隨著台灣直播機制的盛行與商機的湧現，直播商務的議題逐漸受到重視並引發熱烈的討論。Facebook直播平台結合電子商務與直播的機制，透過溝通交流可以協助消費者表達意見和想法。因此本研究除了考慮直播平台的特性外，也針對網路使用者或消費者對於直播購物所考量的因素進行研究。
本研究藉由閱讀及彙整相關文獻以發展本研究之架構與假說，基於計畫行為理論探討感知風險 (Perceived Risk)、知覺互動性 (Perceived Interactivity) 對購買態度 (Purchase Attitude) 的影響，並進一步探討購買意圖 (Purchase Intention)、主觀規範 (Subjective Norm) 與知覺行為控制 (Perceived Behavior Control) 之間的關係。
本研究採用線上問卷的方式進行施測並於Facebook和批踢踢實業坊回收總計377份有效問卷，後續則使用SmartPLS 3.0 統計軟體進行分析。研究結果顯示：網路使用者或消費者的知覺互動性對購買態度有正向影響，但其感知風險對購買態度則有負向影響；而購買態度、主觀規範和知覺行為控制對於購買意圖皆有正向的影響。此外，本研究也發現對於有FB直播購物經驗的人而言，主觀規範與購買意圖之間的關係並不顯著；對於沒有FB直播購物經驗的人而言，知覺行為控制與購買意圖之間的關係並不顯著。
最後本研究依據結論提出實務建議，認為業者透過FB直播平台販售產品時應加強與網路使用者或消費者的互動過程並減少風險認知、利用社群媒體與直播的特色與顧客建立良好的關係，使其形成良好的購買態度；其次也得考慮到主觀規範與知覺行為控制會因為網路使用者或消費者的購物經驗而有不同的影響。

As the live streaming gradually prevalent and brings the potential benefits (or business opportunities) in Taiwan, more and more people are also interested in the live streaming commerce. Live streaming can help the consumers to communicate with sales representatives and express their questions or productions expectations. Thus, this study focus on live streaming features and the factors which the online users or consumers will considering when they purchasing by the Facebook live platform.
The conceptual structures and hypotheses were developed by the literature review and collection. This study was based on the Theory of Planned Behavior (TPB) to explore the attitude’s antecedents which included “Perceived Risk” and “Perceived Interactivity”, furthermore discuss the variables’ relationship which contained “Purchase Attitude”, “Subjective Norm”, “Perceived Behavior Control” and “Purchase Intention”.
The data for this study were collected 377 respondents via an online survey. The study results show that Perceived Interactivity has positive effect on Purchase Attitude, Perceived Risk has negative effect on Purchase Attitude comparatively. Purchase Attitude, Subjective Norm and Perceived Behavior Control has positive effect on Purchase Intention. Moreover, this study also found some interesting results. For the online users who already purchased via FB live platform, the influence of Subjective Norm on Purchase Intention was insignificant; for the online users who has not purchase via FB live platform, the influence of Perceived Behavior Control on Purchase Intention was insignificant.
In conclusion, this study suggests enterprises can enhance the consumers’ perception of interactivity and reduce the perception of risk. Through the features of social media and live stream to establish consumers loyalty and sustain positive relationships. Second, enterprises have to consider that “Subjective Norm” and “Perceived Behavior Control” will have different effects to the online users or consumers.

一、 英文文獻
[1] Ajzen, I. (1985). From intentions to actions: A theory of planned behavior Action control (pp. 11-39): Springer.
[2] Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
[3] Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Decision Processes, 50, 179-211.
[4] Ajzen, I. (2002). Perceived behavioral control, self‐efficacy, locus of control, and the theory of planned behavior. Journal of applied social psychology, 32(4), 665-683.
[5] Bauer, R. A. (1960). Consumer behavior as risk taking. Paper presented at the Proceedings of the 43rd National Conference of the American Marketing Assocation, June 15, 16, 17, Chicago, Illinois, 1960.
