| 研究生: |
劉泇甫 Liu, Jia-Fu |
|---|---|
| 論文名稱: |
以科技接受模式探討消費者網路購買旅遊平安險之行為---以訊息框架為調節因子 Exploring the behavior of consumers online purchasing travel insurance by Technology Acceptance Model: The moderation effect of Message Framing |
| 指導教授: |
黃瀞瑩
Huang, Ching-Ying |
| 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: | 58 |
| 中文關鍵詞: | 科技接受模式 、資訊豐富度 、訊息框架 、旅遊平安險 |
| 外文關鍵詞: | TAM, Information Richness, Message Framing, Travel Insurance |
| 相關次數: | 點閱:113 下載:18 |
| 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 |
近年來,隨著電子商務發展,台灣民眾的消費型態逐漸改變,消費者開始重視購物的即時性與便利性,透過網路完成瀏覽、比較與購買產品,網路購物對消費者的重要性日益增加。除此之外,台灣旅遊人數迅速成長,其中不論為國內旅遊或出國旅遊,皆超過七成的人以純觀光旅遊為目的,由此可見旅遊風氣之盛行。隨著旅遊人數增加,旅遊平安險的需求也大幅提升。綜合以上觀點,未來網路購買旅遊平安險將有更大的市場。
在實證部份,本研究以修正後科技接受模型探討網路購買旅遊平安險之行為,並以訊息框架為調解因子。探討「資訊豐富度」、「認知有用性」、「認知易用性」、「購買意圖」與「購買行為」之間的關係,共蒐集240份問卷,其中232份為有效問卷,經由因素分析、架構分析與迴歸分析探討變數對網路購買旅遊平安險購買行為之影響。
本研究結論為網路之資訊豐富度顯著正向影響購買意圖,網路提供豐富之旅遊平安險資訊使得消費者有更高的購買意圖。消費者之認知有用性與認知易用性顯著正向影響購買意圖,消費者之購買意圖顯著正向影響購買行為,顯示消費者認為網路購買旅遊平安險是有用且容易使用的。訊息框架在購買意圖與購買行為之間具有顯著正向的調節效果,旅遊平安險之廣告訊息使得消費者有更高的購買意圖。研究貢獻為首次將資訊豐富度與訊息框架整合修正後科技接受模型探討網路購買旅遊平安險之行為,可以作為日後探討網路投保之依據。在管理上的貢獻,為保險公司提供目前消費者對於網路購買旅遊平安險之行為分析,可以透過增加廣告訊息提升消費者購買意願。
In recent years, technology develops fast. Online-shopping also grows rapidly. Moreover, the number of people travelling abroad increases year after year. People enjoy travelling. Therefore, the demand for travel insurance increases. Technology Acceptance Model (TAM) has been widely used for predicting the acceptance and use of information technologies and online-shopping. The research focuses on adjusted TAM and exploring the behavior of consumers purchasing travel insurance online. In the empirical part, the research would explore which key factors will affect the behavior of consumers online purchasing travel insurance. In addition, it explores whether the positive and negative advertising messages would affect the behavior of consumers online purchasing travel insurance.
The research collected 240 questionnaires, 232 of which were valid. It explored the relation among Information Richness, Perceived Usefulness, Perceived Ease of Use, Purchase Intention, Purchase Behavior and Message Framing. The variables were analyzed with descriptive statistical analysis, factor analysis, confirmatory factor analysis, reliability analysis, validity analysis, structure analysis and regression analysis.
The results of the research are Information Richness has significantly positive effect on Purchase Intention. More information the Internet provides, the higher Purchase Intention consumers have. Perceived Usefulness and Perceived Ease of Use have significantly positive effect on Purchase Intention. In addition, Purchase Intention has significantly positive effect on Purchase Behavior. It means that consumers believe online purchasing travel insurance is useful and easy. Message Framing has significantly positive moderating effect. Advertising messages of travel insurance let consumers have higher Purchase Intention.
中文文獻
金融監督管理委員會
莊惠婷. (2004). 知覺風險對線上購物意願之影響-以女性消費者為例. 碩士論文, 國立臺北大學企業管理學系, 台北.
吳政怡. (2007). 網路投保行為分析. 國立中央大學財務金融學系碩士論文.
朱國明. (2008). 以網路的資訊豐富環境與訊息框架探討網路購物行為之前因與後果模型研究. 中國管理評論國際學報.
蕭銘雄 & 鄭曉平. (2008). 以延伸式科技接受模型探討消費者線上投保人壽保險之意願. 電子商務學報, 10(1), 1-25.
吳亞馨, 朱素玥, & 方文昌. (2008). 網路購物信任與科技接受模式之實證研究. 資訊管理學報, 頁, 123-152.
