虛實整合 (Online to Offline/Offline to Online, O2O) 為電子商務其中一種模式，兼顧實體通路與虛擬通路，並可運用新的技術和營運模式開發出新的消費者，同時擴大市場。本研究針對餐旅業及觀光業之O2O，即於線上預訂餐廳、旅館或購買旅遊、SPA、健身房、電影、演唱會等餐飲、旅遊、休閒娛樂票券，再至實體店面體驗所預購的服務之消費模式，除了使用延伸型整合科技接受模式 (The extended unified theory of acceptance and use of technology, UTAUT2) 外，也根據過往網路使用行為相關文獻，加入社群網路服務接受模式 (Social Network Services Acceptance Model, SNS)，許多消費行為研究證實，產品涉入程度對行為意圖具調節作用，故在本研究中亦加入消費者產品涉入程度為調節變項。本研究首先以過去文獻之問卷內容為基礎，經由訪談6位專家確定問卷內容效度，發放前測問卷並確認信度後，再以便利抽樣法於各網路平台發放問卷，以結構方程模型 (structural equation modeling , SEM) 進行模型適配度檢驗及路徑分析。根據本研究結果，態度、促進條件、享樂動機、績效預期、習慣及社會影響對行為意圖有顯著正向影響；預期科技安全對行為意圖有顯著負向影響。促進條件及隱私風險對使用行為有顯著負向影響；行為意圖對使用行為則有顯著正向影響。並發現高產品涉入者在績效預期對使用O2O模式之行為意圖具調節作用。最後根據實證結果提出管理意涵建議，使O2O平台業者與店家在發展O2O模式時能夠制定更符合消費者需求之經營策略。

The O2O business model has become the prevailing e-commerce business model in the hospitality industry. However, there is still not enough research to be sure of the factors which will influence consumers’ intention and use behavior in O2O. This study aims to understand consumers’ use intention for O2O on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) by adding Social Network Services Acceptance Model (SNS). Furthermore, this study also added “product involvement” as a moderator in order to predict their use intention for O2O more precisely. This study used the structural equation modeling (SEM) to analyze the factors of consumers using O2O or not by using AMOS and the results from 166 collected samples indicated that attitude, hedonic motivation, performance expectancy, habit, and social influence had significant and positive effects on the behavior intention of using O2O; perceived technology security had behavior intention of O2O. Facilitating conditions and privacy risk had significant and negative effects on the usage of O2O; the behavior intention of using O2O had significant and positive effects on the usage of O2O. High product involvement had a moderated effect on performance expectancy for the behavior intention of using O2O. The future research and managerial implication are discussed.

一、中文文獻
吳明隆、涂金堂 (2014)。SPSS 與統計應用分析 (二版)。臺北市：五南。
吳明隆、張毓仁 (2010)。結構方程模式：實務應用秘笈。臺北市：五南。
吳淑鶯、黃淑鈴 (2003)。影響消費者對咖啡連鎖店涉入程度之前因及結果實證研究。中華管理評論國際學報，6(4)，135-155。
官方網站Gomaji (2017)。關於我們 / 關於 GOMAJI 夠麻吉 (2017年7月12日) 取自：http://www.gomaji.com/index.php?city=Taipei&ref=396&gclid=Cj0KCQjwn6DMBRC0ARIsAHZtCeOgABldvCVl7m8Qy9FsVjo4dgl2EQPJnF_GVcDlDa-0ABFttGCf7fkaAsqREALw_wcB
財團法人台灣網路資訊中心 (2017)。歷年無線上網趨勢分析。(2017年12月25日) 取自：https://www.twnic.net.tw/download/200307/20170109f.pdf
財團法人資訊工業策進會產業情報研究所 (2016)。【網購消費者調查】2016年網購消費平均27,715元。(2017年7月15日) 取自：http://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=464&cred=2017/03/15&type1=2
張偉豪 (2011)。SEM論文寫作不求人。台北市：鼎茂圖書。
張嘉伶 (2015)。專家看台灣電商發展趨勢：行動、支付、大數據、跨境。數位時代。 (2018年7月8日) 取自：https://www.bnext.com.tw/article/35389/BN-ARTICLE-35389
黃慧玲、陳岳陽與許英傑 (2007)。預購通路中消費者產品知覺品質，滿意度及忠誠度間之關係-不同零售通路型態的干擾效果。電子商務學報，9(3)，461-485。
郭彥谷、林舜慈、莊適瑜、林瑩滋與張邦立 (2014)。情緒勞務孰輕孰重？ 探討工作壓力對情緒勞務之影響。管理資訊計算，3，158-165。
曹勝雄 (2017)。觀光行銷學。產業觀點與實務應用。新北市：前程文化事業有限公司。
彭夢竺 (2016)。電商成兆元產業，網購平台2015交易量破3700萬筆。今日新聞。(2017年11月2日)取自https://www.nownews.com/news/20160315/2029009
劉文良 (2004)。電子商務概論特訓教材。台北市：碁峰資訊。
鍾雪晴 (2016)。聚焦台灣大選，看台灣O2O發展現狀。億歐網。(2017年7月9日)取自http://www.iyiou.com/p/19687
戴慧瑀 (2016)。馬雲：純電商消失，新零售來臨。中時電子報。(2017年11月21日)取自http://www.chinatimes.com/newspapers/20161014000850-260303
Meiyu, C. (2018). O2O線上對應線下實體，電子商務新戰場。DGcovery. (2018/7/8) Retrived from:https://www.dgcovery.com/2018/03/09/o2o%E9%9B%BB%E5%AD%90%E5%95%86%E5%8B%99/

二、英文文獻
Acemyan, C. Z., & Kortum, P. (2012). The relationship between trust and usability in systems. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 56, 1842-1846.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Baptista, G. & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computer Human Behavior. 50,418-430.