[6] Benbasat, I., & Barki, H. (2007). Quo vadis TAM? Journal of the Association for Information Systems, 8(4), 7.
[7] Benbasat, I., & Zmud, R. W. (2003). The identity crisis within the IS discipline: Defining and communicating the discipline's core properties. MIS quarterly, 183-194.
[8] Burgoon, J. K., Bonito, J. A., Bengtsson, B., Ramirez Jr, A., Dunbar, N. E., & Miczo, N. (1999). Testing the interactivity model: Communication processes, partner assessments, and the quality of collaborative work. Journal of management information systems, 16(3), 33-56.
[9] Carey James. (1989). International encyclopedia of communications. Interactive media. In: Barnouw Erik, editor. New York: Oxford University Press. 328–330.
[10] Chang, E.-C., & Tseng, Y.-F. (2013). Research note: E-store image, perceived value and perceived risk. Journal of Business Research, 66(7), 864-870.
[11] Chang, M. K. (1998). Predicting unethical behavior: a comparison of the theory of reasoned action and the theory of planned behavior. Journal of Business Ethics, 17(16), 1825-1834.
[12] Chen, Y.-H., & Barnes, S. (2007). Initial trust and online buyer behaviour. Industrial management & data systems, 107(1), 21-36.
[13] Chiu, C. M., Wang, E. T., Fang, Y. H., & Huang, H. Y. (2014). Understanding customers' repeat purchase intentions in B2C e‐commerce: the roles of utilitarian value, hedonic value and perceived risk. Information Systems Journal, 24(1), 85-114.
[14] Chiu, H.-C., Hsieh, Y.-C., & Kao, C.-Y. (2005). Website quality and customer's behavioural intention: an exploratory study of the role of information asymmetry. Total Quality Management and Business Excellence, 16(2), 185-197.
[15] Chung, H., & Zhao, X. (2004). Effects of perceived interactivity on web site preference and memory: Role of personal motivation. Journal of Computer-Mediated Communication, 10(1), JCMC1017.
[16] Churchill Jr, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of marketing research, 64-73.
[17] Cox, D. F. (1967a). Risk handling in consumer behavior-an intensive study of two cases. Risk taking and information handling in consumer behavior, 34-81.
[18] Cox, D. F. (1967b). Risk taking and information handling in consumer behavior.
[19] Crespo, A. H., & Del Bosque, I. R. (2010). The influence of the commercial features of the Internet on the adoption of e-commerce by consumers. Electronic Commerce Research and Applications, 9(6), 562-575.
[20] Crespo, A. H., del Bosque, I. R., & de los Salmones Sanchez, M. G. (2009). The influence of perceived risk on Internet shopping behavior: a multidimensional perspective. Journal of Risk Research, 12(2), 259-277.
[21] Cunningham, M. S. (1967). The major dimensions of perceived risk. Risk taking and information handling in consumer behavior.
[22] Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of consumer research, 21(1), 119-134.
[23] Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474.
[24] Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
[25] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
[26] Fu, J.-R., Ju, P.-H., & Hsu, C.-W. (2015). Understanding why consumers engage in electronic word-of-mouth communication: Perspectives from theory of planned behavior and justice theory. Electronic Commerce Research and Applications, 14(6), 616-630.
[27] Gefen, D., Rao, V. S., & Tractinsky, N. (2003). The conceptualization of trust, risk and their electronic commerce: the need for clarifications. Paper presented at the System Sciences, 2003. Proceedings of the 36th Annual Hawaii International Conference on.
[28] Ghose, S., & Dou, W. (1998). Interactive functions and their impacts on the appeal of Internet presence sites. Journal of advertising research, 38(2), 29-43.
[29] Glover, S., & Benbasat, I. (2010). A comprehensive model of perceived risk of e-commerce transactions. International journal of electronic commerce, 15(2), 47-78.
