網路直播平台近年來於全球各地盛行，資訊呈現方式不再受限於非即時影片、圖片、文字等，任何使用者只要擁有簡單的設備，便能在網路上以現場直播的方式及時將影音資料呈現給全球觀眾。
以往網路媒體平台之學術研究多著重於非即時性影音平台，對於即時性影音平台之研究也僅以少數熱門平台使用者為研究對象，然而近兩年我國在直播平台的使用人數上有顯著成長，甚至有數據顯示，我國在直播產業擁有高達10億商機，因此本研究嘗試以量化方式，全觀性了解國人對網路直播平台的使用行為，藉由初探性的研究，期望能提供未來網路媒體平台新的研究發展面向。
本研究主要探討我國網路直播平台使用者持續使用直播平台之意圖，以IS接受後持續採用模式為基礎架構，結合資訊系統成功模式，並加入娛樂性、互動性等變項，以了解影響使用者持續使用平台之關鍵因素。
研究主要以網路問卷調查法進行研究，共回收286份有效問卷，並使用AMOS 21.0統計軟體進行結構方程式分析資料結果，結果顯示「娛樂性」、「資訊品質」、「系統品質」為影響「知覺有用性」之主要因素；「娛樂性」、「互動性」、「資訊品質」、「系統品質」則是影響「使用者滿意度」之重要因素；而影響「使用者持續使用意圖」之重要因素則是「知覺有用性」。針對上述結果，本研究最終提出幾點網路直播平台營運之實務建議，以期協助直播業者未來發展之參考。

In recent year, video live stream is popular around the world. The way that information present on internet is no longer limited in text, images, non real-time video, etc. Every person is able to make a live show with only simple devices.
Previously, the studies of internet media platform are mostly focus on non real-time video platform. For video live stream, there are only a few cases which is focus on the users in some popular platform. However, in the past two years, the number of users in video live stream platform has a significant growth in our country. Moreover, there is a data said the commercial opportunity of live stream industry is up to 1 billion in our country. So, this study attempts to understand the behavior of the users on video live stream platform by quantitative methods. It hopes to provide a new study orientation in the field of internet media platform.
To explore the continuous intention of the users of video live stream platform, this study create a modified model which is adopted from Post-Acceptance Model of IS Continuance, Information System Success Model, and the factor of interactivity and enjoyment.
Data analysis is conducted via AMOSE 21.0, with 286 valid questionnaires returned. There are three main results. First, the factors of enjoyment, information quality, and system quality have positive effect on the factor of perceived usefulness. Second, the factors of enjoyment, interactivity, information quality, and system quality have positive effect on the factor of user satisfaction. And the final one is that the main effect on the factor of user intention is the factor of perceived usefulness. According to the results mentioned above, this study gives some suggestions in the final part and hopes to provide some idea to live stream industry.

目錄 2
圖目錄 6
表目錄 7
摘要 8
Abstract 9
致謝 10
第一章 緒論 12
1.1. 研究背景與動機 12
表1-1、國人行動上網增長狀況 13
1.2. 研究目的 14
1.3. 研究流程 15
第二章 文獻探討 16
2.1. 網路直播平臺介紹 16
2.1.1.網路直播平台發展 16
2.1.2. 我國網路直播平臺使用現況 17
2.1.3. 網路直播平台商機 19
2.2. 期望確認理論 20
2.2.1. 期望確認理論之基礎構念 20
2.2.2. IS接受後持續採用模式(A Post-Acceptance Model of IS Continuance) 22
2.3. 資訊系統成功模式 23
2.3.1. 資訊系統成功模式之基礎構念 23
2.4. 互動性之探討 24
2.5. 娛樂性之探討 25
第三章 研究方法 27
3.1. 研究架構 27
3.2. 研究模型與操作型定義 28
3.2.1. 娛樂性 28
3.2.2. 互動性 28
3.2.3. 資訊品質 28
3.2.4. 系統品質 29
3.2.5. 確認程度 29
3.2.6.知覺有用性 29
3.2.7. 滿意度 29
3.2.8. 使用者持續使用意圖 30
3.3. 研究假設 31
3.3.1. 娛樂性與滿意度 31
3.3.2. 互動性與滿意度 31
3.3.3. 資訊品質、系統品質與滿意度 31
3.3.4. 確認程度與滿意度 32
3.3.5. 娛樂性與知覺有用性 33
3.3.6. 互動性與知覺有用 33
3.3.7. 資訊品質、系統品質與知覺有用 34
3.3.8. 確認程度與知覺有用 34
3.3.9. 知覺有用與滿意度 35
3.3.10. 知覺有用與持續使用意圖 35
3.3.11. 滿意度與持續使用意圖 36
3.4. 問卷設計 37
表3-1、研究問卷設計 37
3.5. 前測、測量模式分析 41
3.5.1. 個別項目的信度 41
3.5.2. 潛在變項組成信度（Composite Reliability, CR） 42
3.5.3. 收斂效度(Discriminate validity) 42
表3-2、研究模式各變數之信、效度分析表 42
3.5.4. 區別效度 44
表3-3、潛在變項的相關係數矩陣 45
