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題名 影響消費者在投資行為上使用金融科技的因素
Factors Affecting Consumer Adoption of FinTech in Inevstment作者 游舒晴
Yu, Shu-Ching貢獻者 別蓮蒂
游舒晴
Yu, Shu-Ching關鍵詞 金融科技
投資行為日期 2019 上傳時間 7-Aug-2019 17:11:34 (UTC+8) 摘要 第二波數位革命後，以資通訊為核心的數位匯流，正顛覆金融業數百年來的樣貌，透過網路銀行，人們可以隨時隨地享受金融服務，而隨著人工智慧的突破，理財機器人也有了新的進展，然而，卻有消費者始終抗拒金融科技，其中又以年長者居多，因此，本研究針對45-65歲的消費者，從投資行為的角度切入，探討影響使用金融科技的因素。本研究目的有四：一、了解科技接受度對消費者使用意願的影響；二、歸納影響因素並與文獻對照，討論哪些因素呼應過去研究，哪些因素則受到金融科技的產品特質影響，而有所差異；三、探詢影響因素與投資行為的對應關係；四、整理消費者對理專及理財機器人的態度，探討影響因素與使用意願的關聯。深度訪談35位受訪者，回顧文獻並根據紮根理論分析資料後，得出的研究結果可歸納為四大方向：首先，科技接受度會受到認知與說服階段的因素影響，前者包括需求、自願性、行為控制知覺與認知風險；後者則有認知有用性、相容性、可展示性與形象，此外，認知與說服階段的因素會互相影響，舉例來說，受訪者因為工作需要，所以得不斷學習新科技，而科技間的相容性則降低他們學習金融科技的難度。其次，在影響因素方面，共整理出以下七類：替代方式、資訊、方便、即時下單、節省成本、系統、風險與安全感。前五類皆為認知有用性，其中方便又可分為隨時查看、整合與節省時間的方便；系統則為認知易用性，可分為系統穩定度、系統流暢度、學習上的難度、介面的視覺設計與定期更換密碼；而風險與安全感屬於認知階段的因素，提高安全感有助於降低認知風險。接著，在影響因素與投資工具的關係方面，首先在風險態度上，發現風險態度與科技接受度為正相關，此外，風險趨避者交易股票的頻率較低，風險愛好者為追求資本利得，會頻繁交易；而後將投資工具依代理程度與交易頻率分類，發現代理程度低者，為避免受營業員影響，傾向網路下單，且為降低隱私風險，故選擇電腦作為交易載具；而交易頻率高者，需要豐富的理財資訊，所以常透過螢幕較大的電腦看盤。最後，在對理專與理財機器人的態度方面，若受訪者與理專長期互動、建立良好關係，則對理專抱持正面態度，反之，若曾有不好的諮詢經驗：認為理專不夠專業，或有不道德的銷售行為，則對理專抱持負面態度，而負面態度會提升受訪者使用理財機器人的意願。此外，代理程度高的受訪者，因為習慣諮詢後再做投資，所以他們願意使用理財機器人，以獲取更多元的投資資訊；相反的，代理程度低者因為沒有諮詢需求，所以不願意使用理財機器人。整體而言，本研究針對金融科技在投資上的用途，對實務界提出產品設計與行銷方面的建議，而學術上的貢獻，則是透過質化研究方法，重新探討因素間的關係，對影響因素做更細緻的解釋。
After the second wave of the digital revolution, information and communication engineering has fundamentally transformed the finance industry. For instance, people can now asccess financial services without time and geographical limitations via online banking. Also, AI development enhances the application of Robot-advisors. However, some consumers, especially the Elderly, still refuse to use FinTech. With this in mind, this paper aims to understand the factors affecting consumer adoption of FinTech in their investments, with a main focus on 45-65-year-old consumers.The purposes of this research are: 1) to understand how attitudes towards adoption of new information technologies influences consumers’ intention to use FinTech, 2) to identify factors and compare with the existing literature to distinguish which factors remain/differentiate from the literature due to the attributes of FinTech product, 3) to understand the relationship between the research factors and investment behaviors, and 4) to explore consumers’ attitudes towards financial consultants and Robo-advisors to understand the relationship between the research factors and the consumers’ intention to use FinTech. After in-depth interviewing 35 respondents, reviewing the existing literature, and analyzing data with grounded theory, the paper concluded the following findings:1. Acceptance of new information technologies is influenced by the factors in a) knowledge and b) persuasion steps, the former which includes need, voluntariness, perceived behavioral control and perceived risk; the later which includes perceived usefulness, compatibility, result demonstrability and image. In addition, mutual influence exists between factors in knowledge and persuasion steps. For example, respondents need to learn how to use new technologies because of job requirements, and compatibility between the technologies makes them learn FinTech easier.2. Seven research factors are also sorted, namely alternatives; information; convenience; timeliness; cost saving; risk and the sense of safety and system. Alternatives, information, convenience, timeliness and