Barnes, S., Bauer, H. Neumann, M. & Huber, F. (2007). Segmenting cyberspace: A customer typology for the Internet. European Journal of Marketing. 41(1/2), 71-93.
Bartsch, V., Ebers, M., & Maurer, I. (2013). Learning in project-based organizations: The role of project teams' social capital for overcoming barriers to learning. International Journal of Project Management, 31(2), 239-251.
Bhatiasevi, V. (2016). An extended UTAUT model to explain the adoption of mobile banking. Information Development, 32(4), 799-814.
Boss, S. R., Galletta, D. F., Lowry, P. B., Moody, G. D., & Polak, P. (2015). What do users have to fear? Using fear appeals to engender threats and fear that motivate protective security behaviors. MIS Quarterly, 39(4), 837-864.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399-426.
Chen, M. F., & Huang, C. H. (2013). The impacts of the food traceability system and consumer involvement on consumers' purchase intentions toward fast foods. Food Control, 33(2), 313-319.
Cheng, T. E., Lam, D. Y., & Yeung, A. C. (2006). Adoption of internet banking: An empirical study in Hong Kong. Decision Support Systems, 42(3), 1558-1572.
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511-535.
Chung, S., Kim, W., & Bae, Y. H. (2017). O2O Trend and future: Focused on difference from each case. Journal of Marketing Thought, 3(4), 49-66.
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.
Delbecq, A. L., Van de Ven, A. H., & Gustafson, D. H. (1975). Group techniques for program planning: A guide to nominal group and Delphi processes (pp. 83-107). Glenview, IL: Scott & Foresman.
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers' product evaluations. Journal of Marketing Research, 28(3), 307-319.
Drossos, D. A., Maragoudakis, M., & Kokkinaki, F. (2015). Buying behavior on daily-deal sites: the role of face value, product involvement, information, and website quality. Journal of Internet Commerce, 14(2), 200-232.
Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70-88.
Fathema, N., Shannon, D., & Ross, M. (2015). Expanding the technology acceptance model (TAM) to examine faculty use of learning management systems (LMSs) in higher education institutions. Journal of Online Learning & Teaching, 11(2), 210-232.
Foltz, C. B., Newkirk, H. E., & Schwager, P. H. (2016). An empirical investigation of factors that influence user behavior toward changing social networking sites’ security settings. Journal of Theoretical and Applied Electronic Commerce Research, 11(2), 1-15.
Gardner, B. S. (2011). Responsive web design: Enriching the user experience. Sigma Journal: Inside the Digital Ecosystem, 11(1), 13-19.
Harsono, L. D., & Suryana, L. A. (2014). Factors affecting the use behavior of social media using UTAUT 2 model. In Proceedings of the First Asia-Pasific Conference on Global Business, Economics, Finance and Social Sciences, Singapore. 471, 1-14.
Hew, J. J., Lee, V. H., Ooi, K. B., & Wei, J. (2015). What catalyses mobile apps usage intention: An empirical analysis. Industrial Management & Data Systems, 115(7), 1269-1291.
Hong, W., & Thong, J. Y. (2013). Internet privacy concerns: an integrated conceptualization and four empirical studies. MIS Quarterly, 37(1), 275-298.
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564.
Kim, M. J., Chung, N., & Lee, C. K. (2011). The effect of perceived trust on electronic commerce: Shopping online for tourism products and services in South Korea. Tourism Management, 32(2), 256-265.
