| 研究生: |
王藝臻 Wang, Yi-Jen |
|---|---|
| 論文名稱: |
採用認知改變模式探討社會傳播因素對電子化服務使用者持續使用意圖之影響的縱貫性研究 The Adoption of Cognitive Change Model for Investigating the Effect of Social Contagion Factors on Users’ Intention to Continue to Use Electronic Services : A Longitudinal Study |
| 指導教授: |
王維聰
Wang, Wei-Tsong |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 資訊管理研究所 Institute of Information Management |
| 論文出版年: | 2016 |
| 畢業學年度: | 104 |
| 語文別: | 中文 |
| 論文頁數: | 134 |
| 中文關鍵詞: | 電子化服務 、社會傳播理論 、兩階段認知改變理論模型 、縱貫性研究 、持續使用意圖 |
| 外文關鍵詞: | E-services, Social Contagion Theory, Two Stage Cognitive Change Model, longitudinal study, continue to use |
| 相關次數: | 點閱:159 下載:8 |
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隨著網際網路的迅速發展,網路上各種服務的使用已漸漸成為人們每日必做的例行公事,不管是社群網站或者是非社群網站,這些不斷推陳出新的電子化服務對於經營者來說,如何讓使用者願意使用以及持續使用,是很重要的議題。
社會傳播效果的影響會改變個人對事物的看法,不同於過去的研究,本研究嘗試以社會網路的觀點來探討電子化服務的持續使用意圖。而與社會傳播因素有關的網路結構概念有兩種,分別為「凝聚力」與「結構等價」。使用者在採用電子化服務時會受到與自己身邊較常往來的人所影響或參考比較與自己在社會網路中地位類似的人的使用經驗,進而影響使用者對電子化服務的態度或使用意圖。本研究將以電子化服務為例子來進行實證研究並嘗試採用社會傳播因素結合Bhattacherjee與Premkumar提出的兩階段認知改變理論模型,進行縱貫性研究,了解使用者對於使用電子化服務在採用階段的使用意圖以及採用後階段的持續使用意圖。
研究以問卷發放為研究方法,共收集兩階段問卷,第一階段506份問卷,第二階段302份有效問卷,並以結構方程模式進行資料分析。研究結果顯示,凝聚力對使用者的初始態度雖然沒有顯著的影響,但修改後凝聚力對使用者的修改後態度則有顯著的影響。而修改後結構等價雖然對修改後態度沒有顯著影響,但結構等價則對使用者的初始態度有顯著的影響,且初始態度及修改後態度也分別對使用者的使用意圖及持續使用意圖有顯著的影響。故本研究結果凸顯社會傳播因素為影響使用者使用意圖及持續使用意圖的重要因子。本研究結果彌補過去文獻之不足,並提供電子化服務業者在留住使用者方面相關實務之依據。
Many people now use online services (e-services) every day, and thus service providers are interesting the intentions of users to continue to use these. This study attempts to investigate e-service continued usage intentions through the concept of a social network, with a focus on the contagion effects of “cohesion” and “structural equivalence”. When people use e-services, their attitudes will be influenced by people who are close to them or people who have same social positions as them. This study thus adopts social contagion factors and a two-stage cognitive change model to carry out a longitudinal study of the continued usage intentions of e-services users. By applying a structural equation modeling technique to investigate the proposed model, the hypotheses were empirically validated based on two-stage survey data collected from 302 e-services users. The results indicate that cohesion does not have a significant effect on initial attitude, while modified cohesion does have a significant effect on attitude. In addition, modified structural equivalence does not have a significant effect on modified attitude. In contrast, structural equivalence has a significant effect on initial attitude, initial attitude has a significant effect on the intention to use, and modified attitude has a significant effect on continuance intention. The results show that social contagion factors are important one that will influence the intention to use and continued use of e-services.
中文部分
台灣網路資訊中心(2015)-2015台灣寬頻網路使用調查
Retrieved 2016/1/18, from
http://www.twnic.net.tw/download/200307/20150901e.pdf
邱皓政. (2011). 結構方程模式: LISREL 的理論, 技術與應用. 雙葉書廊.
蕭文龍. (2007). 多變量分析最佳入門實用書 SPSS+ LISREL (SEM). 碁峰資訊服份有限公司, 臺北, 民國九十六年.
英文部分
Al-Maghrabi, T., Dennis, C., & Vaux Halliday, S. (2011). Antecedents of continuance intentions towards e-shopping: the case of Saudi Arabia. Journal of Enterprise Information Management, 24(1), 85-111.
Bagozzi, R. P., & Yi, Y. (1988).On the evaluation of structural equationmodels.Journal of the academy of marketing science, 16(1), 74-94.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 25(3), 351-370.
Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Quarterly, 28(2), 229-254.
Brass, D. J., Butterfield, K. D., & Skaggs, B. C. (1998). Relationships and unethical behavior: A social network perspective. Academy of Management Review, 23(1), 14-31.
Burt, R. S. (1987). Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology, 92(6), 1287-1335.
Burt, R. S., & Uchiyama, T. (1989). The conditional significance of communication for interpersonal influence. In M.Kochen (Ed.), The Small World (pp. 67-87). Norwood, NJ: Ablex.
Casati, F., & Shan, M. C. (2001). Dynamic and adaptive composition of e-services. Information systems, 26(3), 143-163.
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.
Diefenbach, M. A., Weinstein, N. D., & O'Reilly, J. (1993). Scales for assessing perceptions of health hazard susceptibility. Health Education Research, 8(2), 181-192.
Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117-140.
Fishbein, M., & i Ajzen, I.(1975). Belief, Attitude, Intention, and Behaviour: An Introduction to Theory and Research.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Fujimoto, K., Unger, J. B., & Valente, T. W. (2012). A Network Method of Measuring Affiliation‐Based Peer Influence: Assessing the Influences of Teammates’ Smoking on Adolescent Smoking. Child Development, 83(2), 442-451.