cost saving are perceived usefulness, in which convenience can be sorted as checking the account at any given time, integration of different system and time-saving. System is classified as perceived ease of use which can be sorted as system stability, system smoothness, difficulty of learning, interface design and changing the passwords regularly. Risk and the sense of safety are the factors in the knowledge step, and an increase in sense of safety can help decrease perceived risk.3. There is a positive correlation between risk attitude and the acceptance of new information technologies. In addition, the risk avoiders trade less frequently than the risk seekers do. And then, distinguishing the investment Instruments with the tendency on proxy and the trading frequency, the paper found out that respondents in a lower degree of proxy prefer to trade online in order to avoid the influence from securities specialists, and also by using computers to trade to decrease the risk of privacy. On the other hand, respondents in a high trading frequency prefer to read the financial information needed via large-screen computers.4. If the respondents have built a good relationship with financial consultants, they will have a positive attitude towards financial consultants. On the other hand, if the respondents were unsatisfied with their previous consulting experience, they will have a negative attitude towards financial consultants, thus they will be more willing to use Robo-advisor. In addition, respondents in a high degree of proxy are more willing to use Robo-advisor because they are used to receive advice before investment. On the contrary, the respondents in a low degree of proxy invest without any professional suggestion. As a result, they tend not to use Robo-advisor.According to the above research results, this paper provides the industry with suggestions about product designing and marketing. In terms of academic contribution, this paper also explores the relationship between factors and explains the factors in more detail through qualitative research.參考文獻 朱柔若(譯)(2000)。社會研究方法——質化與量化取向(原作者：W.Lawrence Neuman)。台北市：揚智文化。(原著出版年：1997) pp. 613-619, pp. 789-619。吳芝儀、李奉儒(譯)(1995)。質的評鑑與研究(原作者：Michael Quinn Patton)。新北市：桂冠圖書。(原著出版年：1990) pp. 135-147。吳芝儀、廖梅花(譯)(2001)。質性研究入門：紮根理論研究方法(原作者：Anselm Strauss & Juliet Corbin)。嘉義市：濤石文化。(原著出版年：1998) pp. 210-216。林秀雲(譯)(2013)。社會科學研究方法(原作者：Earl Babbie)。台北市：雙葉書廊。(原著出版年：2013) 。林榮春、邱天佑、林茂雄(2011)。影響網路銀行實際使用行為之研究。顧客滿意學刊，7 (1)，1-22。廖娟(2013)。風險態度測量方法研究。改革與戰略，8(29)，67-69。Ajzen, Icek & Martin Fishbein (1980). Understanding Attitudes and Predicting Social Behavior. New Jersey, America: Prentice Hall.Ajzen, Icek (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.Bass, Frank M. (1969). A new product growth for model consumer durables. Management Science, 15(5), 215-227.Berry, Leonard L. (1995). Relationship marketing of services—growing interest, emerging perspectives. Journal of the Academy of Marketing Science, 23(4), 237-245.Bettman, James R. (1973). Perceived risk and its components: A model and empirical test. Journal of Marketing Research, 10(2), 184-190.Bodie, Zvi & Dwight B. Crane (1997). Personal investing advice, theory, and evidence. Financial Analysts Journal, 53(6), 13-23.Brennan, Michael J. & H. Henry Cao (1997). International portfolio investment flows. The Journal of Finance, 52(5), 1851-1880.Callaghan, Michael, Jannelle McPhail, & O.H.M Yau(1994). Dimensions of a relationship