3.6. 研究樣本 45
3.7. 資料蒐集程序 46
3.8. 資料分析方法與工具 46
第四章 資料分析與結果 48
4.1. 敘述性統計分析 48
表4-1、人口統計變數 49
4.2. 結構模式分析 51
表4-2、量測模式評估結果 52
4.3. 假說驗證結果 53
表4-3、本研究之結構分析結果 54
表4-4、研究構面之解釋變異量（R Square值） 55
第五章 結論與建議 56
5.1. 研究結論 56
5.1.1. 知覺有用性之影響因素探討 56
5.1.2. 使用者滿意度之影響因素探討 57
5.1.3. 使用者持續使用意圖之影響因素探討 57
5.2. 理論上之貢獻 58
5.3. 管理意涵 59
5.3.1. 強化平台分眾功能 59
5.3.2. 強化平台內容 59
5.4. 研究限制 60
5.4.1. 樣本對象僅限於台灣地區 60
5.4.2. 僅針對採用後的持續採用因素進行探究 60
5.4.3. 使用者使用之平台類型為區分 60
5.5. 未來研究方向與建議 61
5.5.1. 針對不同國家文化的直播平台使用者進行探討 61
5.5.2. 以縱斷研究方法瞭解影響因素之變化情形 61
5.5.3. 以平台類型區分受訪者 61
第六章 參考文獻 62
6.1. 學術文獻 62
6.2. 網路資料 71

6.1. 學術文獻
1. Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12(2), 125−143.
2. Bailey, J. E. and Person, S. W. (1983). Development of a Tool for Measuring and Analyzing Computer User Satisfaction. Management Science, Vol.29, No.5, pp.519-529.
3. Barua, A., Chellappa, R. and Whinston, A. B. (1995). Creating a Collaboratory in Cyberspace: Theoretical Foundation and an Implementation. Journal of Organizational Computing, Vol.5, No.4, pp.417-442.
4. Bharatia, P. and Chaudhury, A., (2004). An Empirical Investigation of Decision-Making Satisfaction in Web-based Decision Support Systems. Decision Support Systems, Vol.37, No.2, 187–197.
5. Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
6. Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201−214.
7. Bhattacherjee, A., Perols, J., & Sanford, C. (2008). Information technology continuance: a theoretic extension and empirical test. Journal of Computer Information Systems, 49(1), 17-26
8. Caceres, R. C. & Paparoidamis, N. G. (2005). Service quality, relationship satisfaction, trust, commitment and business-to-bussiness loyalty. Journal of European Marketing, 41(7), 836-867.
9. Cardozo, R. N. (1965). An Experimental Study of Consumer Effort, Expectation and Satisfaction. Journal of Marketing Research, Vol. 2, pp.44-249.
10. Chang, C. C. (2004). The interplay of product class knowledge and trial experience in attitude formation. The Journal of Advertising, 33(1), 83−92.
11. Chang, I.-C., Lee, J., & Su, Y. (2011). The Impact of Virtual Community Trust Influence over Consumer Participation in Online Group-Buying. 2011 International Conference, Shanghai, China.
12. Chen, H., Wigand, R. T., and Nilan, M. (1999). Optimal Experience of Web Activities. Computers in Human Behavior, Vol.15, No.5, pp.585-608.
13. Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C. and Sun, P. C. (2005). Usability, Quality, Value and e-Learning Continuance Decisions. Computers & Education, Vol.45, No.4, pp.399-416.
14. Churchill, Jr., G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of Marketing Research, 19(4), 491−504.
15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319−342.
16. Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology (22:14), pp 1111-1132.
17. Davis, F.D., Bagozzi, R.P. and Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, Vol.22, No.14, pp.1111-1132.
18. DeLone, W. H. and McLean, E. R. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, Vol.3, No.1, pp.60-95.
19. Eighmey, J. (1997). Profiling User Responses to Commercial Websites. Journal of Advertising Research (37:3), pp 59-66.
20. Godwin-Jones, R. (2007). Digital video update: YouTube, flash, high-definition: UNIV HAWAII, NATL FOREIGN LANGUAGE RESOURCE CENTER 1859 EAST WEST RD, 106, HONOLULU, HI 96822 USA.