Fujimoto, K., & Valente, T. W. (2012). Social network influences on adolescent substance use: Disentangling structural equivalence from cohesion. Social Science & Medicine, 74(12), 1952-1960.
Godes, D., & Mayzlin, D. (2009). Firm-Created Word-of-Mouth Communication: Evidence from a Field Test. Marketing Science, 28(4), 721-739.
Goethals, G. R., & Darley, J. M. (1987). Social comparison theory: Self-evaluation and group life. In Theories of Group Behavior (pp. 21-47). Springer New York.
Goldenberg, J., Han, S., Lehmann, D. R., & Hong, J. W. (2009). The Role of Hubs in the Adoption Processes. Journal of Marketing, 73(2).
Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010).Multivariate Data Analysis. Upper Saddle River, NJ: Pearson Education.
Hassanein, K., & Head, M. (2007). Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping.International Journal of Human-Computer Studies, 65(8), 689-708.
He, W., & Wei, K. K. (2009). What drives continued knowledge sharing? An investigation of knowledge-contribution and-seeking beliefs. Decision Support Systems, 46(4), 826-838.
Hinz, O., Schulze, C., & Takac, C. (2012). New product adoption in social networks: Why direction matters. Journal of Business Research, 67(1), 2836-2844.
Hsu, C. L., Yu, C. C., & Wu, C. C. (2014). Exploring the continuance intention of social networking websites: an empirical research. Information Systems and e-Business Management, 12(2), 139-163.
Hsu, M. H., Yen, C. H., Chiu, C. M., & Chang, C. M. (2006). A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human-Computer Studies, 64(9), 889-904.
Huang, H.-C., Shih, H.-Y., & Wu, Y.-C. (2011). Contagion effects of national innovative capacity: Comparing structural equivalence and cohesion models. Technological Forecasting and Social Change, 78(2), 244-255.
Islam, A. K. M. (2012). The Role of Perceived System Quality as Educators’ Motivation to Continue E-learning System Use. AIS Transactions on Human-Computer Interaction, 4(1), 25-43.
Iyengar, R., Van den Bulte, C., & Valente, T. W. (2011). Opinion Leadership and Social Contagion in New Product Diffusion. Marketing Science, 30(2), 195-212.
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.
Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management Science, 51(5), 741-755.
Kim, S. S. (2009). The integrative framework of technology use: an extension and test. MIS Quarterly, 33(3), 513-537.
Kline, R. B. (2010). Principles and Practice of Structural Equation Modeling. New York: The Guilford Press.
Langley, D. J., Bijmolt, T. H. A., Ortt, J. R., & Pals, N. (2012). Determinants of Social Contagion during New Product Adoption. Journal of Product Innovation Management, 29(4), 623-638.
Lankton, N., McKnight, D. H., & Thatcher, J. B. (2014). Incorporating trust-in-technology into Expectation Disconfirmation Theory. The Journal of Strategic Information Systems, 23(2), 128-145.
Lee, J. S., Cho, H., Gay, G., Davidson, B., & Ingraffea, A. R. (2003). Technology acceptance and social networking in distance learning. Educational Technology & Society, 6(2), 50-61.
Leenders, R. T. A. (2002). Modeling social influence through network autocorrelation: constructing the weight matrix. Social Networks, 24(1), 21-47.
Lin, H. F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International Journal of Information Management, 31(3), 252-260.
Lin, K. M., Chen, N. S., & Fang, K. (2011). Understanding e-learning continuance intention: a negative critical incidents perspective. Behaviour & Information Technology, 30(1), 77-89.
Limayem, M., & Cheung, C. M. (2008). Understanding information systems continuance: The case of Internet-based learning technologies. Information & management, 45(4), 227-232.
Lorrain, F., & White, H. C. (1971). Structural equivalence of individuals in social networks. The Journal of Mathematical Sociology, 1(1), 49-80.
Nunnally, J. C., Bernstein, I. H., & Berge, J. M. T. (1967). Psychometric theory(Vol. 226). New York: McGraw-Hill.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.
Petter, S., Straub, D., & Rai, A. (2007). Specifying Formative Constructs in Information Systems Research. MIS Quarterly, 31(4), 623-656.
Rice, R. E., & Aydin, C. (1991). Attitudes toward new organizational technology: Network proximity as a mechanism for social information processing. Administrative Science Quarterly, 36(2), 219-244.
Rogers Everett, M. (1983). Diffusion of innovations. New York: The Free Press.
Shah, P. P. (1998). Who are employees' social referents? Using a network perspective to determine referent others. Academy of Management Journal,41(3), 249-268.
Shih, H.-Y. (2008). Contagion effects of electronic commerce diffusion: Perspective from network analysis of industrial structure. Technological Forecasting and Social Change, 75(1), 78-90.
Sun, H. (2013). A longitudinal study of herd behavior in the adoption and continued use of technology. MIS Quarterly, 37(4), 1013-1041.
Tang, J. T. E., & Chiang, C. H. (2010). Integrating experiential value of blog use into the expectation-confirmation theory model. Social Behavior and Personality: An International Journal, 38(10), 1377-1389.
Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
Venkatesh, V., Thong, J. Y., Chan, F. K., Hu, P. J. H., & Brown, S. A. (2011). Extending the two‐stage information systems continuance model: incorporating UTAUT predictors and the role of context. Information Systems Journal, 21(6), 527-555.
Yen, C. H., & Lu, H. P. (2008). Effects of e-service quality on loyalty intention: an empirical study in online auction. Managing Service Quality: An International Journal, 18(2), 127-146.