marketing orientation: An empirical exposition. Proceedings of the Seventh Biannual World Marketing Congress, 7(2), 10-65.Chattananon, Apisit & Jirasek Trimetsoontorn (2009). Relationship marketing: A Thai case. International Journal of Emerging Markets, 4(3), 252-274.Cockburn, C. & T.D. Wilson (1996). Business use of the world-wide web. International Journal of Information Management, 16(2), 83-102.Conrad, Clifton F. (1978). A grounded theory of academic Change. Sociology of Education, 51(2),101-112.Crosby, Lawrence A., Kenneth R. Evans, & Deborah Cowles (1990). Relationship quality in services selling: An interpersonal influence perspective. Journal of Marketing, 54(3),68-81.Daft, Richard L. (1978). A dual-core model of organizational innovation. The Academy of Management Journal, 21(2), 193-210.Davis, Fred D., Richard P. Bagozzi, & Paul R. Warshaw (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.Dowling, Grahame R. & Richard Staelin (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21(1), 119-134.Echchakoui, Saïd (2016). Relationship between sales force reputation and customer behavior: Role of experiential value added by sales force. Journal of Retailing and Consumer Services, 28, 54-66.Eichhorn, David, Francis Gupta, & Eric Stubbs (1998). Using constraints to improve the robustness of asset allocation. The Journal of Portfolio Management, 24(3), 41-48.Garbarino, Ellen & Mark S. Johnson (1999). The different roles of satisfaction, trust, and commitment in customer relationships. Journal of Marketing, 63(2), 70-87.Gordon, Michael S., Olivia S. Mitchell, & Marc M. Twinney (1997). Positioning Pensions for the Twenty-First Century. Pennsylvania state, America: University of Pennsylvania Press.Grinblatt, Mark & Matti Keloharju (2000). The investment behavior and performance of various investor types: A study of Finland`s unique data set. Journal of Financial Economics, 55(1), 43-67.Hage, Jerald & Robert Dewar (1973). Elite values versus organizational structure in predicting innovation. Administrative Science Quarterly, 18(3), 279-290.Jarvenpaa, Sirrka & Peter Todd (1996/1997). Consumer reactions to electronic shopping on the world wide web. International Journal of Electronic Commerce, 1(2),59-88.Karahanna, Elena & Detmar W. Straub (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35(4), 237-250.Kent, Daniel, David Hirshleifer, & Avanidhar Subrahmanyam (1998). Investor psychology and security market under- and overreactions. The Journal of Finance, 53(6),1839-1885.Kuisma, Tuire, Tommi Laukkanen, Mika, & Hiltunen (2007). Mapping the reasons for resistance to Internet banking: A means-end approach. International Journal of Information Management, 27(2), 75-85.Lambert, Douglas M., Arun Sharma, & Michael Levy (1997). What information can relationship marketers obtain from customer evaluations of salespeople? Industrial Marketing Management, 26(2), 177-187.Lee, Ming-Chi (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.Leonard-Barton, Dorothy (1988). Implementation characteristics of organizational innovations: Limits and opportunities for management strategies. Communication Research, 15(5), 603-631.Liao, Shaoyi, Yuan Pu Shao, Huaiqing Wang, & Ada Chen (1999). The adoption of virtual banking: An empirical study. International Journal of Information Management, 19(1), 63-74.Liao, Z.