[30] Goes, P., Ilk, N., Yue, W. T., & Zhao, J. L. (2011). Live-chat agent assignments to heterogeneous e-customers under imperfect classification. ACM Transactions on Management Information Systems (TMIS), 2(4), 24.
[31] Grazioli, S., & Jarvenpaa, S. L. (2000). Perils of Internet fraud: An empirical investigation of deception and trust with experienced Internet consumers. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 30(4), 395-410.
[32] Guo, Z., Tan, F. B., & Cheung, K. (2010). Students' uses and gratifications for using computer-mediated communication media in learning contexts.
[33] Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5): Prentice hall Upper Saddle River, NJ.
[34] Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. The Journal of Marketing, 50-68.
[35] Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust online. Communications of the ACM, 42(4), 80-85.
[36] Hung, S.-Y., Yu, A. P.-I., & Chiu, Y.-C. (2018). Investigating the factors influencing small online vendors’ intention to continue engaging in social commerce. Journal of Organizational Computing and Electronic Commerce, 28(1), 9-30.
[37] Jacoby, J., & Kaplan, L. B. (1972). The components of perceived risk. ACR Special Volumes.
[38] Jarvenpaa, S. L., Tractinsky, N., & Saarinen, L. (1999). Consumer trust in an Internet store: A cross-cultural validation. Journal of Computer-Mediated Communication, 5(2), JCMC526.
[39] Jee, J., & Lee, W.-N. (2002). Antecedents and consequences of perceived interactivity: An exploratory study. Journal of Interactive Advertising, 3(1), 34-45.
[40] Jiang, Z., Chan, J., Tan, B. C., & Chua, W. S. (2010). Effects of interactivity on website involvement and purchase intention. Journal of the Association for Information Systems, 11(1), 34.
[41] Kang, L., Wang, X., Tan, C.-H., & Zhao, J. L. (2014). Understanding the antecedents and consequences of Live-Chat use in e-commerce context. Paper presented at the International Conference on HCI in Business.
[42] Kang, L., Wang, X., Tan, C.-H., & Zhao, J. L. (2015). Understanding the antecedents and consequences of live chat use in electronic markets. Journal of Organizational Computing and Electronic Commerce, 25(2), 117-139.
[43] Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480-1486.
[44] Kim, J., & Lee, K. H. (2013). Towards a theoretical framework of motivations and interactivity for using IPTV. Journal of Business Research, 66(2), 260-264.
[45] Kim, J., & Lee, K. H. (2017). Influence of integration on interactivity in social media luxury brand communities. Journal of Business Research.
[46] Kim, J., Spielmann, N., & McMillan, S. J. (2012). Experience effects on interactivity: Functions, processes, and perceptions. Journal of Business Research, 65(11), 1543-1550.
[47] LaRose, R. (1995). Communications media in the information society: Wadsworth Publ. Co.
[48] Lee, M.-C. (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.
[49] Liao, C., Lin, H.-N., & Liu, Y.-P. (2010). Predicting the use of pirated software: A contingency model integrating perceived risk with the theory of planned behavior. Journal of Business Ethics, 91(2), 237-252.
[50] Lim, N. (2003). Consumers’ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2(3), 216-228.
[51] Lin, W.-B. (2008). Investigation on the model of consumers’ perceived risk—integrated viewpoint. Expert Systems with Applications, 34(2), 977-988.
[52] Liu, Y. (2003). Developing a scale to measure the interactivity of websites. Journal of advertising research, 43(2), 207-216.
[53] Lv, Z., Jin, Y., & Huang, J. (2018). How do sellers use live chat to influence consumer purchase decision in China? Electronic Commerce Research and Applications, 28, 102-113.
[54] 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.
[55] Matteson, M. L., Salamon, J., & Brewster, L. (2011). A systematic review of research on live chat service. Reference & User Services Quarterly, 51(2), 172-189.
[56] McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information systems research, 13(3), 334-359.
