博碩士論文 108421007 詳細資訊




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姓名 羅昕薇(Hsin-Wei Lo)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 金融科技公司績效分析
(Performance Measurement of FinTech Company)
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摘要(中) 近年來全球金融科技(FinTech)的發展越發迅速,金融科技公司展現出不錯的成長潛力。而各國政府也紛紛推出相關的政策目標和原則來應對這個趨勢,例如美國於2017年發布《金融科技政策框架》(A Framework for FinTech)白皮書,內容闡述了聯邦政府對於金融科技創新的政策原則及其對該領域發展的態度。基於以上議題,本研究建構了三步驟的整合式模型:第一個步驟是採用動態兩階段網路資料包絡分析法(Dynamic Two-stage Network Data Envelopment Analysis)評估美國上市金融科技公司2015年至2019年整體及技術和營運兩階段的效率表現;第二個步驟是使用衝擊反應函數(Impulse Response Function)探討《金融科技政策框架》白皮書對於公司動態效率的影響;第三個步驟則是運用敏感度分析(Sensitivity Analysis)比較各個變數對效率之影響程度。研究結果顯示,金融科技公司整體效率低下的主因是受到技術效率表現不佳的影響;且政府確實可透過政策的制定和正向的態度促進金融科技產業的發展。本研究之結果不僅可提供金融科技公司管理改善的方向,也能提供政府關於金融科技發展的建議。
摘要(英) In recent years, the global financial technology (FinTech) has developed rapidly, and FinTech companies have shown good growth potential. Governments of various countries have also promulgated relevant policy objectives and principles to respond to this trend. For example, the United States published the "A Framework for FinTech" white paper in 2017, which elaborated on the federal government’s policy principles for FinTech innovation and its attitude towards the development of the field. Based on the above issues, this study constructs a three-step integrated model. The first step is to use Dynamic Two-stage Network Data Envelopment Analysis to evaluate the overall efficiency, technology efficiency and operation efficiency of U.S. public FinTech companies from 2015 to 2019. The second step is to use the Impulse Response Function to explore the impact of the " A Framework for FinTech " white paper on the company’s dynamic efficiency. The third step is to use Sensitivity Analysis to compare the degree of influence of each variable on efficiency. The results show that the main reason for the overall inefficiency of FinTech companies is the poor performance of technology efficiency, and the government can indeed promote the development of the FinTech industry through policy formulation and a positive attitude. The results of this study can not only provide directions for improving the management of FinTech companies, but also provide government suggestions on the development of FinTech.
關鍵字(中) ★ 金融科技
★ 資料包絡分析
★ 績效評估
★ 衝擊反應函數
★ 敏感度分析
關鍵字(英) ★ FinTech
★ Data Envelopment Analysis
★ Performance Measurement
★ Impulse Response Function
★ Sensitivity Analysis
論文目次 摘要 I
Abstract II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 VI
第一章 緒論 1
1-1 研究背景與動機 1
1-2 研究目的 3
1-3 研究流程 4
第二章 文獻探討 5
2-1 金融科技 5
2-2 金融科技相關文獻 6
2-3 金融產業績效評估 10
第三章 研究方法 13
3-1 研究架構 13
3-2 變數說明 14
3-3 研究對象 16
3-4 計量方法 17
3-4-1 動態網路資料包絡分析法 17
3-4-2 衝擊反應函數 21
3-4-3 敏感度分析 22
第四章 實證結果 24
4-1 統計分析 24
4-2 步驟一:效率表現分析 26
4-2-1 整體效率分析 26
4-2-2 技術效率分析 30
4-2-3 營運效率分析 31
4-2-4 兩階段效率比較 33
4-3 步驟二:政策對效率之影響 34
4-4 步驟三:敏感度分析 36
第五章 結論與建議 38
5-1 研究結果 38
5-2 管理意涵 39
5-2-1 學術意涵 39
5-2-2 實務建議 40
5-2-3 公共政策建議 41
5-3 研究限制與未來研究方向 42
參考文獻 43
參考文獻 中文文獻
何偉光 (2016). 迎向金融科技(FinTech)加速創業能量. Available: https://www.taipeiecon.taipei/article_cont.aspx?MmmID=1201&MSid=710375602476350503 (accessed 21.06.15.).
孫遜 (2004). 資料包絡分析法—理論與應用. 台北:揚智文化事業股份有限公司.
顏俊仁、林彥廷、廖國智、簡大翔、郭彥鋒、李清祺 (2018). 金融科技專利關鍵技術研析. 智慧財產權月刊, 232, 22-36.