& W. K. Wong (2008). The determinants of customer interactions with Internet-enabled e-Banking services. The Journal of the Operational Research Society, 59(9), 1201-1210.Lim, Nena (2003). Consumers’ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2(3), 216-228.Mohammed, A. Al-Sharafi, Ruzaini Abdullah Arshah, Qasim Alajmi, Fadi A. Herzallah, & Yousef A. M. Qasem (2018). Influence of perceived trust on understanding banks’ customers behavior to accept Internet banking service. Indian Journal of Science and Technology, 11(20), 1-9.Moore, Gary C. & Izak Benbasat (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.Morgan, Robert M. & Shelby D. Hunt (1995). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38.Patel, Kiran J. & Hiren J. Patel (2018). Adoption of internet banking services in Gujarat: An extension of TAM with perceived security and social influence. International Journal of Bank Marketing, 36(7),147-169.Rogers, Everett M. (2003). Diffusion of Innovations. New Work, America: Free Press.Román, Sergio (2003). The impact of ethical sales behaviour on customer satisfaction, trust and loyalty to the company: An empirical study in the financial services industry. The Service Industries Journal, 19, 915-939.Sathye, Milind (1999). Adoption of Internet banking by Australian consumers: An empirical investigation. International Journal of Bank Marketing, 17(7), 324-334.Sin, Leo Y.M., Alan C.B. Tse, Oliver H.M. Yau, Raymond P.M. Chow, Jenny S.Y. Lee, & Lorett B.Y. Lau (2005). Relationship marketing orientation: scale development and cross-cultural validation. Journal of Business Research, 58(2), 185-194.Stone, Robert N. & Kjell Gronhaug (1993). Perceived risk: Further considerations for the marketing discipline. European Journal of Marketing, 27(3), 39-50.Tan, Margaret & Thompson S. H. Teo (2000). Factors influencing the adoption of Internet banking. Journal of the Association for Information Systems, 1(7),1-41.Tolba, Ahmed, Iman Seoudi, Hakim Meshriki, & Mina Abdelshahid (2015). Impact of ethical sales behavior, quality and image on customer satisfation and loyalty: Evidence from retail banking in Egypt. International Journal of Management and Marketing Research,8(2), 1-18.Tversky, Amos & Daniel Kahneman (1986). Rational choice and the framing of decisions. Journal of Business,59(4), 251-278.Yousafzai, Shumaila Y., John G Pallister, & Gordon R Foxall (2003). A proposed model of e-trust for electronic banking. Technovation, 23(11), 847-860. 描述 碩士
國立政治大學
企業管理研究所(MBA學位學程)
106363017資料來源 http://thesis.lib.nccu.edu.tw/record/#G0106363017 資料類型 thesis dc.contributor.advisor 別蓮蒂 zh_TW dc.contributor.author (Authors) 游舒晴 zh_TW dc.contributor.author (Authors) Yu, Shu-Ching en_US dc.creator (作者) 游舒晴 zh_TW dc.creator (作者) Yu, Shu-Ching en_US dc.date (日期) 2019 en_US dc.date.accessioned 7-Aug-2019 17:11:34 (UTC+8) - dc.date.available 7-Aug-2019 17:11:34 (UTC+8) - dc.date.issued (上傳時間) 7-Aug-2019 17:11:34 (UTC+8) - dc.identifier (Other Identifiers) G0106363017 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/125057 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 企業管理研究所(MBA學位學程) zh_TW dc.description (描述) 106363017 zh_TW dc.description.abstract (摘要) 第二波數位革命後，以資通訊為核心的數位匯流，正顛覆金融業數百年來的樣貌，透過網路銀行，人們可以隨時隨地享受金融服務，而隨著人工智慧的突破，理財機器人也有了新的進展，然而，卻有消費者始終抗拒金融科技，其中又以年長者居多，因此，本研究針對45-65歲的消費者，從投資行為的角度切入，探討影響使用金融科技的因素。本研究目的有四：一、了解科技接受度對消費者使用意願的影響；二、歸納影響因素並與文獻對照，討論哪些因素呼應過去研究，哪些因素則受到金融科技的產品特質影響，而有所差異；三、探詢影響因素與投資行為的對應關係；四、整理消費者對理專及理財機器人的態度，探討影響因素與使用意願的關聯。深度訪談35位受訪者，回顧文獻並根據紮根理論分析資料後，得出的研究結果可歸納為四大方向：首先，科技接受度會受到認知與說服階段的因素影響，前者包括需求、自願性、行為控制知覺與認知風險；後者則有認知有用性、相容性、可展示性與形象，此外，認知與說服階段的因素會互相影響，舉例來說，受訪者因為工作需要，所以得不斷學習新科技，而科技間的相容性則降低他們學習金融科技的難度。