[57] McMillan, S. J. (2005). The researchers and the concept: Moving beyond a blind examination of interactivity. Journal of Interactive Advertising, 5(2), 1-4.
[58] McMillan, S. J., & Hwang, J.-S. (2002). Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity. Journal of advertising, 31(3), 29-42.
[59] Mero, J. (2018). The effects of two-way communication and chat service usage on consumer attitudes in the e-commerce retailing sector. Electronic Markets, 1-13.
[60] Miniard, P. W., & Cohen, J. B. (1981). An examination of the Fishbein-Ajzen behavioral-intentions model's concepts and measures. Journal of Experimental Social Psychology, 17(3), 309-339.
[61] Mitchell, V.-W. (2001). Re-conceptualizing consumer store image processing using perceived risk. Journal of Business Research, 54(2), 167-172.
[62] Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. Journal of Consumer affairs, 35(1), 27-44.
[63] Nepomuceno, M. V., Laroche, M., & Richard, M.-O. (2014). How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns. Journal of Retailing and Consumer Services, 21(4), 619-629.
[64] Newhagen, J. E., Cordes, J. W., & Levy, M. R. (1995). Nightly@ nbc. com: Audience scope and the perception of interactivity in viewer mail on the Internet. Journal of communication, 45(3), 164-175.
[65] Orlikowski, W. J., & Iacono, C. S. (2001). Research commentary: Desperately seeking the “IT” in IT research—A call to theorizing the IT artifact. Information systems research, 12(2), 121-134.
[66] Ou, C. X., Davison, R. M., Pavlou, P. A., & Li, M. Y. (2008). Leveraging rich communication tools: Evidence of online trust and Guanxi in China. ICIS 2008 Proceedings, 66.
[67] Pavlou, P. (2001). Integrating trust in electronic commerce with the technology acceptance model: model development and validation. Amcis 2001 proceedings, 159.
[68] Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7(3), 101-134.
[69] Qiu, L., & Benbasat, I. (2005). Online consumer trust and live help interfaces: The effects of text-to-speech voice and three-dimensional avatars. International journal of human-computer interaction, 19(1), 75-94.
[70] Regan, Holly (2017). The Facebook Live Streaming Benchmark Report (WOWZA Report)
[71] Salomonson, N., Åberg, A., & Allwood, J. (2012). Communicative skills that support value creation: A study of B2B interactions between customers and customer service representatives. Industrial Marketing Management, 41(1), 145-155.
[72] Schiffman, L. G., & Kanuk, L. L. (2000). Consumer behavior, 7th. NY: Prentice Hall, 15-36.
[73] Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of consumer research, 15(3), 325-343.
[74] Song, J. H., & Zinkhan, G. M. (2008). Determinants of perceived web site interactivity. Journal of marketing, 72(2), 99-113.
[75] Straubhaar, Joseph and Robert LaRose (1996). Communications Media in the Information Society. Belmont, CA: Wadsworth Press.
[76] Sundar, S. S., & Kim, J. (2005). Interactivity and persuasion: Influencing attitudes with information and involvement. Journal of Interactive Advertising, 5(2), 5-18.
[77] Thorson, K. S., & Rodgers, S. (2006). Relationships between blogs as eWOM and interactivity, perceived interactivity, and parasocial interaction. Journal of Interactive Advertising, 6(2), 5-44.
[78] Van Slyke, C., Shim, J., Johnson, R., & Jiang, J. J. (2006). Concern for information privacy and online consumer purchasing. Journal of the Association for Information Systems, 7(1), 16.
[79] Weathers, D., Sharma, S., & Wood, S. L. (2007). Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods. Journal of retailing, 83(4), 393-401.
[80] Wu, G., & Wu, G. (2006). Conceptualizing and measuring the perceived interactivity of websites. Journal of Current Issues & Research in Advertising, 28(1), 87-104.
[81] Wu, K., Vassileva, J., Noorian, Z., & Zhao, Y. (2015). How do you feel when you see a list of prices? The interplay among price dispersion, perceived risk and initial trust in Chinese C2C market. Journal of Retailing and Consumer Services, 25, 36-46.
