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An Application of the Dynamic Network DEA Model: The Case of Banks in Taiwan

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  • Chuang-Min Chao
  • Ming-Miin Yu
  • Hsiao-Ning Wu

Abstract

In this study, we apply the dynamic network slack-based measure data envelopment analysis model (DNSBM) to measure the efficiency of Taiwanese banks during the period 2005–11. Using the network structure, we define intellectual capital creation capability as one of the production stages. In order to capture the dynamics of the transformation process, the nonperforming loans and loan loss reserves are defined as carryover items. This study offers sufficient information for managers to understand not only the overall performance of their banks but also the efficiency of each production stage and the dynamic changes of the overall and divisional efficiencies.

Suggested Citation

  • Chuang-Min Chao & Ming-Miin Yu & Hsiao-Ning Wu, 2015. "An Application of the Dynamic Network DEA Model: The Case of Banks in Taiwan," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(S1), pages 133-151, January.
    • Handle: RePEc:mes:emfitr:v:51:y:2015:i:s1:p:s133-s151
    DOI: 10.1080/1540496X.2014.998887
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    Cited by:

    1. Khushalani, Jaya & Ozcan, Yasar A., 2017. "Are hospitals producing quality care efficiently? An analysis using Dynamic Network Data Envelopment Analysis (DEA)," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 15-23.
    2. Yung‐ho Chiu & Tai‐Yu Lin & Tzu‐Han Chang & Yi‐Nuo Lin & Shih‐Yung Chiu, 2021. "Prevaluating efficiency gains from potential mergers and acquisitions in the financial industry with the Resample Past–Present–Future data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 369-384, March.
    3. Gulati, Rachita & Charles, Vincent & Hassan, M. Kabir & Kumar, Sunil, 2023. "COVID-19 crisis and the efficiency of Indian banks: Have they weathered the storm?," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    4. Jamal Ouenniche & Skarleth Carrales, 2018. "Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback," Annals of Operations Research, Springer, vol. 266(1), pages 551-587, July.
    5. Huang, Tai-Hsin & Lin, Chung-I & Wu, Ruei-Cian, 2019. "Assessing the marketing and investment efficiency of Taiwan’s life insurance firms under network structures," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 132-147.
    6. Mohamed Dia & Amirmohsen Golmohammadi & Pawoumodom M. Takouda, 2020. "Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA," JRFM, MDPI, vol. 13(4), pages 1-25, April.
    7. Yu, Ming-Miin & Lin, Chung-I & Chen, Kuan-Chen & Chen, Li-Hsueh, 2021. "Measuring Taiwanese bank performance: A two-system dynamic network data envelopment analysis approach," Omega, Elsevier, vol. 98(C).
    8. Pooja Bansal & Aparna Mehra & Sunil Kumar, 2022. "Dynamic Metafrontier Malmquist–Luenberger Productivity Index in Network DEA: An Application to Banking Data," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 297-324, January.
    9. Ying Li & Yung‐ho Chiu & Ying Yu Chen & Lihua Wang & Yi‐Nuo Lin & Su‐Wan Wang, 2022. "The impact of market share on efficiency of commercial banks: Resampling slacks‐based measure data envelopment analyses model," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(5), pages 1621-1634, July.
    10. Li‐Ting Yeh & Dong‐Shang Chang & Huei‐Min Li, 2022. "Developing a network data envelopment analysis model to measure the efficiency of banking with the governance, innovation, and operations," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2863-2874, October.
    11. Juhi Gupta & Payal Rathore & Smita Kashiramka, 2023. "Impact of Intellectual Capital on the Financial Performance of Innovation-Driven Pharmaceutical Firms: Empirical Evidence from India," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1052-1076, June.

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