其次，在影響因素方面，共整理出以下七類：替代方式、資訊、方便、即時下單、節省成本、系統、風險與安全感。前五類皆為認知有用性，其中方便又可分為隨時查看、整合與節省時間的方便；系統則為認知易用性，可分為系統穩定度、系統流暢度、學習上的難度、介面的視覺設計與定期更換密碼；而風險與安全感屬於認知階段的因素，提高安全感有助於降低認知風險。接著，在影響因素與投資工具的關係方面，首先在風險態度上，發現風險態度與科技接受度為正相關，此外，風險趨避者交易股票的頻率較低，風險愛好者為追求資本利得，會頻繁交易；而後將投資工具依代理程度與交易頻率分類，發現代理程度低者，為避免受營業員影響，傾向網路下單，且為降低隱私風險，故選擇電腦作為交易載具；而交易頻率高者，需要豐富的理財資訊，所以常透過螢幕較大的電腦看盤。最後，在對理專與理財機器人的態度方面，若受訪者與理專長期互動、建立良好關係，則對理專抱持正面態度，反之，若曾有不好的諮詢經驗：認為理專不夠專業，或有不道德的銷售行為，則對理專抱持負面態度，而負面態度會提升受訪者使用理財機器人的意願。此外，代理程度高的受訪者，因為習慣諮詢後再做投資，所以他們願意使用理財機器人，以獲取更多元的投資資訊；相反的，代理程度低者因為沒有諮詢需求，所以不願意使用理財機器人。整體而言，本研究針對金融科技在投資上的用途，對實務界提出產品設計與行銷方面的建議，而學術上的貢獻，則是透過質化研究方法，重新探討因素間的關係，對影響因素做更細緻的解釋。 zh_TW dc.description.abstract (摘要) After the second wave of the digital revolution, information and communication engineering has fundamentally transformed the finance industry. For instance, people can now asccess financial services without time and geographical limitations via online banking. Also, AI development enhances the application of Robot-advisors. However, some consumers, especially the Elderly, still refuse to use FinTech. With this in mind, this paper aims to understand the factors affecting consumer adoption of FinTech in their investments, with a main focus on 45-65-year-old consumers.The purposes of this research are: 1) to understand how attitudes towards adoption of new information technologies influences consumers’ intention to use FinTech, 2) to identify factors and compare with the existing literature to distinguish which factors remain/differentiate from the literature due to the attributes of FinTech product, 3) to understand the relationship between the research factors and investment behaviors, and 4) to explore consumers’ attitudes towards financial consultants and Robo-advisors to understand the relationship between the research factors and the consumers’ intention to use FinTech. After in-depth interviewing 35 respondents, reviewing the existing literature, and analyzing data with grounded theory, the paper concluded the following findings:1. Acceptance of new information technologies is influenced by the factors in a) knowledge and b) persuasion steps, the former which includes need, voluntariness, perceived behavioral control and perceived risk; the later which includes perceived usefulness, compatibility, result demonstrability and image. In addition, mutual influence exists between factors in knowledge and persuasion steps. For example, respondents need to learn how to use new technologies because of job requirements, and compatibility between the technologies makes them learn FinTech easier.2. Seven research factors are also sorted, namely alternatives; information; convenience; timeliness; cost saving; risk and the sense of safety and system. Alternatives, information, convenience, timeliness and cost saving are perceived usefulness, in which convenience can be sorted as checking the account at any given time, integration of different system and time-saving. System is classified as perceived ease of use which can be sorted as system stability, system smoothness, difficulty of learning, interface design and changing the passwords regularly. Risk and the sense of safety are the factors in the knowledge step, and an increase in sense of safety can help decrease perceived risk.3. There is a positive correlation between risk attitude and the acceptance of new information