[82] Xu, B., Lin, Z., & Shao, B. (2010). Factors affecting consumer behaviors in online buy-it-now auctions. Internet Research, 20(5), 509-526.
[83] Yadav, M. S., & Varadarajan, R. (2005). Interactivity in the electronic marketplace: An exposition of the concept and implications for research. Journal of the Academy of Marketing Science, 33(4), 585-603.

二、 中文文獻
[1] Oath看見數位行銷力 (2016)。讓過時行銷人跳腳的2017數位趨勢之：連巴菲特的股東會都要參一腳了，你還不知道2017年「直播」的3大趨勢是什麼嗎？
2018年02月24日取自
http://yahoo-emarketing.tumblr.com/post/155010193106/2017trend-live
[2] 尼爾森 (2017)。
尼爾森：2017年台灣網購消費者透過行動裝置購物首度超越電腦。
2018年05月04日取自
http://www.nielsen.com/tw/zh/press-room/2017/taiwan-mobile-shopping-overpassed-shopping-via-pc.html
[3] 何佩珊 (2017)。直播平台前撲後繼，贏家可能跟你想得不一樣。數位時代。
2018年02月25日取自
https://www.bnext.com.tw/article/42897/taiwan-live-streaming-2017
[4] 李科成 (2017)，直播行銷革命：13招直播變現技巧X8大產業實戰應用，從企業到素人都適用的爆紅影響力，商周出版股份有限公司，2017年06月，頁37。
[5] 陳敬哲 (2017)。網路影片黏著度狂飆開創電子商務直播趨勢。
今日新聞 (NOWnews)。2018年02月24日取自
https://www.nownews.com/news/20170426/2499484
[6] 陳敬哲 (2017)。電商直播化先機 複合式平台成趨勢。今日新聞 (NOWnews)。
2018年02月24日取自
https://www.nownews.com/news/20170413/2482107
[7] 創市際市場研究顧問公司 (2017)。
創市際2017合作專題一：台灣直播市場『台灣網友直播看什麼？』調查。
2018年02月24日取自
http://www.ixresearch.com/news/news_07_06_17
[8] 創市際市場研究顧問公司 (2017)。創市際雙週刊第九十二期 20170815
2018年02月24日取自
http://www.ixresearch.com/reports/創市際雙週刊第九十二期-20170815/
[9] 楊之瑜 (2017)。【圖輯】臉書直播趨勢分析：人氣最高的不是美妝，而是賣運動鞋。The News Lens 關鍵評論。2018年02月23日取自
https://www.thenewslens.com/article/83459
[10] 資策會產業情報研究所 (Market Intelligence & Consulting Institute, MIC) (2014)。96.2%台灣網友近期曾使用社交網站。
2018年02月26日取自https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=364
[11] 資策會產業情報研究所 (Market Intelligence & Consulting Institute, MIC) (2015)。
《網路社群調查》逾80%網友在個人化社群尋找購物資訊。
2018年02月25日取自https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=412
[12] 資策會產業情報研究所 (Market Intelligence & Consulting Institute, MIC) (2017)。
自媒體產業鏈漸成熟 內容專業化成發展焦點。
2018年02月24日取自
https://mic.iii.org.tw/Industryobservation_MIC02views.aspx?sqno=251
[13] 資策會產業情報研究所 (Market Intelligence & Consulting Institute, MIC) (2017)。
網紅經濟下國際直播平台營運模式分析。
2018年02月23日取自
https://mic.iii.org.tw/Industryobservation_MIC02views.aspx?sqno=260
[14] 資策會產業情報研究所AISP情報顧問服務 (2017)。
【直播大調查系列一】網友最愛Facebook、Youtube、17直播。
2018年02月23日取自
https://mic.iii.org.tw/aisp/PressRoom0.aspx?id=475