英文文獻
Andresen, S. (2017). Regulatory and supervisory issues from FinTech. Remarks at the Cambridge Centre for Alternative Finance conference on Navigating the Contours of Alternative Finance, 29 June 2017, Cambridge.
Arias-Oliva, M., Pelegrín-Borondo, J., & Matías-Clavero, G. (2019). Variables influencing cryptocurrency use: a technology acceptance model in spain. Frontiers in Psychology, 10, 475.
Arner, D. W., Barberis, J., & Buckley, R. P. (2016). The evolution of Fintech: A new post-crisis paradigm? Georgetown Journal of International Law, 47, 1271-1319.
Arner, D. W., Buckley, R. P., Zetzsche, D. A., & Veidt, R. (2020). Sustainability, FinTech and financial inclusion. European Business Organization Law Review, 21(1), 7-35.
Axos Financial, Inc. Annual Report (2019). Available: https://www.annualreports.com/HostedData/AnnualReportArchive/a/NYSE_AX_2019.pdf (accessed 21.06.15.).
Bang, H. S., Kang, H. W., Martin, J., & Woo, S. H. (2012). The impact of operational and strategic management on liner shipping efficiency: a two-stage DEA approach. Maritime Policy & Management, 39(7), 653-672.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
Bettinger, A. (1972). Fintech: A series of 40 time shared models used at Manufacturers Hanover Trust Company. Interfaces, 62-63.
Bowlin, W. F. (1998). Measuring performance: An introduction to data envelopment analysis (DEA). The Journal of Cost Analysis, 15(2), 3-27.
Brummer, C., & Yadav, Y. (2019). Fintech and the innovation trilemma. Georgetown Law Journal, 107(2), 235-307.
Bu, Y., Li, H., & Wu, X. (2021). Effective regulations of FinTech innovations: the case of China. Economics of Innovation and New Technology, 1-19.
Cardtronics plc Annual Report (2019). Available: https://ir.cardtronics.com/static-files/0331659a-967c-468d-9ea8-a9a350df0a5f (accessed 21.06.15.).
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
Chen, K. C. (2020). Implications of Fintech Developments for Traditional Banks. International Journal of Economics and Financial Issues, 10(5), 227.
Chen, Z., Li, Y., Wu, Y., & Luo, J. (2017). The transition from traditional banking to mobile internet finance: an organizational innovation perspective-a comparative study of Citibank and ICBC. Financial Innovation, 3(1), 1-16.
Chen, T. H., & Peng, J. L. (2020). Statistical and bibliometric analyses of the effects of financial innovation. Library Hi Tech, 38(2), 308-319.
Cook, W. D., Yang, F., & Zhu, J. (2009). Nonlinear inputs and diminishing marginal value in DEA. Journal of the Operational Research Society, 60(11), 1567-1574.
Cumming, D. J., & Schwienbacher, A. (2018). Fintech venture capital. Corporate Governance-An International Review, 26(5), 374-389.
Degl′Innocenti, M., Kourtzidis, S. A., Sevic, Z., & Tzeremes, N. G. (2017). Bank productivity growth and convergence in the European Union during the financial crisis. Journal of Banking & Finance, 75, 184-199.
Demir, A., Pesqué-Cela, V., Altunbas, Y., & Murinde, V. (2020). Fintech, financial inclusion and income inequality: a quantile regression approach. The European Journal of Finance, 1-22.
Deng, X., Huang, Z., & Cheng, X. (2019). FinTech and sustainable development: Evidence from China based on P2P data. Sustainability, 11(22), 6434.
Faccia, A., & Cavaliere, L. P. L. (2021). Online Banking in Italy. “Widiba Bank” Case Study, PESTLE and DEA Analysis. Financial Markets, Institutions and Risks, 5(1), 89-97.
Fan, K., Li, H., Jiang, W., Xiao, C., & Yang, Y. (2018). Secure authentication protocol for mobile payment. Tsinghua Science and Technology, 23(5), 610-620.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281.
Feng, F., Wang, B., Zou, Y., & Du, Y. (2013). A New Internet DEA Structure: Measurement of Chinese R&D Innovation Efficiency in High Technology Industry. International Journal of Business and Management, 8(21), 32.
Fernandez-Vazquez, S., Rosillo, R., De La Fuente, D., & Priore, P. (2019). Blockchain in FinTech: A mapping study. Sustainability, 11(22), 6366.
Fukuyama, H., Matousek, R., & Tzeremes, N. G. (2020). A Nerlovian cost inefficiency two-stage DEA model for modeling banks’ production process: Evidence from the Turkish banking system. Omega, 95, 102198.
