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研究生(外文):Te-yang Lin
論文名稱(外文):The factors of Facebook continuance intention
指導教授(外文):Pei-chen Sun
外文關鍵詞:FacebookContinuance IntentionExpectation Confirmation TheoryIS Success ModelUse & Gratification Theory
  • 被引用被引用:1
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面對市場激烈的競爭,瞭解影響使用者持續使用社群網站的因素能幫助社群網站發展有效策略以留住現有使用者,並能永續經營。本研究目的為探討影響使用者持續使用社群網站的關鍵因素,透過回顧社群網站持續使用的相關文獻,我們根據資訊系統持續使用意願模型,探討資訊系統品質因素與滿足因素對持續使用意願的影響,並檢視哪一因素對社群網站持續使用的影響較為重要。我們針對Facebook使用者進行了線上問卷調查,得到了316份有效問卷,並使用SmartPLS 2.0統計軟體進行分析。研究結果發現使用者滿意度、知覺有用性對持續使用意願有正向影響,期望確認、知覺愉悅性、臉書的滿足娛樂性、臉書的系統品質則是使用者滿意度的前置因素。
Social Network Sites (SNSs) are now facing many competitors in the market. It is crucial for SNSs to retain existing users in order to survive and sustain a long-term operation. The aim of this study is to investigate the key factors influencing the SNSs continuance intention. By reviewing the previous studies of SNS continuance, we propose an integrated model based on Expectance Confirmation Theory and integrate quality factors and gratification factors. We conducted a survey on Facebook users to see whether the proposed model provide better explanation to SNS continuance phenomenon. We collected 316 valid respondents and performed PLS to validate our model, and our findings imply that user satisfaction and perceived usefulness have direct impact on continuance intention, and confirmation of expectation, perceived enjoyment, gratification of entertainment and system quality have consequential effect. The operators of SNSs can improve and develop new function according to our results.
中文摘要 i
英文摘要 iii
目錄 v
表次 vii
圖次 ix
第一章 緒論 1
 第一節 研究背景 1
 第二節 研究動機與目的 3
 第三節 論文架構與研究流程 5
 第四節 研究範圍 7
 第五節 研究對象 8
第二章 文獻探討 9
 第一節 社群網站 9
 第二節 期望確認理論 16
 第三節 資訊系統成功模型 23
 第四節 使用與滿足理論 27
第三章 研究方法 33
 第一節 研究設計 33
 第二節 量表發展 34
 第三節 研究實施程序 38
 第四節 問卷施測與回收 40
第四章 資料分析與討論 41
 第一節 敘述性統計 41
 第二節 測量模型分析 43
 第三節 研究模型檢測與假說驗證 52
第五章 結論與建議 59
 第一節 研究結果與討論 59
 第二節 研究貢獻 63
 第三節 研究限制與未來研究方向 66
參考文獻 69
附錄一:問卷問項 79
表2-1 社群網站持續使用相關文獻整理 12
表2-2 使用與滿足理論相關文獻整理 29
表3-1 構面操作型定義與來源 35
表4-1 受測人口統計變項 42
表4-2 Pearson積差相關分析矩陣 44
表4-3 共線性檢測統計量 45
表4-4 量表構面之信度分析 47
表4-5 量表構面之信效度分析 49
表4-6 區別效度評估表 51
表4-7 本研究模型之路徑係數與假說檢定結果 56
圖1-1美國網路使用者每日使用特定社群網站之平均時間 2
圖1-2 研究流程圖 6
圖1-3 美國網路使用者使用之社群網站排名 8
圖2-1 期望確認理論架構圖 16
圖2-2 資訊系統持續使用意願模型架構圖 18
圖2-3 資訊成功模型研究架構模型 23
圖2-4 修正的資訊成功模型研究架構模型 24
圖2-5 研究架構模型 32
圖3-1 研究實施程序圖 39
圖4-1 研究模型路徑圖 57

Agrifoglio, R., Black, S., Metallo, C., & Ferrara, M. (2012). Extrinsic versus intrinsic motivation in continued twitter usage. The Journal of Computer Information Systems, 53(1), 33-41.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Al-Debei, M. M., Al-Lozi, E., & Papazafeiropoulou, A. (2013). Why people keep coming back to Facebook: Explaining and predicting continuance participation from an extended theory of planned behaviour perspective. Decision Support Systems, 55(1), 43-54.
Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29(5), 530-545.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2), 285-309.
Barnes, S. J., & Böhringer, M. (2011). Modeling use continuance behavior in microblogging services: The case of Twitter. Journal of Computer Information Systems, 51(4), 1-10.
Basak, E. and F. Calisir (2015). An empirical study on factors affecting continuance intention of using Facebook. Computers in Human Behavior, 48: 181-189.
Belsley, D.A., Kuh, E. and Welsch, R.E. (1980). Regression diagnostics, Identifying influential data and sources of collinearity, John Wiley and Sons, New York.
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.
Chang, Y. P., & Zhu, D. H. (2012). The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China. Computers in Human Behavior, 28(3), 995-1001.
Chen, Y. H., Hsu, I., & Lin, C. C. (2010). Website attributes that increase consumer purchase intention: A conjoint analysis. Journal of Business Research, 63(9), 1007-1014.
Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii-xvi.
Chiu, C. M., Cheng, H. L., Huang, H. Y., & Chen, C. F. (2013). Exploring individuals’ subjective well-being and loyalty towards social network sites from the perspective of network externalities: The Facebook case. International Journal of Information Management, 33(3), 539-552.
Chiu, C. M., & Huang, H. Y. (2014). Examining the antecedents of user gratification and its effects on individuals’ social network services usage: the moderating role of habit. European Journal of Information Systems advance online publication, 29 April, doi:10.1057/ejis.2014.9
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95.
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30.
Deng, S., Liu, Y., Li, H., & Hu, F. (2013). How does personality matter? An investigation of the impact of extraversion on individuals' SNS use. Cyberpsychology, Behavior, and Social Networking, 16(8), 575-581.
Dong, T. P., Cheng, N. C., & Wu, Y. C. J. (2014). A study of the social networking website service in digital content industries: The Facebook case in Taiwan. Computers in Human Behavior, 30, 708-714.
Eighmey, J., & Mccord, L. (1998). Adding value in the information age: Uses and gratifications of sites on the World Wide Web. Journal of Business Research, 41(3), 187-194.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook friends: Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143-1168.
eMarketer. Social Network Ad Spending to Hit $23.68 Billion Worldwide in 2015, April 2015 (available online at http://www.emarketer.com/Article/Social-Network-Ad-Spending-Hit-2368-Billion-Worldwide-2015/1012357).
eMarketer. Social Networking Reaches Nearly One in Four Around the World, June 2013 (available online at http://www.emarketer.com/Article/Social-Networking-Reaches-Nearly-One-Four-Around-World/1009976).
eMarketer. Younger Users Spend More Daily Time on Social Networks, November 2014 (available online at http://www.emarketer.com/Article/Younger-Users-Spend-More-Daily-Time-on-Social-Networks/1011592).
Field, A. (2005). Discovering statistics using SPSS (2nd ed.). London: Sage.
Fogel, J., & Nehmad, E. (2009). Internet social network communities: Risk taking, trust, and privacy concerns. Computers in Human Behavior, 25(1), 153-160.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388.
Gwebu, K. L., Wang, J., & Guo, L. (2014). Continued usage intention of multifunctional friend networking services: A test of a dual-process model using Facebook. Decision Support Systems, 67, 66-77.
Hagel, J., & Armstrong, A. (1997). Net gain: Expanding markets through virtual communities. Harvard Business Press.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2009). Multivariate data analysis (7th Edition). Upper Saddle River, NJ: Pearson Prentice Hall.
Hew, K., & Hara, N. (2007). Knowledge sharing in online environments: A qualitative case study. Journal of the American Society for Information Science and Technology, 58(14), 2310-2324.
Hong, S., Thong, J. Y., & Tam, K. Y. (2006). Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decision Support Systems, 42(3), 1819-1834.
Hsu, C. L., & Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45(1), 65-74.
Hsu, M. H., Tien, S. W., Lin, H. C., & Chang, C. M. (2015). Understanding the roles of cultural differences and socio-economic status in social media continuance intention. Information Technology & People, 28(1), 224-241.
Hu, T., Kettinger, W. J., & Poston, R. S. (2014). The effect of online social value on satisfaction and continued use of social media. European Journal of Information Systems advance online publication, 9 September; doi:10.1057/ejis.2014.22
Huang, L. Y., Hsieh, Y. J., & Wu, Y. C. J. (2014). Gratifications and social network service usage: The mediating role of online experience. Information & Management, 51(6), 774-782.