technologies. In addition, the risk avoiders trade less frequently than the risk seekers do. And then, distinguishing the investment Instruments with the tendency on proxy and the trading frequency, the paper found out that respondents in a lower degree of proxy prefer to trade online in order to avoid the influence from securities specialists, and also by using computers to trade to decrease the risk of privacy. On the other hand, respondents in a high trading frequency prefer to read the financial information needed via large-screen computers.4. If the respondents have built a good relationship with financial consultants, they will have a positive attitude towards financial consultants. On the other hand, if the respondents were unsatisfied with their previous consulting experience, they will have a negative attitude towards financial consultants, thus they will be more willing to use Robo-advisor. In addition, respondents in a high degree of proxy are more willing to use Robo-advisor because they are used to receive advice before investment. On the contrary, the respondents in a low degree of proxy invest without any professional suggestion. As a result, they tend not to use Robo-advisor.According to the above research results, this paper provides the industry with suggestions about product designing and marketing. In terms of academic contribution, this paper also explores the relationship between factors and explains the factors in more detail through qualitative research. en_US dc.description.tableofcontents 第一章 研究動機與目的 1第一節 研究動機 1第二章 研究目的 2一、 科技接受度與風險態度對消費者使用金融科技的影響 3二、 影響消費者使用金融科技的因素 3三、 影響消費者在投資工具上使用金融科技的因素 3四、 影響消費者對理專與理財機器人態度的因素 3第二章 文獻回顧 5第一節 創新採用度 5一、 得知創新的管道 10二、 社會構面：主觀規範與形象 10三、 經濟優勢 11四、 使用能力 11五、 複雜性 11六、 可觀察性 11第二節 認知風險 13一、 財務風險 14二、 績效風險 15三、 個人風險 15四、 隱私風險 15第三節 風險態度 15第四節 理專特質與關係行銷 17第三章 研究方法 22第一節 質化研究方法 22一、 紮根理論 23二、 訪談法 24第二節 研究對象 25一、 抽樣方法 25二、 篩選條件 26三、 問卷回收數與本研究實際分析的個案 30四、 受訪者輪廓 32第三節 資料蒐集流程 40一、 發放網路過篩問卷 41二、 電話訪談 41三、 實地深度訪談 42第四節 資料分析流程 44一、 共同分析：三角測定 45二、 獨立分析：開放性、主軸與選擇性編碼 46第四章 研究結果 48第一節 受訪者輪廓 48一、 性別 48二、 年齡 50三、 職業 51五、 月收入 54第二節 科技接受度與風險態度 54一、 科技接受度 55二、 風險態度 68三、 科技接受度與風險態度的關係 75第三節 使用金融科技與否的因素 78一、 方便 79二、 替代方式 83三、 節省成本 86四、 系統 87五、 風險與安全感 96六、 即時下單 102七、 資訊 104第四節 投資工具的特性 106一、 代理程度 107二、 交易頻率 111第五節 影響不同投資工具使用金融科技與否的因素 116一、 代理程度高：基金與外幣 116二、 交易頻率低：投資股票並以賺取股利為目的 123三、 交易頻率高：頻繁交易股票或期權 126第六節 投資資訊的來源 131一、 個人來源 132二、 公共來源 135三、 商業來源 136第七節 對理專與理財機器人的態度 140一、 受訪者對理專的態度 141二、 受訪者對理財機器人的態度 149三、 願意使用理財機器人的因素 152四、 不願意使用理財機器人的因素 156五、 受訪者對理專與理財機器人態度的關係 161第五章 結論與建議 165第一節 結論 165一、 影響使用金融科技與否的構面與因素 165二、 影響投資行為使用金融科技的因素 167第二節 建議與貢獻 169一、 對實務界的建議 169二、 對學術界的貢獻 170第三節 研究限制與後續研究方向 171一、 樣本同質性限制 171二、 定性研究限制 171三、 投資行為的資料不夠深入 172四、 輔以其他蒐集資料的方法 172《參考文獻》 173《附錄》 180附錄一、網路過篩問卷 180附錄二、深度訪談問題 187附錄三、編碼者間一致性信度 201 zh_TW dc.format.extent 2911110 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0106363017 en_US dc.subject (關鍵詞) 金融科技 zh_TW dc.subject (關鍵詞) 投資行為 zh_TW dc.title (題名) 影響消費者在投資行為上使用金融科技的因素 zh_TW dc.title (題名) Factors Affecting Consumer Adoption of FinTech in Inevstment en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 朱柔若(譯)(2000)。社會研究方法——質化與量化取向(原作者：W.Lawrence Neuman)。台北市：揚智文化。(原著出版年：1997) pp. 613-619, pp. 789-619。吳芝儀、李奉儒(譯)(1995)。質的評鑑與研究(原作者：Michael Quinn Patton)。新北市：桂冠圖書。(原著出版年：1990) pp. 135-147。吳芝儀、廖梅花(譯)(2001)。質性研究入門：紮根理論研究方法(原作者：Anselm Strauss & Juliet Corbin)。嘉義市：濤石文化。(原著出版年：1998) pp. 210-216。林秀雲(譯)(2013)。社會科學研究方法(原作者：Earl Babbie)。台北市：雙葉書廊。(原著出版年：2013) 。