Fukuyama, H., & Weber, W. L. (2015). Measuring Japanese bank performance: a dynamic network DEA approach. Journal of Productivity Analysis, 44(3), 249-264.
Gabor, D., & Brooks, S. (2017). The digital revolution in financial inclusion: international development in the fintech era. New Political Economy, 22(4), 423-436.
Golany, B., & Roll, Y. (1989). An application procedure for DEA. Omega, 17(3), 237-250.
Gong, X., Wu, X., & Luo, M. (2019). Company performance and environmental efficiency: A case study for shipping enterprises. Transport Policy, 82, 96-106.
Green Dot Corp Annual Report (2019). Available: https://ir.greendot.com/static-files/0731701b-e910-4fdb-a16a-69568415e175 (accessed 21.06.15.).
Gregoriou, G. N., Lusk, E. J., & Halperin, M. (2008). A two-staged benchmarked decision support system using DEA profiles of efficiency. INFOR: Information Systems and Operational Research, 46(3), 177-187.
Gruin, J., & Knaack, P. (2020). Not just another shadow bank: Chinese authoritarian capitalism and the ‘developmental’ promise of digital financial innovation. New political economy, 25(3), 370-387.
Haddad, C., & Hornuf, L. (2019). The emergence of the global fintech market: Economic and technological determinants. Small Business Economics, 53(1), 81-105.
Hasan, M. M., Yajuan, L., & Mahmud, A. (2020). Regional development of China’s inclusive finance through financial technology. SAGE Open, 10(1), 2158244019901252.
Hinson, R., Lensink, R., & Mueller, A. (2019). Transforming agribusiness in developing countries: SDGs and the role of FinTech. Current Opinion in Environmental Sustainability, 41, 1-9.
Hu, Z., Ding, S., Li, S., Chen, L., & Yang, S. (2019). Adoption intention of fintech services for bank users: An empirical examination with an extended technology acceptance model. Symmetry, 11(3), 340.
Hu, W. C., Lai, M. C., & Huang, H. C. (2009). Rating the relative efficiency of financial holding companies in an emerging economy: A multiple DEA approach. Expert Systems with Applications, 36(3), 5592-5599.
Hung, S. W., He, D. S., & Lu, W. M. (2014). Evaluating the dynamic performances of business groups from the carry-over perspective: A case study of Taiwan׳ s semiconductor industry. Omega, 46, 1-10.
Investopedia (2020). Financial Technology–Fintech. Available: https://www.investopedia.com/terms/f/fintech.asp (accessed 21.06.15.).
Izzo, F., Tomnyuk, V., & Varavallo, G. (2020). Intellectual Capital and Company Performance: Evidence from European FinTech Companies. International Business Research, 13(6), 1-34.
Kalra, D. (2019). Overriding FINTECH. 2019 International Conference on Digitization (ICD) (pp. 254-259). IEEE.
Kang, J. (2018). Mobile payment in Fintech environment: trends, security challenges, and services. Human-centric Computing and Information Sciences, 8(1), 1-16.
Kaplan, L. D., Daniel, C., Brown, T. P., Sachs, G. S., & Greenbacker, L. K. D. (2017). The OCC′s Proposed Fintech Charter: If It Walks Like a Bank and Quacks Like a Bank, It′s a Bank. Banking LJ, 134, 192.
Kočišová, K. (2014). The use of credit cards and bank efficiency. E+ M Ekonomie a Managament, 17(1), 121-139.
Kourtzidis, S. A., Matousek, R., & Tzeremes, N. G. (2019). Productivity growth in network models: An application to banking during the financial crisis. Journal of the Operational Research Society, 70(1), 111-124.
Kweh, Q. L., Lu, W. M., Lin, F., & Deng, Y. J. (2021). Impact of research and development tax credits on the innovation and operational efficiencies of Internet of things companies in Taiwan. Annals of Operations Research, 1-25.
Laidroo, L., & Avarmaa, M. (2019). The role of location in FinTech formation. Entrepreneurship & Regional Development, 1-18.
Lakhani, K. R., & Iansiti, M. (2017). The truth about blockchain. Harvard Business Review, 95(1), 119-127.
Lee, J., Ryu, M. H., & Lee, D. (2019). A study on the reciprocal relationship between user perception and retailer perception on platform-based mobile payment service. Journal of Retailing and Consumer Services, 48, 7-15.
Lee, I., & Shin, Y. J. (2018). Fintech: Ecosystem, business models, investment decisions, and challenges. Business Horizons, 61(1), 35-46.