21. Ha, L. and James, E. L. (1998). Interactivity Reexamined: A Baseline Analysis of Early Business Web Sites. Journal of Broadcasting & Electronic Media, Vol.42, No.4, pp.457-474.
22. Hars, A., & Ou, S. (2002). Working for free? Motivations for participating in open-source projects. International Journal of Electronic Commerce, 6(3), 25−39.
23. Hayashi, A., Chen, C., Ryan, T., & Wu, J. (2004). The role of social presence and moderating role of computer self efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15(2), 139−154.
24. Heeter, C. (1989). Implications of New Interactive Technologies for Conceptualizing Communication, In Salvaggio, J. L., and Bryant, J., Media Use in the Information Age: Emerging Patterns of Adoption and Consumer Use. 00.217-235, Hillsdale, N.J.: Lawrence Erlbaum.
25. Hoffman, D. L. and Novak, T. P. (1996). Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations. Journal of Marketing, Vol.60, No.3, pp.50-68.
26. Hong, S., Thong, J. Y. L., & 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.
27. Igbaria, M., Parasuraman, S. and Baroudi, J. J. (1996). A Motivational Model of Microcomputer Usage. Journal of Management Information Systems, Vol.13, No.1, pp.127-143.
28. Iivari, J. and Koskela, E. (1987). The PIOCO Model for Information Systems Design. MIS Quarterly, Vol.11, No.3, pp.401-419.
29. Jin, X.-L., Cheung, C. M. K., Lee, M. K. O., & Chen, H.-P. (2009). How to Keep Members Using the Information in a Computer-Supported Social Network. Computers in Human Behavior. 25(5): 1172-1181.
30. Julian, D. A., Reischl, T. M., Carrick, R. V., & Katrenich, C. (1997). Citizen participation—Lessons from a local united way planning process. Journal of the American Planning Association, 63(3), 345−355.
31. K. Pires and G. Simon. (2015). Youtube live and twitch: a tour of user-generated live streaming systems. In Proc. of ACM MMSys, pages 225–230.
32. Liao, C., Chen, J.-L., & Yen, D. C. (2007). Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: An integrated model. Computers in Human Behavior, 23(6), 2804−2822.
33. Lieberman, N. J. (1997). Playfulness: Its Relationship to Imagination and Creativity. New York: Academic Press.
34. Lin, C. P., & Ding, C. G. (2005). Opening the black box: assessing the mediating mechanism of relationship quality and the moderating effects of prior experience in ISP service. International Journal of Service Industry Management, 16(1), 55-80.
35. Lin, C. S., Wu, S., and Tsai, R. J. (2005). Integrating Perceived Playfulness into Expectation-confirmation Model for Web Portal Context. Inf. Manage, pp 683-693.
36. McGill, T., Hobbs, V. and Kloba, J. (2003). User-Developed Applications and Information Systems Success: a Test of DeLone and McLean’s Model. Information Resources Management Journal, Vol.16, No.1, pp.24–45.
37. McKinney, V., Yoon, K. and Zahedi, F. (2002). The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach. Information Systems Research, Vol.13, No.3, pp.296-315.
38. Moon, J. W. and Kim, Y. G. (2001). Extending the TAM for the World Wide Web Context. Information & Management, Vol.38, No.4, pp.217-230.
39. Nardi, B., Schiano, D. and Gumbrecht, M. (2004). Blogging as Social Activity, or, would you let 900 Million People Read your Diary?. Proceedings of Computer Supported Cooperative Work 2004, Available at－ http://home.comcast.net/%7Ediane.schiano/CSCW04.Blog.pdf
40. Novak, P. T. and Hoffman, D. L. (1997). Measuring the Flow Experience among Web Users. Interval Research Corporation, July 31
41. Novak, P. T., and Hoffman, D. L. and Yung, Y. F. (1998). Modeling the Structure of the Flow Experience among Web Users. Informs Marketing Science and the Internet Mini-Conference, MIT.
42. Oliver, P., Marwell, G., & Teixeira, R. (1985). A theory of the critical mass. I. Interdependence, group heterogeneity, and the production of collective action. American journal of Sociology, 91(3): 522-556.
43. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, (17)4, 460−469.
44. Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418−430.
45. Oliver, R. L., & Bearden, W. O. (1985). Disconfirmation processes and consumer evaluations in product usage. Journal of Business Research, 13(3), 235−246.
46. Olsen S. O. (2002). Comparative Evaluation and the Relationship between Quality, Satisfaction, and Repurchase Loyalty. Journal of the Academy of Marketing Science, Vol.30, No.3, pp.240-249.