Jin, C. (2013). The perspective of a revised TRAM on social capital building: The case of Facebook usage. Information & Management, 50(4), 162-168.
Kang, Y. S., & Lee, H. (2010). Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction. Computers in Human Behavior, 26(3), 353-364.
Kang, Y. S., Min, J., Kim, J., & Lee, H. (2013). Roles of alternative and self-oriented perspectives in the context of the continued use of social network sites. International Journal of Information Management, 33(3), 496-511.
Katz, E. (1959). Mass communication research and the study of popular culture: An editorial note on a possible future for this journal. Studies in Public Communication, 2, 1-6.
Katz, E., Blumler, J. G., & Gurevitch, M. (1974). User and gratification research. The Public Opinion Quarterly, 37(4), 509-523.
Kim, B. (2011). Understanding antecedents of continuance intention in social-networking services. Cyberpsychology, Behavior, and Social Networking, 14(4), 199-205.
Kim, B., & Han, I. (2009). The role of trust belief and its antecedents in a community‐driven knowledge environment. Journal of the American Society for Information Science and Technology, 60(5), 1012-1026.
Ku, Y. C., Chen, R., & Zhang, H. (2013). Why do users continue using social networking sites? An exploratory study of members in the United States and Taiwan. Information & Management, 50(7), 571-581.
Lee, H., Kim, J., Kim, J. (2007), “Determinants of success for application service provider: An empirical test in small businesses”, International Journal of Human-Computer Studies, 65(9), 796-815.
Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28(2), 331-339.
Li, D. C. (2011). Online social network acceptance: A social perspective. Internet Research, 21(5), 562-580.
Lin, H., Fan, W., & Chau, P. Y. (2014). Determinants of users’ continuance of social networking sites: A self-regulation perspective. Information & Management, 51(5), 595-603.
Luo, X., & Bhattacharya, C. B. (2006). Corporate social responsibility, customer satisfaction, and market value. Journal of marketing, 70(4), 1-18.
Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users’ information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336–355.
Nunnally, J.C. (1978). Psychometric theory, McGraw-Hill Series in Psychology, New York.
Oliver, R. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 50(4), 460-469.
Oliver, R. L., Balakrishnan, P. S., & Barry, B. (1994). Outcome satisfaction in negotiation: A test of expectancy disconfirmation. Organizational Behavior and Human Decision Processes, 60(2), 252-275.
Palmgreen, P., Wenner, L. A., & Rosgengreen, K. E. (1985). Uses and gratifications and research: The past ten years. In K. E. Rosengren (Eds.), Media Gratification Research: Current Perspectives. Beverly Hill, CA: Sage, 11-37
Parasurman, A., Valarie A. Zeithaml, and Leonard L. Berry (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(Fall), 41-50.
Parasuraman, A., Leonard L. Berry, Valarie A. Zeithaml,(1988)., SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64, 12-40
Parthasarathy, M., & Bhattacherjee, A. (1998). Understanding post-adoption behavior in the context of online services. Information Systems Research, 9(4), 362-379.
Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: a measure of information systems effectiveness. MIS Quarterly, 19(2), 173-187.
Rheingold, H. (1993). The virtual community: Finding connection in a computerized world. Addison-Wesley Longman Publishing Co., Inc..
Roseman IJ. (1984) Cognitive determinants of emotion: a structural theory. In Shaver P, ed. Review of personality and social psychology: Emotions, relationships, and health. Beverly Hills, CA: Sage, 11-36.
Rubin, A. M. (1993). Audience activity and media use. Communications Monographs, 60(1), 98-103.
Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication and Society, 3(1), 3-37.
Russell, Martha G. (2009), A call for creativity in new metrics for liquid media, Journal of Interactive Advertising, 9(2), 3-24.
Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240-253.
Shin, D. H. (2010). The effects of trust, security and privacy in social networking: A security-based approach to understand the pattern of adoption. Interacting with Computers, 22(5), 428-438.
van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704
Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5-33.
Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102.
Yoon, C., & Rolland, E. (2015). Understanding continuance use in social networking services. Journal of Computer Information Systems, 55(2) , 1-8.
Zhao, L., & Lu, Y. (2012). Enhancing perceived interactivity through network externalities: An empirical study on micro-blogging service satisfaction and continuance intention. Decision Support Systems, 53(4), 825-834.

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