Leong, C., Tan, B., Xiao, X., Tan, F. T. C., & Sun, Y. (2017). Nurturing a FinTech ecosystem: The case of a youth microloan startup in China. International Journal of Information Management, 37(2), 92-97.
Li, J., Li, J., Zhu, X., Yao, Y., & Casu, B. (2020). Risk spillovers between FinTech and traditional financial institutions: Evidence from the US. International Review of Financial Analysis, 71, 101544.
Lim, S. H., Kim, D. J., Hur, Y., & Park, K. (2019). An empirical study of the impacts of perceived security and knowledge on continuous intention to use mobile fintech payment services. International Journal of Human–Computer Interaction, 35(10), 886-898.
Liu, J. S., Lu, L. Y., Lu, W. M., & Lin, B. J. (2013). A survey of DEA applications. Omega, 41(5), 893-902.
Liu, X., Sun, J., Yang, F., & Wu, J. (2020). How ownership structure affects bank deposits and loan efficiencies: an empirical analysis of Chinese commercial banks. Annals of Operations Research, 290(1), 983-1008.
Lu, W. M., Wang, W. K., & Kweh, Q. L. (2014). Intellectual capital and performance in the Chinese life insurance industry. Omega, 42(1), 65-74.
Lu, W. M., Wang, W. K., & Lee, H. L. (2013). The relationship between corporate social responsibility and corporate performance: Evidence from the US semiconductor industry. International Journal of Production Research, 51(19), 5683-5695.
MarketAxess Holdings Inc. Annual Report (2019). Available: https://investor.marketaxess.com/static-files/f422d046-5241-490a-9482-6f624fe8c1b1 (accessed 21.06.15.).
Mehrban, S., Nadeem, M. W., Hussain, M., Ahmed, M. M., Hakeem, O., Saqib, S., ... & Khan, M. A. (2020). Towards Secure FinTech: A Survey, Taxonomy, and Open Research Challenges. IEEE Access, 8, 23391-23406.
Mejia-Escobar, J. C., González-Ruiz, J. D., & Duque-Grisales, E. (2020). Sustainable Financial Products in the Latin America Banking Industry: Current Status and Insights. Sustainability, 12(14), 5648.
Meng, W., Zhu, L., Li, W., Han, J., & Li, Y. (2019). Enhancing the security of FinTech applications with map-based graphical password authentication. Future Generation Computer Systems, 101, 1018-1027.
Mention, A.-L. (2019). The future of fintech. Research-Technology Management, 62(4), 59-63.
Milian, E. Z., Spinola, M. D. M., & de Carvalho, M. M. (2019). Fintechs: A literature review and research agenda. Electronic Commerce Research and Applications, 34, 100833.
National Economic Council (2017). A Framework for FinTech. Available: https://obamawhitehouse.archives.gov/sites/obamawhitehouse.archives.gov/files/documents/A%20Framework%20for%20FinTech%20_FINAL.pdf (accessed 21.06.15.).
Nourani, M., Ting, I. W. K., Lu, W. M., & Kweh, Q. L. (2019). Capital structure and dynamic performance: Evidence from asean-5 banks. The Singapore Economic Review, 64(03), 495-516.
Phan, D. H. B., Narayan, P. K., Rahman, R. E., & Hutabarat, A. R. (2020). Do financial technology firms influence bank performance?. Pacific-Basin Finance Journal, 62, 101210.
PwC (2016). Global FinTech Report. Available: https://www.pwc.co.uk/financial-services/fintech/assets/FinTech-Global-Report2016.pdf (accessed 21.06.15.).
Ryu, H. S. (2018). What makes users willing or hesitant to use Fintech?: the moderating effect of user type. Industrial Management & Data Systems, 118(3), 541-569.
Sales, J., Baybordi, A., Aydenlu, M., & Asaldoost, N. (2015). Measuring the effect of managerial ability on earning quality. Management Science Letters, 5(9), 821-826.
Saltelli, A. (2002). Sensitivity analysis for importance assessment. Risk analysis, 22(3), 579-590.
Say, J., Zhao, H., Agbenyegah, F. S., Nusenu, A. A., Boadi, E. A., & Egbadewoe, S. M. (2020). Regional efficiency disparities in rural and community banks in Ghana: A data envelopment analysis. Journal of Psychology in Africa, 30(3), 249-256.
Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management science, 45(9), 1270-1288.
Senyo, P. K., & Osabutey, E. L. (2020). Unearthing antecedents to financial inclusion through FinTech innovations. Technovation, 98, 102155.
Shim, Y., & Shin, D. H. (2016). Analyzing China’s fintech industry from the perspective of actor–network theory. Telecommunications Policy, 40(2-3), 168-181.