47. Rafaeli, S. (1988). Interactivity: From New Media to Communication, in R. Hawkins, J. M. Wiermann, and S. Pingree(Eds.), Advancing Communication Science: Merging Mass and Interpersonal Bervely Hills, CA: Sage, pp.110-134.
48. Rai, A., Lang, S. S., and Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, Vol.13, No.1, pp.50-69.
49. Richmond, A. (1996). Enticing Online Shoppers to Buy-- A Human Behavior Study. Comput. Netw. ISDN Syst. (28:7-11), pp 1469-1480.
50. Roca, J. C., Chiu, C. M. and Martínez, F. J. (2006). Understanding E-learning Continuance Intention: An Extension of the Technology Acceptance Model. International Journal of Human-Computer Studies, Vol.64, No.8, pp.683-696.
51. Ryan, J. (1995). A Uses and Gratifications Study of the Internet Social Interaction Site LambdaMOO: Talking with “Dinos”, Ball State University.
52. Sanchez-Franco, M. J., Ramos, A. F. V., & Velicia, F. A. M. (2009). The moderating effect of gender on relationship quality and loyalty toward Internet service providers. Information & Management, 46(3), 196-202.
53. Seddon, P. B. and Kiew, M. Y. (1994). A Partial Test and Development of the DeLone and McLean Model of IS Success. In Proceedings of the International Conference on Information Systems, pp.99-110, Vancouver, Canada.
54. Seddon, P.B. (1997). A Respecification and Extension of the DeLone and McLean Modelof IS Success. Information Systems Research, 8(3), 240-253.
55. Selnow, G. W. (1988). Using Interactive Computer to Communicate Scientific Information”, American Behavioral Scientist, Vol.32, pp.124-135.
56. Steuer, J. (1992). Defining Virtual Reality: Dimensions Determining Telepresence. Journal of Communication, 42(4), 79-93.
57. Sullivan, J. (1999). What are the Functions of Corporate Home Page?” Journal of World Business, Vol.34, No.2, pp.193-210.
58. Tsai, M.-T., Cheng, N.-C., & Chen, K.-S. (2011). Understanding Online Group Buying Intention: The Roles of Sense of Virtual Community and Technology Acceptance Factors. Total Quality Management & Business Excellence, 22(10): 1091-1104.
59. Tung, L. L. (2004). Service Quality and Perceived Value’s Impact on Satisfaction, Intention and Usage of Short Message Service (SMS)”, Information Systems Frontiers, Vol.6, No.4, pp.353-368.
60. Wang, E.T.G., Fan, Y.-W., Chiang, M.-H., & Wang, J.-Y. (2010). A Study on Consumers’ Continuing to Use Online Group-Buying Platforms. Chinese Business Review, 9(12): 44-52.
61. Webster, J., Trevino, K. L. and Ryan, L. (1993) The Dimensionality and Correlates of Flow in Human-Computer Interactions. Computers in Human Behavior, Vol.9, No.4, pp.411-426.
62. Wu, G. (1999). Perceived Interactivity and Attitude toward Website”, Paper presented at Annual Conference of American Academy of Advertising, FL: University of Florida, pp.254-262.
63. Wu, J. H., Wang, Y.M. (2006). Measuring KMS success: A Respecification of the DeLone and McLean’s Model”, Information & Management, Vol.43, No.6, pp.728-739
64. Yoo, W. S., Suh, K. S., & Lee, M. B. (2002). Exploring the factors enhancing member participation in virtual communities, Journal of Global Information Management, 10(3), 55−71.
65. 吳肇銘(1998)。影響網站使用意向之因素研究－以入門網站為例，中央大學資訊管理學研究所。博士論文。
66. 岳修平(2008)。Web 2.0影音分享平臺之學習應用探討。臺灣圖書館管理季刊，4(3)，9-21。
67. 張簡群哲(2010)。「影響社交網站黏著度因素之研究－以 Facebook 為例」。國立中央大學資訊管理研究所碩士論文。
68. 黃文楷(2007)。探討Blog使用者持續採用行為之研究－以期望確認理論為基礎。國立高雄第一科技大學資訊管理系碩士論文。
69. 魏佑寧(2009)。網站系統與資訊內容對虛擬社群意識影響之研究-以Web 2.0網站為例。國立高雄大學資訊管理學系碩士論文。
70. 程婉婷(2011)。Facebook 粉絲專頁對網路持續使用行為意圖之影響：以使用與滿足理論與社會影響觀點。國立交通大學管理科學系碩士論文。