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Measuring Chinese Bank Performance with Undesirable Outputs: A Slack-Based Two-Stage Network DEA Approach

In: Data-Enabled Analytics

Author

Listed:
  • Ya Chen

    (Hefei University of Technology)

  • Mengyuan Wang

    (Hefei University of Technology)

  • Jingyu Yang

    (Hefei University of Technology)

Abstract

Data envelopment analysis (DEA) under big data has become a hot topic in recent years. It is proposed that network DEA is big data enabled analytics and is related to the value dimension of big data. In this paper we evaluate Chinese banks’ two-stage network performance from 2009 to 2018. To do this an undesirable variable slacks-based measure(UVSBM) model is developed for measuring bank performance in the presence of undesirable outputs. We analyze and test efficiencies of 20 Chinese listed commercial banks and investigate the impact of interest rate marketization on bank efficiency. Our results suggest: (1) The source of inefficiency of different banks is from the fund-raising stage or the fund-using stage; (2) The overall efficiency and fund-raising efficiency of 20 Chinese listed banks follow the same trend, declined in 2009–2011 and then increased in 2012–2018. However, the fund-using efficiency is stable during the sample period; (3) On average, with the acceleration of interest rate market liberalization, the efficiency of Chinese commercial banks has improved slightly. But its improvement is insignificant; (4) For different types of banks the efficiency of state-owned commercial banks (SOCBs) is higher than that of city commercial banks (CCBs) followed by joint-stock commercial banks (JSCBs). And this difference is mainly reflected in the fund-raising stage. Besides, our results also suggest a potential improvement for each inefficient bank.

Suggested Citation

  • Ya Chen & Mengyuan Wang & Jingyu Yang, 2021. "Measuring Chinese Bank Performance with Undesirable Outputs: A Slack-Based Two-Stage Network DEA Approach," International Series in Operations Research & Management Science, in: Joe Zhu & Vincent Charles (ed.), Data-Enabled Analytics, pages 299-326, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-75162-3_11
    DOI: 10.1007/978-3-030-75162-3_11
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    Cited by:

    1. Huaqing Wu & Jingyu Yang & Wensheng Wu & Ya Chen, 2023. "Interest rate liberalization and bank efficiency: A DEA analysis of Chinese commercial banks," 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. 31(2), pages 467-498, June.

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