林榮春、邱天佑、林茂雄(2011)。影響網路銀行實際使用行為之研究。顧客滿意學刊，7 (1)，1-22。廖娟(2013)。風險態度測量方法研究。改革與戰略，8(29)，67-69。Ajzen, Icek & Martin Fishbein (1980). Understanding Attitudes and Predicting Social Behavior. New Jersey, America: Prentice Hall.Ajzen, Icek (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.Bass, Frank M. (1969). A new product growth for model consumer durables. Management Science, 15(5), 215-227.Berry, Leonard L. (1995). Relationship marketing of services—growing interest, emerging perspectives. Journal of the Academy of Marketing Science, 23(4), 237-245.Bettman, James R. (1973). Perceived risk and its components: A model and empirical test. Journal of Marketing Research, 10(2), 184-190.Bodie, Zvi & Dwight B. Crane (1997). Personal investing advice, theory, and evidence. Financial Analysts Journal, 53(6), 13-23.Brennan, Michael J. & H. Henry Cao (1997). International portfolio investment flows. The Journal of Finance, 52(5), 1851-1880.Callaghan, Michael, Jannelle McPhail, & O.H.M Yau(1994). Dimensions of a relationship marketing orientation: An empirical exposition. Proceedings of the Seventh Biannual World Marketing Congress, 7(2), 10-65.Chattananon, Apisit & Jirasek Trimetsoontorn (2009). Relationship marketing: A Thai case. International Journal of Emerging Markets, 4(3), 252-274.Cockburn, C. & T.D. Wilson (1996). Business use of the world-wide web. International Journal of Information Management, 16(2), 83-102.Conrad, Clifton F. (1978). A grounded theory of academic Change. Sociology of Education, 51(2),101-112.Crosby, Lawrence A., Kenneth R. Evans, & Deborah Cowles (1990). Relationship quality in services selling: An interpersonal influence perspective. Journal of Marketing, 54(3),68-81.Daft, Richard L. (1978). A dual-core model of organizational innovation. The Academy of Management Journal, 21(2), 193-210.Davis, Fred D., Richard P. Bagozzi, & Paul R. Warshaw (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.Dowling, Grahame R. & Richard Staelin (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21(1), 119-134.Echchakoui, Saïd (2016). Relationship between sales force reputation and customer behavior: Role of experiential value added by sales force. Journal of Retailing and Consumer Services, 28, 54-66.Eichhorn, David, Francis Gupta, & Eric Stubbs (1998). Using constraints to improve the robustness of asset allocation. The Journal of Portfolio Management, 24(3), 41-48.Garbarino, Ellen & Mark S. Johnson (1999). The different roles of satisfaction, trust, and commitment in customer relationships. Journal of Marketing, 63(2), 70-87.Gordon, Michael S., Olivia S. Mitchell, & Marc M. Twinney (1997). Positioning Pensions for the Twenty-First Century. Pennsylvania state, America: University of Pennsylvania Press.Grinblatt, Mark & Matti Keloharju (2000). The investment behavior and performance of various investor types: A study of Finland`s unique data set. Journal of Financial Economics, 55(1), 43-67.Hage, Jerald & Robert Dewar (1973). Elite values versus organizational structure in predicting innovation. Administrative Science Quarterly, 18(3), 279-290.Jarvenpaa, Sirrka & Peter Todd (1996/1997). Consumer reactions to electronic shopping on the world wide web. International Journal of Electronic Commerce, 1(2),59-88.Karahanna, Elena & Detmar W. Straub (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35(4), 237-250.Kent, Daniel, David Hirshleifer, & Avanidhar Subrahmanyam (1998). Investor psychology and