目前現有的團購網站大多為一集結帄台，網頁本身並不販售任何商品，而是邀請賣方主動將商品上架到團購網頁上，買家會依據自我意願在網頁帄台上互相聚集購買，但這種集結行為往往侷限於團購帄台內，無法有效發揮網路的社群功能。而本研究提出了一套創新的社群團購系統，相較於傳統的團購網頁，系統並不架設單一的網頁帄台，而是直接將團購服務鑲嵌於賣家的賣場當中，同時結合了社群網站的功能，透過其龐大的瀏覽流量與網路傳播能力，將使用者對商品的喜好與購買意願等使用者經驗，轉化成實際對商品團購的動力，藉此幫助團購成員的聚集。
在系統建置時，會透過服務藍圖方式來整理社群團購系統所提供的服務，並以流程圖的方式來描述使用者行為，觀察使用者在各個操作過程中遭遇的失誤或感到困惑的設計，藉此驗證、修改或維護系統服務。
本研究邀請26名在學學生進行系統體驗，測詴過程中會全程記錄使用者操作流程與反應，並利用分解式計劃行為理論就不同分析構陎設計問卷，測詴完成後根據問卷數據統計及受測者實測影片加以洞察驗證，檢視系統是否達到當初設計者預期的體驗效果。
分析驗證從行為態度、知覺行為控制兩個方向出發，探討使用者對於社群團購系統的採用意願。從實測影片以及問卷的帄均得分統計可以得看出，使用者普遍能夠接受社群團購系統，由於系統在設計時考慮了操作易用的特定，讓使用者不需耗費額外的時間學習就能熟悉系統的操作。在知覺行為控制構陎中，因受測者皆有使用過社群網站臉書的經驗，所以對於系統所提供的社群按鈕服務並不陌生，可以直覺透過系統社群功能分享個人經驗，從問卷分數帄均的結果也看得出大部分使用者在操作上沒有遭遇到太多的困難。就整體使用意願而言使用者大多抱持著正向的態度，並且樂於接受這項線上社群團購系統。

Nowadays, most of group buying websites only provide a platform for sellers to list products and process transactions. Consumers are attracted and gathered by bonuses or discounts provided by the websites. Product information is listed in one specific website and users have to go to the website for finding or purchasing products which they are looking for. Different from traditional group buying websites, we design a novel group buying system that directly embeds grouping service in sellers’ webpages instead of establishing a traditional website. In addition, user experiences are collected and employed to improve the potential of creating group purchasing activities.
While building our system, service blueprinting technique is used to arrange the services that we offer. At the same time, the operation procedures which might cause misunderstanding or confusion are carefully checked and tested. After the initial check, we invited 26 students to experience our system. The whole experiments including the operation process and user interactions are all recorded. Decomposed Theory of Planned Behavior is utilized to design the questionnaire survey. The results from the statistics of the questionnaire and testing videos are used to verify whether the system achieves the goal for increasing group purchasing activities.
Based on Decomposed Theory of Planned Behavior of attitude toward behavior and perceived behavioral control, we analyze and observe user acceptance for our system. Through the videos and the statistics gathered from questionnaire survey, we found that most users feel that our system is easy to use without difficulties. In the part of perceived behavioral control, since most testers have experience to use social websites like Facebook, they all felt familiar with the social service plug-in provided by our system, and certainly can share their own experience through social websites. In general, most users keep positive attitude to our system, and are willing to use our service for online group purchasing.

[1] McHugh, J. 1999. Consumer collusion!. Forbes, 164(5), 222-223.
[2] Lai, H., 2002. “Collective Bargaining Models on e-Marketplace.”, International Conference on Advance in Infrastructure for e-Business, e-Education, e-Science, e-Medicine on the Internet, L’Aquila, Italy.
[3] Anand, K. S., & Aron, R. 2003. Group-buying on the web: A comparison of price-discovery mechanisms. Management Science, 49(11): 1546-1562.
[4] Baldwin, I. 2000. Mastering the incredible bulk. Kiplinger's Personal Finance, 54,126-128.
[5] Komando, K. 2000. Playing the numbers. Popular Mechanics, 177, 32-33.
[6] Kauffman, R. J., & Wang, B. 2001. New buyers' arrival under dynamic pricing market microstructure: The case of group-buying discounts on the Internet. Journal of Management Information Systems, 18(2), 157-188.
[7] Fishbein, M. & Ajzen. 1975. Belief, Attitude, Intention, and Behavior：An Introduction to Theory and Research. Reading. MA：Addison-Wesley.
[8] Ajzen, Icek. 1991,“The Theory of Planned Behavior,” Organizational Behavior and Human Decision Processes , 50(2), pp.179-211.
[9] Ajzen, Icek and Thomas J. Madden. 1985,“Prediction of Goal-Directed Behavior： Attitudes, Intentions, and Perceived Behavioral Contro,” Journal of Experimental Social Psychology, 22(5), pp.453-474.
[10] Ajzen, Icek . 1985,“From Intentions to Actions：A Theory of Planned Behavior,” in Action Control from Cognition to Behavior, Kuhl Julius and Bechmann Jurgen, pp.11-39.
[11] Davis, F.D., R.P. Bagozzi and P.R. Warshaw.1989, “User Acceptance of Computer Ttechnology：A Comparison of Two Theoretical Models,” Management Science, 35(8), pp.982-1003.
[12] Bagozzi, Richard P. 1981, “Attitudes, Intentions, and Behavior：A Test of Some Key Hypotheses,” Journal of Personality and Social Psychology, 41(4), pp.607-627.
[13] E.M. Rogers. 1983, “Diffusion of Innovations,” third edn, The Free Press, New York.
[14] Davis, Fred D. 1989, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, pp.319-335.
[15] Bandura, A. 1982. Self-Efficacy Mechanism in Human Agency. American Psychologist, 37(2), 122-147.
[16] Taylor, S. & Todd, P. A. 1995. Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176.
[17] Taylor, S. & Todd, P. A. 1995b. “Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions,” 82 International Journal of Research in Marketing, 12(2), 137-155.
[18] Mathieson, K. 1991. Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information systems research, 2(3), 173-191.
[19] Triandis, H. C. 1971. Attitude and attitude change. New York: Wiley.
[20] Ajjan, H., & Hartshorne, R. 2008. Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests. The Internet and Higher Education, 11(2), 71-80.
[21] Lin, H. F. 2008. Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6(4), 433-442.
[22] Kwahk, K. Y., & Lee, J. N. 2008. The role of readiness for change in ERP implementation: Theoretical bases and empirical validation. Information & Management, 45(7), 474-481.
[23] Compearu, D. R. & Higgins, C. A. 1995b. Computer Self-Efficacy: Development of a Measure and Initial Test. MIS Quarterly, 19(2), 189-211.
[24] Hung, S. Y., & Chang, C. M. 2005. User acceptance of WAP services: test of competing theories. Computer Standards & Interfaces, 27(4), 359-370.
[25] Bitner, M. J., Ostrom, A. L., & Morgan, F. N. 2008. Service blueprinting: a practical technique for service innovation. California Management Review, 50(3), 66.