Kondrat, J. (2017). Understanding asymmetries in ict acceptance at individual use in Poland: The UTAUT2 theory combined with attitude, privacy risk, perceived security (Doctoral dissertation). Availible from Portugal: NOVA Information Management School.
Laaksonen, P. (1994). Consumer involvement: Concepts and research. London, England: Routledge.
Lastovicka, J. L. & Gardner, D. M., (1978). Low involvement versus high involvement cognitive structures. Advances in Consumer Research, 5, 87-92.
Laurent, G., & Kapferer, J. N. (1985). Measuring consumer involvement profiles. Journal of Marketing Research, 22, 41-53.
Lian JW, Yen DC (2014). Online shopping drivers and barriers for older adults; age and gender differences. Computer Human Behavior. 37(3), 133–143.
Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705-737.
Lu, H. K., Lin, P. C., & Lin, Y. C. (2016). A study of the factors affecting the purchase intention on mobile game apps. Journal of Advances in Information Technology, 7(4), 239-244.
Marsh, H. W., Hau, K. T., Balla, J. R., & Grayson, D. (1998). Is more ever too much? The number of indicators per factor in confirmatory factor analysis. Multivariate Behavioral Research, 33(2), 181-220.
Martín, H., & Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341-350.
Metzger, M. J. (2006). Privacy, trust, and disclosure: Exploring barriers to electronic commerce. Journal of Computer‐Mediated Communication, 9(4), JCMC942.
Phang, C. W., Tan, C. H., Sutanto, J., Magagna, F., & Lu, X. (2014). Leveraging O2O commerce for product promotion: An empirical investigation in Mainland China. IEEE Transactions on Engineering Management, 61(4), 623-632.
Rampell, A. (2010). Why online to Offline commerce is a trillion dollar opportunity. 2017/12/20 Retrieved from http://techcrunch.com/2010/08/07/why-online2offline-commerce-is-a-trillion-dollar-opportunity.San
Schifter, D. B., & Ajzen, I. (1985). Intention, perceived control, and weight loss: And application of the theory of planned behaviour. Journal of Personality and Social Psychology, 49(3), 842-851.
Seo, S., & Moon, S. (2016). Decision-making styles of restaurant deal consumers who use social commerce. International Journal of Contemporary Hospitality Management, 28(11), 2493-2513.
Sherif, M., & Cantril, H. (1947). The Psychology of Ego-involvements: Social Attitudes and Identifications. New York, United State: Wiley.
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.
Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: Extending UTAUT with innovativeness, risk, and trust. Psychology and Marketing, 32(8), 860-873.
Sörbom, D. (1989). Model Modification. Psychometrika, 54 (3), 371-384.
Sproles, G. and Kendall, E. (1986). A methodology for profiling consumer decision making styles. Journal of Consumer Affairs, 20(4), 267-279.
Strachan, D. (2014). Free Wi-Fi networks: The world's most connected cities. The Daily Telegraph. 2017/12/02 Retrieved from http://www.telegraph.co.uk/travel/advice/Free-Wi-Fi-networks-the-worlds-most-connected-cities/
Tandon, U., Kiran, R., & Sah, A. N. (2016). Customer satisfaction using website functionality, perceived usability and perceived usefulness towards online shopping in India. Information Development, 32(5), 1657-1673.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Venkatesh, V., Thong, J. I. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.
Verbeke, W. & Vackier, I. (2004). Profile and effects of consumer involvement in fresh meat. Meat Science, 67, 159-168.
Walsh, G., Hennig-Thurau, T., Wayne-Mitchell, V. & Wiedmann, K. (2001). Consumers' decision making styles as a basis for market segmentation. Journal of Targeting, Measurement and Analysis for Marketing, 10(2), 117-131.
Wen, I. (2009). Factors affecting the online travel buying decision: A review. International Journal of Contemporary Hospitality Management, 21(6), 752-765.
Wong, J., & Law, R. (2005). Analysing the intention to purchase on hotel websites: A study of travellers to Hong Kong. International Journal of Hospitality Management, 24(3), 311-329.
Wu, T. J., Zhao, R. H., & Tzeng, S. Y. (2015). An empirical research of consumer adoption behavior on catering transformation to mobile O2O. Journal of Interdisciplinary Mathematics, 18(6), 769-788.
Zaichkowsky, J.L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341-352.
Zaichkowsky, J. L. (1994). The personal involvement inventory: Reduction, revision, and application to advertising. Journal of Advertising, 23(4), 59-70.
Zhao, Y., Xue, Y., & Yang, J. (2015). The influence factors of O2O E-Commerce trust research-based on the perspective of consumer participants. International Journal of Research Studies in Science, Enginering and Technology, 2(8), 84-90.