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DEA considering technological heterogeneity and intermediate output target setting: the performance analysis of Chinese commercial banks

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  • Xiaohong Liu

    (University of Science and Technology of China)

  • Feng Yang

    (University of Science and Technology of China)

  • Jie Wu

    (University of Science and Technology of China)

Abstract

This study proposes a two-stage data envelopment analysis model based on the meta-frontier boundary and intermediate output goal setting. Comparing to the traditional models, the proposed model is able not only to consider technology heterogeneity of decision making units, but also to target the intermediate output. The proposed model was applied to an analysis of 28 Chinese commercial banks (CCBs). Empirical analysis has obtained some valuable research results. First, the efficiency of the CCBs’ deposit sub-system is not very high, especially in terms of the deposit efficiency of city commercial banks (CBs). Second, in the deposit sub-system, the efficiency gap among state-owned commercial banks (SBs) is higher than the joint stock commercial banks (JBs) and the CBs. Third, in the loan sub-system, the efficiency gap among SBs and CBs is higher than that in the JBs. Fourth, the deposits of more than half of CCBs are not on the frontier of efficiency, showing that the financial resource allocation of CCBs is severely ineffective. Finally, this study divides CCBs into four categories and provides specific recommendations to improve performance and deposit target setting.

Suggested Citation

  • Xiaohong Liu & Feng Yang & Jie Wu, 2020. "DEA considering technological heterogeneity and intermediate output target setting: the performance analysis of Chinese commercial banks," Annals of Operations Research, Springer, vol. 291(1), pages 605-626, August.
    • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-019-03413-w
    DOI: 10.1007/s10479-019-03413-w
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    1. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    2. Xiao Shi & Yongjun Li & Ali Emrouznejad & Jianhui Xie & Liang Liang, 2017. "Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1045-1055, September.
    3. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    4. Fukuyama, Hirofumi & Matousek, Roman, 2011. "Efficiency of Turkish banking: Two-stage network system. Variable returns to scale model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 75-91, February.
    5. Paradi, Joseph C. & Zhu, Haiyan, 2013. "A survey on bank branch efficiency and performance research with data envelopment analysis," Omega, Elsevier, vol. 41(1), pages 61-79.
    6. Matthews, Kent, 2013. "Risk management and managerial efficiency in Chinese banks: A network DEA framework," Omega, Elsevier, vol. 41(2), pages 207-215.
    7. Chien Wang & Ram Gopal & Stanley Zionts, 1997. "Use of Data Envelopment Analysis in assessing Information Technology impact on firm performance," Annals of Operations Research, Springer, vol. 73(0), pages 191-213, October.
    8. 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.
    9. Chih-Ching Yang, 2014. "An enhanced DEA model for decomposition of technical efficiency in banking," Annals of Operations Research, Springer, vol. 214(1), pages 167-185, March.
    10. Sherman, H. David & Gold, Franklin, 1985. "Bank branch operating efficiency : Evaluation with Data Envelopment Analysis," Journal of Banking & Finance, Elsevier, vol. 9(2), pages 297-315, June.
    11. Feng Yang & Dexiang Wu & Liang Liang & Gongbing Bi & Desheng Wu, 2011. "Supply chain DEA: production possibility set and performance evaluation model," Annals of Operations Research, Springer, vol. 185(1), pages 195-211, May.
    12. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    13. Avkiran, Necmi K., 2011. "Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks," Omega, Elsevier, vol. 39(3), pages 323-334, June.
    14. Chen, Yao & Cook, Wade D. & Li, Ning & Zhu, Joe, 2009. "Additive efficiency decomposition in two-stage DEA," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1170-1176, August.
    15. Vincent Charles & Ioannis E. Tsolas & Tatiana Gherman, 2018. "Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector," Annals of Operations Research, Springer, vol. 269(1), pages 81-102, October.
    16. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.
    17. Sturm, Jan-Egbert & Williams, Barry, 2004. "Foreign bank entry, deregulation and bank efficiency: Lessons from the Australian experience," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1775-1799, July.
    18. Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
    19. Chen, Yu-Chuan & Chiu, Yung-Ho & Huang, Chin-Wei & Tu, Chien Heng, 2013. "The analysis of bank business performance and market risk—Applying Fuzzy DEA," Economic Modelling, Elsevier, vol. 32(C), pages 225-232.
    20. Somayeh Soheilirad & Kannan Govindan & Abbas Mardani & Edmundas Kazimieras Zavadskas & Mehrbakhsh Nilashi & Norhayati Zakuan, 2018. "Application of data envelopment analysis models in supply chain management: a systematic review and meta-analysis," Annals of Operations Research, Springer, vol. 271(2), pages 915-969, December.
    21. Ying Li & Yung-ho Chiu & Tai-Yu Lin & Yun Yuan Huang, 2019. "Market share and performance in Taiwanese banks: min/max SBM DEA," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 233-252, July.
    22. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1658-1668.
    23. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    24. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    25. Wu, Jie & Chu, Junfei & Sun, Jiasen & Zhu, Qingyuan, 2016. "DEA cross-efficiency evaluation based on Pareto improvement," European Journal of Operational Research, Elsevier, vol. 248(2), pages 571-579.
    26. Xiao Shi & Yongjun Li & Ali Emrouznejad & Jianhui Xie & Liang Liang, 2017. "Erratum to: Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 983-983, August.
    27. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    28. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
    29. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    30. Zha, Yong & Liang, Nannan & Wu, Maoguo & Bian, Yiwen, 2016. "Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach," Omega, Elsevier, vol. 60(C), pages 60-72.
    31. Fukuyama, Hirofumi & Matousek, Roman, 2017. "Modelling bank performance: A network DEA approach," European Journal of Operational Research, Elsevier, vol. 259(2), pages 721-732.
    32. Wang, Ke & Huang, Wei & Wu, Jie & Liu, Ying-Nan, 2014. "Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA," Omega, Elsevier, vol. 44(C), pages 5-20.
    33. Hou, Xiaohui & Gao, Zhixian & Wang, Qing, 2016. "Internet finance development and banking market discipline: Evidence from China," Journal of Financial Stability, Elsevier, vol. 22(C), pages 88-100.
    34. Sun, Jiasen & Yuan, Yang & Yang, Rui & Ji, Xiang & Wu, Jie, 2017. "Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis," Transport Policy, Elsevier, vol. 60(C), pages 75-86.
    35. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    36. Chiu, Ching-Ren & Liou, Je-Liang & Wu, Pei-Ing & Fang, Chen-Ling, 2012. "Decomposition of the environmental inefficiency of the meta-frontier with undesirable output," Energy Economics, Elsevier, vol. 34(5), pages 1392-1399.
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    2. Facundo Costa de Arguibel & Carolina Wittig & Juan Antonio Dip, 2023. "Estructura de Propiedad, Origen de Capital y Eficiencia Bancaria: Evidencia para A," Working Papers 251, Red Nacional de Investigadores en Economía (RedNIE).
    3. David Cummins, J. & Rubio-Misas, María, 2021. "Country factor behavior for integration improvement of European life insurance markets," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 186-202.
    4. Jiawei Yang, 2023. "Disentangling the sources of bank inefficiency: a two-stage network multi-directional efficiency analysis approach," Annals of Operations Research, Springer, vol. 326(1), pages 369-410, July.
    5. 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.

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