| 研究生: |
陳冠丞 Chen, Kuan-Cheng |
|---|---|
| 論文名稱: |
探討消費者對於機器人理財之態度與使用意願之研究 An Exploratory Study of Consumer’s Attitude and Intention to Use Robo-Advisor |
| 指導教授: |
莊雙喜
Chuang, Shuang-Shii |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 企業管理學系 Department of Business Administration |
| 論文出版年: | 2018 |
| 畢業學年度: | 106 |
| 語文別: | 中文 |
| 論文頁數: | 82 |
| 中文關鍵詞: | 機器人理財 、態度 、使用意願 、科技接受模型 |
| 外文關鍵詞: | Robo-Advisor, Attitude, Intention to Use, Technology Acceptance Model |
| 相關次數: | 點閱:52 下載:0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
隨著科技的快速進步,各產業皆積極創新服務,以提供更有效率地方式來滿足消費者之需求。在金融業方面,隨著近年來金融科技(FinTech)之發展與推廣,亦提出多種創新服務供消費者使用。本研究主要探討之主題為針對台灣機器人理財之研究,機器人理財是指使用者通過業者推出之自動化、客製化之網路投資平台,對使用者之資料、風險接受程度、所定策略等,利用演算法進行資產配置的一種投資理財方式。透過探討台灣消費者對於機器人理財之態度與使用意願,以幫助企業、政府在台灣推動FinTech與機器人理財相關議題上發展策略。
本研究以科技接受模型為研究架構,並加入知覺相容性、知覺安全性與社會影響力來擴展模型,以多方角度深入探討影響消費者對機器人理財之態度與使用意願之影響。本研究共收集368份有效問卷,並使用結構方程模型(Structural Equation Modelling, SEM)進行資料分析。本研究結果發現,知覺相容性、知覺有效性、知覺易用性、知覺安全性與社會影響力皆會對消費者之態度有顯著影響。而使用態度具有顯著之中介效果,因此在提升消費者對機器人理財之使用意願中扮演一個相當重要的角色。透過提升消費者對機器人理財之正面態度,才能有效地提升其對機器人理財之使用意願。
With the rapid advancement of technology, various industry players are actively innovating services to provide more efficient ways to meet consumer demand. In the financial industry, with the development of financial technology, innovation services have also been proposed for consumer use. Robo-advisor refers to an investment and wealth management method that uses the algorithm to configure assets through the automation, customized network investment platform, user data, risk acceptance, and defined strategy introduced by the industry. The purpose of this research is to explore the factors may affect consumer’s attitude and intention to use and to provide the suggestion for finance company to plan the strategy to promote robo-advisor. The foundation of research framework bases on technology acceptance model. Besides, we add perceived compatibility, perceived security and social influence to use multiple perspectives to deeply explore the impact of consumers' willingness to use the robo-advisor. This study will use structural equation modeling (SEM) for data analysis. The results of the study found that perceived compatibility, perceived usefulness, perceived ease of use, perceived security, and social influence all have a significant impact on consumer attitudes. The attitude has a complete mediating effect and therefore plays an important role in increasing consumers' willingness to use robo-advisor. By enhancing the attitude of consumers, we can effectively increase its willingness to use robo-advisor.
中文文獻
吳萬益(2011),「企業研究方法 (四版) 」,台北:華泰文化事業股份有限公司。
周子敬(2006),「結構方程模式 (SEM)-精通 LISREL」,台北:全華圖書公司。
楊雅婷(2009),「以理性行為理論和科技接受模型來探討消費者對創新科技智慧型手機的購買意願行為之研究」。
歐勁麟(2012),「以科技接受模式探討智慧型手機購買之行為意圖-以 iPhone手機為例」。
英文文獻
Bauer, H. H., Reichardt, T., Barnes, S. J., & Neumann, M. M. (2005). Driving consumer acceptance of mobile marketing: A theoretical framework and empirical study. Journal of electronic commerce research, 6(3), 181.
Bentler, P. M. (1983). Simultaneous equation systems as moment structure models: With an introduction to latent variable models. Journal of econometrics, 22(1-2), 13-42.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 351-370.
Bland, J. M., & Altman, D. G. (1997). Statistics notes: Cronbach's alpha. Bmj, 314(7080), 572.
Cho, Y. H., & Choi, B.-D. (2004). E-government to combat corruption: The case of Seoul metropolitan government. International journal of public administration, 27(10), 719-735.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS quarterly, 13(3), 319-340. doi:10.2307/249008
Devaraj, S., Fan, M., & Kohli, R. (2002). Antecedents of B2C channel satisfaction and preference: validating e-commerce metrics. Information systems research, 13(3), 316-333.
Fein, M. L. (2015). Robo-advisors: A closer look. Browser download this paper.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 27(1), 51-90.
Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the association for information systems, 1(1), 8.
Gliem, J. A., & Gliem, R. R. (2003). Calculating, interpreting, and reporting Cronbach’s alpha reliability coefficient for Likert-type scales.
Hardgrave, B. C., Davis, F. D., & Riemenschneider, C. K. (2003). Investigating determinants of software developers' intentions to follow methodologies. Journal of management information systems, 20(1), 123-151.
Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
Likert, R. (1932). A technique for the measurement of attitudes. Archives of psychology.
Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision support systems, 49(2), 222-234.
Lwin, M., Wirtz, J., & Williams, J. D. (2007). Consumer online privacy concerns and responses: a power–responsibility equilibrium perspective. Journal of the academy of marketing science, 35(4), 572-585.
Lynn, M. R. (1986). Determination and quantification of content validity. Nursing research.
Mackenzie, A. (2015). The fintech revolution. London business school review, 26(3), 50-53.
Mallat, N., Rossi, M., Tuunainen, V. K., & Oorni, A. (2006). The impact of use situation and mobility on the acceptance of mobile ticketing services. Paper presented at the System Sciences, 2006. HICSS'06. Proceedings of the 39th Annual Hawaii International Conference on.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222.
Oh, S., Ahn, J., & Kim, B. (2003). Adoption of broadband Internet in Korea: the role of experience in building attitudes. Journal of information technology, 18(4), 267-280.
Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). ES-QUAL: A multiple-item scale for assessing electronic service quality. Journal of service research, 7(3), 213-233.
Park, J. Y., Ryu, J. P., & Shin, H. J. (2016). Robo Advisors for Portfolio Management. Advanced science and technology letters, 141, 104-108.
Plouffe, C. R., Hulland, J. S., & Vandenbosch, M. (2001). Richness versus parsimony in modeling technology adoption decisions—understanding merchant adoption of a smart card-based payment system. Information systems research, 12(2), 208-222.
Rogers, E. M. (2010). Diffusion of innovations: Simon and Schuster.
Schierz, P. G., Schilke, O., & Wirtz, B. (2009). Understanding Consumer Acceptance of Mobile Payment Services: An Empirical Analysis.
Shen, Y.-C., Huang, C.-Y., Chu, C.-H., & Hsu, C.-T. (2010). A benefit–cost perspective of the consumer adoption of the mobile banking system. Behaviour & information technology, 29(5), 497-511.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE transactions on engineering management(1), 28-45.
Van der Heijden, H. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands. Information & management, 40(6), 541-549.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Wang, Y. S., Lin, H. H., & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information systems journal, 16(2), 157-179.
Webster, J., & Trevino, L. K. (1995). Rational and social theories as complementary explanations of communication media choices: Two policy-capturing studies. Academy of management journal, 38(6), 1544-1572.
校內:2023-06-01公開