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How financial technology (fintech) can improve the business performance of securities firms by using the dynamic data envelopment analysis modified model

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  • Hong‐Jing Lin
  • Che‐Chien Chen
  • Yung‐ho Chiu
  • Tai‐Yu Lin

Abstract

Past literature is lack of consideration on financial technology (fintech) and undesirable output. We aim to understand the reasons underlying the operating performance of fintech in these securities firms and provide suggestions to them for promoting this growing technology phenomenon. This research employs the modified dynamic slacks‐based measurement (SBM) model to explore the electronic transaction efficiency of 38 securities firms in Taiwan. The research results show that most integrated and specialist securities firms fail to achieve the best efficiency in fintech operating performance, and large‐ and medium‐sized integrated securities firms do not achieve economies of scale.

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  • Hong‐Jing Lin & Che‐Chien Chen & Yung‐ho Chiu & Tai‐Yu Lin, 2022. "How financial technology (fintech) can improve the business performance of securities firms by using the dynamic data envelopment analysis modified model," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(4), pages 1113-1132, June.
    • Handle: RePEc:wly:mgtdec:v:43:y:2022:i:4:p:1113-1132
    DOI: 10.1002/mde.3443
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    References listed on IDEAS

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    1. Hirofumi Fukuyama & William Weber, 2015. "Measuring Japanese bank performance: a dynamic network DEA approach," Journal of Productivity Analysis, Springer, vol. 44(3), pages 249-264, December.
    2. Laurent Botti & Sabri Boubaker & Amal Hamrouni & Bernardin Solonandrasana, 2014. "Corporate governance efficiency and internet financial reporting quality," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 13(1), pages 43-64, February.
    3. Ruiyue Lin & Zhiping Chen & Qianhui Hu & Zongxin Li, 2017. "Dynamic network DEA approach with diversification to multi-period performance evaluation of funds," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 821-860, July.
    4. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    5. Hirofumi Fukuyama & William L. Weber, 2017. "Measuring bank performance with a dynamic network Luenberger indicator," Annals of Operations Research, Springer, vol. 250(1), pages 85-104, March.
    6. Sepideh Kaffash & Marianna Marra, 2017. "Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds," Annals of Operations Research, Springer, vol. 253(1), pages 307-344, June.
    7. Muhammad Imran Qureshi & Adeela Rustam & Sehrish Rustam & Abdullah Bin Umar & Khalid Zaman, 2012. "Measuring Bank Branch Performance in Pakistan: Data Envelopment Analysis (DEA)," Oeconomics of Knowledge, Saphira Publishing House, vol. 4(4), pages 25-40, October.
    8. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    9. Chih-Cheng Chen, 2015. "Assessing the Activeness of Online Economic Activity of Taiwan’s Internet Users: An Application of the Super-Efficiency Data Envelopment Analysis Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 433-451, June.
    10. Wanke, Peter & Abul Kalam Azad, Md & Emrouznejad, Ali & Antunes, Jorge, 2019. "A dynamic network DEA model for accounting and financial indicators: A case of efficiency in MENA banking," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 52-68.
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    1. Pampurini, Francesca & Pezzola, Annagiulia & Quaranta, Anna Grazia, 2024. "Lending business models and FinTechs efficiency," Finance Research Letters, Elsevier, vol. 65(C).

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