Sims, C. A. (1980). Macroeconomics and reality. Econometrica: journal of the Econometric Society, 1-48.
Temelkov, Z. (2018). Fintech firms opportunity or threat for banks?. International journal of information, Business and Management, 10(1), 137-143.
The Business Research Company (2020). Fintech Global Market Opportunities And Strategies. Available: https://www.thebusinessresearchcompany.com/report/fintech-market (accessed 21.06.15.).
Tone, K., Kweh, Q. L., Lu, W. M., & Ting, I. W. K. (2019). Modeling investments in the dynamic network performance of insurance companies. Omega, 88, 237-247.
Tone, K., & Tsutsui, M. (2010). Dynamic DEA: A slacks-based measure approach. Omega, 38(3-4), 145-156.
Tone, K., & Tsutsui, M. (2014). Dynamic DEA with network structure: A slacks-based measure approach. Omega, 42(1), 124-131.
Tsai, M. C., Cheng, C. H., Nguyen, V. T., & Tsai, M. I. (2020). The Theoretical Relationship between the CCR Model and the Two-Stage DEA Model with an Application in the Efficiency Analysis of the Financial Industry. Symmetry, 12(5), 712.
Tsaur, R. C., Chen, I. F., & Chan, Y. S. (2017). TFT-LCD industry performance analysis and evaluation using GRA and DEA models. International Journal of Production Research, 55(15), 4378-4391.
Ulusoy, S., Batıoğlu, A., & Ovatman, T. (2019). Omni-script: Device independent user interface development for omni-channel fintech applications. Computer Standards & Interfaces, 64, 106-116.
Upton, E. J. (2018). Chartering Fintech: The OCC′s Newest Nonbank Proposal. Geo. Wash. L. Rev., 86(5), 1392-1437.
Visa Annual Report (2019). Available: https://www.annualreports.com/HostedData/AnnualReportArchive/v/NYSE_V_2019.pdf (accessed 21.06.15.).
Wang, Q., Hang, Y., Sun, L., & Zhao, Z. (2016). Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach. Technological Forecasting and Social Change, 112, 254-261.
Wang, K., Huang, W., Wu, J., & Liu, Y. N. (2014). Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA. Omega, 44, 5-20.
Wang, C. N., Luu, Q. C., Nguyen, T. K. L., & Day, J. D. (2019). Assessing bank performance using dynamic SBM model. Mathematics, 7(1), 73.
Wanke, P., Barros, C. P., & Faria, J. R. (2015). Financial distress drivers in Brazilian banks: A dynamic slacks approach. European Journal of Operational Research, 240(1), 258-268.
Wójcik, D. (2020a). Geographies of finance I: Exploring FinTech–Maps and concepts. Progress in Human Geography, 0309132520952865.
Wójcik, D. (2020b). Financial geography II: The impacts of FinTech–Financial sector and centres, regulation and stability, inclusion and governance. Progress in Human Geography, 0309132520959825.
Xu, T. (2018). Can Foreign Capital Participation Enhance Commercial Banks’ Market Efficiency?. Engineering Economics, 29(1), 24-31.
Yang, G. L., Song, Y. Y., Xu, D. L., & Yang, J. B. (2017). Overall Efficiency and its Decomposition in a Two-Stage Network DEA Model. Journal of Management Science and Engineering, 2(3), 161-192.
Yeh, K. H., Deng, R. H., & Kikuchi, H. (2020). Special Issue on FinTech Security and Privacy. Future Generation Computer Systems, 112, 1172-1173.
Zha, Y., Liang, N., Wu, M., & Bian, Y. (2016). Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach. Omega, 60, 60-72.
Zhao, Q., Tsai, P. H., & Wang, J. L. (2019). Improving financial service innovation strategies for enhancing china’s banking industry competitive advantage during the fintech revolution: A Hybrid MCDM model. Sustainability, 11(5), 1419.
Zhou, Z., Amowine, N., & Huang, D. (2018). Quantitative efficiency assessment based on the dynamic slack-based network data envelopment analysis for commercial banks in Ghana. South African Journal of Economic and Management Sciences, 21(1), 1-11.
Zou, W. J., Huang, C. W., Chiu, Y. H., Shen, N., & Wang, S. M. (2016). The dynamic DEA assessment of the intertemporal efficiency and optimal quantity of patent for China’s high-tech industry. Asian Journal of Technology Innovation, 24(3), 378-395.
指導教授 洪秀婉(Shiu-Wan Hung) 審核日期 2021-7-28
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