security market under- and overreactions. The Journal of Finance, 53(6),1839-1885.Kuisma, Tuire, Tommi Laukkanen, Mika, & Hiltunen (2007). Mapping the reasons for resistance to Internet banking: A means-end approach. International Journal of Information Management, 27(2), 75-85.Lambert, Douglas M., Arun Sharma, & Michael Levy (1997). What information can relationship marketers obtain from customer evaluations of salespeople? Industrial Marketing Management, 26(2), 177-187.Lee, Ming-Chi (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.Leonard-Barton, Dorothy (1988). Implementation characteristics of organizational innovations: Limits and opportunities for management strategies. Communication Research, 15(5), 603-631.Liao, Shaoyi, Yuan Pu Shao, Huaiqing Wang, & Ada Chen (1999). The adoption of virtual banking: An empirical study. International Journal of Information Management, 19(1), 63-74.Liao, Z.& W. K. Wong (2008). The determinants of customer interactions with Internet-enabled e-Banking services. The Journal of the Operational Research Society, 59(9), 1201-1210.Lim, Nena (2003). Consumers’ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2(3), 216-228.Mohammed, A. Al-Sharafi, Ruzaini Abdullah Arshah, Qasim Alajmi, Fadi A. Herzallah, & Yousef A. M. Qasem (2018). Influence of perceived trust on understanding banks’ customers behavior to accept Internet banking service. Indian Journal of Science and Technology, 11(20), 1-9.Moore, Gary C. & Izak Benbasat (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.Morgan, Robert M. & Shelby D. Hunt (1995). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38.Patel, Kiran J. & Hiren J. Patel (2018). Adoption of internet banking services in Gujarat: An extension of TAM with perceived security and social influence. International Journal of Bank Marketing, 36(7),147-169.Rogers, Everett M. (2003). Diffusion of Innovations. New Work, America: Free Press.Román, Sergio (2003). The impact of ethical sales behaviour on customer satisfaction, trust and loyalty to the company: An empirical study in the financial services industry. The Service Industries Journal, 19, 915-939.Sathye, Milind (1999). Adoption of Internet banking by Australian consumers: An empirical investigation. International Journal of Bank Marketing, 17(7), 324-334.Sin, Leo Y.M., Alan C.B. Tse, Oliver H.M. Yau, Raymond P.M. Chow, Jenny S.Y. Lee, & Lorett B.Y. Lau (2005). Relationship marketing orientation: scale development and cross-cultural validation. Journal of Business Research, 58(2), 185-194.Stone, Robert N. & Kjell Gronhaug (1993). Perceived risk: Further considerations for the marketing discipline. European Journal of Marketing, 27(3), 39-50.Tan, Margaret & Thompson S. H. Teo (2000). Factors influencing the adoption of Internet banking. Journal of the Association for Information Systems, 1(7),1-41.Tolba, Ahmed, Iman Seoudi, Hakim Meshriki, & Mina Abdelshahid (2015). Impact of ethical sales behavior, quality and image on customer satisfation and loyalty: Evidence from retail banking in Egypt. International Journal of Management and Marketing Research,8(2), 1-18.Tversky, Amos & Daniel Kahneman (1986). Rational choice and the framing of decisions. Journal of Business,59(4), 251-278.Yousafzai, Shumaila Y., John G Pallister, & Gordon R Foxall (2003). A proposed model of e-trust for electronic banking. Technovation, 23(11), 847-860. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU201900174 en_US