劉柏村. (2016). 網路投保法制之研究. 臺灣大學科際整合法律學研究所學位論文, 1-152.
英文文獻
Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & management, 44(3), 263-275.
Bosnjak, M., Obermeier, D., & Tuten, T. L. (2006). Predicting and explaining the propensity to bid in online auctions: a comparison of two action‐theoretical models. Journal of Consumer Behaviour, 5(2), 102-116.
Chin, W. W., & Todd, P. A. (1995). On the use, usefulness, and ease of use of structural equation modeling in MIS research: a note of caution. MIS quarterly, 237-246.
Chen, L. D., & Tan, J. (2004). Technology Adaptation in E-commerce:: Key Determinants of Virtual Stores Acceptance. European Management Journal, 22(1), 74-86.
Cheema, U., Rizwan, M., Jalal, R., Durrani, F., & Sohail, N. (2013). The trend of online shopping in 21st century: Impact of enjoyment in TAM Model. Asian Journal of Empirical Research, 3(2), 131-141.
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.
Daft, R. L., & Lengel, R. H. (1984). Information Richness: A New Approach to Manage Information Processing and Organizational Design. Research on Organizational Behavior, Greenwich, CT: JAI. and (1986)," Organizational Information Requirements, Media Richness and Structural Design," Management Science, 13(5), 554-571.
Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management science, 32(5), 554-571.
Daft, R., & Griffin, R. (1986). Organizations as Information Processing Systems. TEXAS A AND M UNIV COLLEGE STATION DEPT OF MANAGEMENT.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology).
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
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.
Gilly, M. C., Graham, J. L., Wolfinbarger, M. F., & Yale, L. J. (1998). A dyadic study of interpersonal information search. Journal of the Academy of Marketing Science, 26(2), 83-100.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 27(1), 51-90.
Guritno, S., & Siringoringo, H. (2013). Perceived usefulness, ease of use, and attitude towards online shopping usefulness towards online airlines ticket purchase. Procedia-Social and Behavioral Sciences, 81, 212-216.
Hurme, P. (2005). Mobile communication and work practices in knowledge-based organizations. Human Technology: An Interdisciplinary Journal on Humans in ICT Environments.
Hsu, C. L., Chuan-Chuan Lin, J., & Chiang, H. S. (2013). The effects of blogger recommendations on customers’ online shopping intentions. Internet Research, 23(1), 69-88.
Krishnamurthy, P., Carter, P., & Blair, E. (2001). Attribute framing and goal framing effects in health decisions. Organizational behavior and human decision processes, 85(2), 382-399.
Kim, J. B. (2012). An empirical study on consumer first purchase intention in online shopping: integrating initial trust and TAM. Electronic Commerce Research, 12(2), 125-150.
Levin, I. P., & Gaeth, G. J. (1988). How consumers are affected by the framing of attribute information before and after consuming the product. Journal of consumer research, 15(3), 374-378.
Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational behavior and human decision processes, 76(2), 149-188.
Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of marketing, 70(3), 74-89.
Meyerowitz, B. E., & Chaiken, S. (1987). The effect of message framing on breast self-examination attitudes, intentions, and behavior. Journal of personality and social psychology, 52(3), 500.
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230.
Moshrefjavadi, M. H., Dolatabadi, H. R., Nourbakhsh, M., Poursaeedi, A., & Asadollahi, A. (2012). An analysis of factors affecting on online shopping behavior of consumers. International Journal of Marketing Studies, 4(5), 81.
Park, C., & Kim, Y. (2008). The effect of information satisfaction and relational benefit on consumer’s online shopping site commitment. Web Technologies for Commerce and Services Online, 1, 149.
Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management science, 42(1), 85-92.
Shiv, B., Edell Britton, J. A., & Payne, J. W. (2004). Does elaboration increase or decrease the effectiveness of negatively versus positively framed messages. Journal of consumer research, 31(1), 199-208.
Senecal, S., & Nantel, J. (2004). The influence of online product recommendations on consumers’ online choices. Journal of retailing, 80(2), 159-169.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. science, 185(4157), 1124-1131.
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453-458.
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 27(3), 451-481.
Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & management, 41(6), 747-762.
Walters, P. G. (2008). Adding value in global B2B supply chains: Strategic directions and the role of the Internet as a driver of competitive advantage. Industrial Marketing Management, 37(1), 59-68.
Wu, L. (2013). The antecedents of customer satisfaction and its link to complaint intentions in online shopping: An integration of justice, technology, and trust. International Journal of Information Management, 33(1), 166-176.
Wu, W. Y., & Ke, C. C. (2015). An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance. Social Behavior and Personality: an international journal, 43(1), 85-97.