銀行業受Fin-Tech的影響日益增加，加上少子化、微利化的衝擊，如何引進機器人並增加應用面向，已成為重要課題。本研究主要以科技接受模式（TAM）為研究架構，加入便利性及娛樂性兩個構面探討銀行行員與機器人協同工作的態度與配合意願，並分析可能的影響因素。調查對象為五家銀行行員，以問卷調查方式蒐集102份有效問卷，並以Smart PLS方法驗證模型。
調查結果顯示，原始TAM中的知覺有用性，對銀行行員與機器人協同工作的使用態度有顯著影響，並間接影響行為意向；知覺易用性對知覺有用性有顯著影響，而對使用態度則無顯著影響。另加入便利性及娛樂性的外部變數，則對知覺有用性及知覺易用性皆有顯著的影響。
總結來說，銀行行員對與機器人進行協同工作的使用意願顯著，而影響其意願的因素有知覺有用性、知覺易用性、便利性及娛樂性。本研究建議未來導入機器人行員時，可強化這些因素，以增加行員的接受意願，並提升其與機器人協同工作的成效。

With the increasing influence of Fin-Tech on the banking industry, coupled with the impact of low birth rate and meager profits, how can robots be introduced and increase the aspects applied have become important issues. This study focuses on TAM as the research framework. Adding convenience and entertainment two aspects to study the attitudes and cooperation intentions of bankers for them co-working with robots and analyze possible influencing factors. The survey targets are bank members from five different banks, collecting 102 valid questionnaires, and verified the model by Smart PLS.
The results show the usefulness of the perception in the original TAM, having a significant impact on the working attitudes of the bank staff by co-working with robots, and indirectly affects the behavioral intention; perceived ease of use has a significant impact on the perceived usefulness, while the attitude of the usage has no significant effect. Moreover, the addition external variables of convenience and entertainment have a significant impact on perceived usefulness and perceived ease of use.
In summary, bank members' willingness to co-work with robots is significant, and the factors that affect their willingness are perceived usefulness, perceived ease of use, convenience and entertainment. This study suggests that these factors should be enhanced in the future when introducing robot bank staffs so as to increase the willingness of bank members to accept and enhance the effectiveness of collaborative work with robots.

Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of marketing, 66(3), 1-17.
Bollen, K. A., & Stine, R. A. (1992). Bootstrapping Goodness-of-Fit Measures in Structural Equation Models. Sociological Methods & Research, 21(2), 205-229.
Chin, W. W. (1998). Issues and opinion on structural equation modeling. Management Information Systems Quarterly, 22(1), 7-16.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189-217.
Chin, W. W., & Newsted, P. R. (1999). Structural Equation Modeling Analysis with Small Samples Using Partial Least Squares. In R. Hoyle (Ed.), Statistical Strategies for Small Sample Research (pp. 307- 341). Thousand Oaks, CA: Sage Publications.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and results. (Ph, D. Ph, D.), Massachusetts Institute of Technology Cambridge, MA.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 382-388.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). Upper Saddle River, NJ: Prentice-Hall.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20(2), 195-204.
Manyika, J., & Bughin, J. (2017). Harnessing automation for a future that works. Retrieved from https://www.mckinsey.com/global-themes/digital-disruption/harnessing-automation-for-a-future-that-works
Mariano, J. (2016). Wall Street bank branches are evolving … and shrinking. Retrieved from http://www.msn.com/en-us/money/markets/wall-street-bank-branches-are-evolving-and-shrinking/ar-BBs4JMn?ocid=spartanntp
Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230.
Nunnally, J. (1978). Psychometric methods: New York: McGraw-Hill.
Ross, A. (2016). 未來產業: 天下文化.
王妍文. (2017, 2017/04/27). 「五秒鐘原則」 決定你會不會被機器人取代. 遠見雜誌.
林奇伯. (2017, 2017/01). 真人vs.機器人
當「人機飯碗大戰」成真，你得建立無法取代的價值！. Cheers.
洪新原, 梁定澎, & 張嘉銘. (2005). 科技接受模式之彙總研究. 資訊管理學報, 12(4), 211-234.
彭杏珠. (2014, 2014/09). 萬能好友來了. 遠見雜誌.
鉅亨網. (2016). 月薪逾26K！ 機器人Pepper到這3家金融業上班囉！. Retrieved from https://news.cnyes.com/news/id/3564308
廖君雅. (2016, 2016/03/10). 全台首位機器人行員報到　小ｉ跪坐迎賓. 財訊.
數位時代. (2017). 推廣 Pepper 機器人半年，沛博科技：台灣環境還有很大的進步空間. Retrieved from https://technews.tw/2017/04/27/pepper-robot-to-promote-six-months-the-taiwan-environment-needs-more-progress/
蔡齡瑤. (2016). 結合 Pepper 打造金融新服務.
蕭軒. (2017). 欠缺感受溫度 機器無法取代人工. Retrieved from https://www.epochtimes.com.tw/n226544/%E6%AC%A0%E7%BC%BA%E6%84%9F%E5%8F%97%E6%BA%AB%E5%BA%A6-%E6%A9%9F%E5%99%A8%E7%84%A1%E6%B3%95%E5%8F%96%E4%BB%A3%E4%BA%BA%E5%B7%A5.html
賴子歆. (2015). 服務型機器人爆發成長 台灣豈能錯過良機. Retrieved from http://www.tairoa.org.tw/column/column.aspx?column_id=2222&column_type_id=7
藍弋丰. (2016). 美國銀行業紛紛縮減分行規模，數位服務取代人力 [Press release]. Retrieved from http://finance.technews.tw/2016/05/06/us-banks-reduced-the-size-of-branches-digital-substituted-service-personnel/
顏理謙. (2015, 2015/02/05). 日銀行引進人型機器人，會說19國語言. 數位時代.