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Using Network DEA to Explore the Effect of Mobile Payment on Taiwanese Bank Efficiency

Author

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  • Bao-Ngoc Tong

    (College of Management, National Yunlin University of Science and Technology, Douliu 64002, Taiwan)

  • Cheng-Ping Cheng

    (College of Management, National Yunlin University of Science and Technology, Douliu 64002, Taiwan)

  • Lien-Wen Liang

    (Department of Banking and Finance, Chinese Culture University, Taipei City 11114, Taiwan)

  • Yi-Jun Liu

    (College of Management, National Yunlin University of Science and Technology, Douliu 64002, Taiwan)

Abstract

In order to explore the potential influence of new mobile payment services on the Ephesus model developed by Kao and Hwang (2008), we investigated the relative performance of 19 Taiwanese banks from 2018 to 2021. The network efficiency was divided into two parts: management efficiency and profitability efficiency. Only one bank achieved total efficiency from 2019 to 2021. The stage efficiencies showed increments during the first three years (2018–2020), but they declined in 2021. Most banks had low efficiency in the management stage and high efficiency in the profitability stage, suggesting that there are weaknesses in the management of physical resources but high awareness that mobile payment services can be exploited to achieve high profitability. Our results prove that mobile payment is a potential and profitable new service that Taiwanese banks should take advantage of. Comparing the results between the CCR model and the NDEA model, we observed that the NDEA model has more explanatory power, as it provides insight into the internal structure of the working process of Taiwanese banks.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6344-:d:1117979
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    References listed on IDEAS

    as
    1. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    2. Yao, Meifang & Di, He & Zheng, Xianrong & Xu, Xiaobo, 2018. "Impact of payment technology innovations on the traditional financial industry: A focus on China," Technological Forecasting and Social Change, Elsevier, vol. 135(C), pages 199-207.
    3. 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.
    4. Phung, Manh-Trung & Cheng, Cheng-Ping & Guo, Chuanyin & Kao, Chen-Yu, 2020. "Mixed Network DEA with Shared Resources: A Case of Measuring Performance for Banking Industry," Operations Research Perspectives, Elsevier, vol. 7(C).
    5. M. Humbani & M. Wiese, 2018. "A Cashless Society for All: Determining Consumers’ Readiness to Adopt Mobile Payment Services," Journal of African Business, Taylor & Francis Journals, vol. 19(3), pages 409-429, July.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. 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.
    8. Luo, Xueming, 2003. "Evaluating the profitability and marketability efficiency of large banks: An application of data envelopment analysis," Journal of Business Research, Elsevier, vol. 56(8), pages 627-635, August.
    9. Kawaljeet Kaur Kapoor & Yogesh K. Dwivedi & Michael D. Williams, 2015. "Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service," Information Systems Frontiers, Springer, vol. 17(5), pages 1039-1056, October.
    10. Yang, Chyan & Liu, Hsian-Ming, 2012. "Managerial efficiency in Taiwan bank branches: A network DEA," Economic Modelling, Elsevier, vol. 29(2), pages 450-461.
    11. 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.
    12. Taixing Liu & Beixiao Pan & Zhichao Yin, 2020. "Pandemic, Mobile Payment, and Household Consumption: Micro-Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2378-2389, August.
    13. 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.
    14. 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.
    15. Wu, Yunna & Ke, Yiming & Zhang, Ting & Liu, Fangtong & Wang, Jing, 2018. "Performance efficiency assessment of photovoltaic poverty alleviation projects in China: A three-phase data envelopment analysis model," Energy, Elsevier, vol. 159(C), pages 599-610.
    16. 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.
    17. 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.
    18. Lozano, Sebastián, 2016. "Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector," Omega, Elsevier, vol. 60(C), pages 73-84.
    19. Berger, Allen N. & Hunter, William C. & Timme, Stephen G., 1993. "The efficiency of financial institutions: A review and preview of research past, present and future," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 221-249, April.
    20. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    21. Nicole Koenig-Lewis & Morgan Marquet & Adrian Palmer & Anita Lifen Zhao, 2015. "Enjoyment and social influence: predicting mobile payment adoption," The Service Industries Journal, Taylor & Francis Journals, vol. 35(10), pages 537-554, July.
    22. 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.
    23. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    24. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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