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank. Expert Systems with Applications, 31, 108–115.

    Article  Google Scholar 

  • Xu, X., & Shi, P. (2006). Efficiency comparative study on commercial Bank in China Based on DEA and SFA. Journal of Applied Statistics and Management, 1, 68–72.

    Google Scholar 

  • Zhang, J. (2003). DEA method on efficiency study of Chinese commercial banks and the positivist analysis from 1997 to 2001. Journal of Financial Research, 3, 11–25.

    Google Scholar 

  • Zhao, L., Zhu, Q. Y., & Zhang, L. (2021). Regulation adaptive strategy and bank efficiency: A network slacks-based measure with shared resources. European Journal of Operational Research, 295, 348–362.

    Article  Google Scholar 

  • Zhou, F., Zhang, H., & Sun, B. (2010). China commercial Bank efficiency evaluation-based on the two stages DEA model. Journal of Financial Research, 11, 169–179.

    Google Scholar 

  • Zhou, L., & Zhu, S. (2017). Research on the efficiency of Chinese commercial banks based on undesirable output and super-SBM DEA model. Journal of Mathematical Finance, 7, 102–120.

    Article  Google Scholar 

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Correspondence to Meifen Chu .

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Chu, M., Zhou, G., Wu, W. (2022). Data Envelopment Analysis on Relative Efficiency Assessment and Improvement: Evidence from Chinese Bank Branches. In: Bilgin, M.H., Danis, H., Demir, E., Zaremba, A. (eds) Eurasian Business and Economics Perspectives. Eurasian Studies in Business and Economics, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-030-94036-2_9

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