智慧型手機（smart phone）逐漸取代了功能性手機（feature phone）的地位，伴隨著智慧型手機的發展，手機軟體（App）也逐漸受到大眾的注目。截至2011年底為止，App Store 以及 Google Play 上的 App 都已經超過五十萬個，其中 App Store 更在2012年三月時更達到了總數250億次的下載量。然而隨著 App 市場的壯大，許多研究發現 App 的獲利模式逐漸從一次性購買轉移至「軟體內購買（In-App Purchases）」，且大多數獲利的 App 都是屬於遊戲的軟體。本研究利用計畫行為理論（Theory of Planned Behavior, TPB）作為研究的架構，並且以沉浸理論（Flow Theory）作為切入點，試圖解釋使用者在遊戲類的 App 進行軟體內購買的行為。
本研究利用「問卷調查法」進行研究資料的蒐集，總計回收有效樣本數達到326份，並且透過 PLS 以及 SPSS 進行資料的分析，以檢驗研究假說。研究結果發現：一、計畫行為理論可以有效的解釋使用者的軟體內購買行為；二、當使用者進入沉浸狀態的時候，會對其軟體內購買的行為有正向的直接影響，比起計畫行為理論的理性因素，屬於非理性因素的沉浸經驗能更直接有效地影響使用者行為；三、對於使用軟體內購買的行為來說，描述性規範比起命令性規範更加有效。

In recent years, smart phones have gradually replaced feature phones in the mobile market. Along with the rapid growth of smart phones, mobile phone’s application (app) also receive public acceptance. By the end of 2011, the number of apps available on both the Apple App Store and the Google Play all surpassed 50,000. In addition, Apple App Store has reached 25 billion in app download count by March 2012. With the growth of App’s market, the App revenue model has gradually transformed from “one-time purchases” to “in-app purchases.” Of all App categories, Games have netted the most revenue. This study attempts to look into the phenomenon of “in-app purchases,” trying to explain the seemingly impulsive behavior. We extended the “Theory of Planned Behavior (TPB)” with “Flow theory.”
In this study, data was collected from 326 valid respondents through web-based questionnaires distributed through relevant discussion groups. PLS and SPSS were employed as data analysis tools. Result revealed that: (1) the extended TPB model is effective in explaining the respondent’s in-app purchases behavior; (2) “flow experience” has a directly effect on respondent’s actual behavior; and (3) descriptive norm is more likely to influence the respondents than injunctive norm in in-app purchase behavior.

Ajzen, I. (1985). From intentions to action: “A theory of planned behaviour.” In J. Kuhl & J. Beckmann (Eds.). Action control: From cognition to behaviour, Heidelberg: Springer, pp. 11-39.
Ajzen, I. (1991). “The theory of planned behaviour.” Organizational Behaviour and Human Decision Processes, 50, 179-211.
Ajzen, I. (1991). “The theory of planned behaviour.” Organizational Behaviour and Human Decision Processes, 50, 179-211.
Ajzen, I., & Fishbein, M. (1977). “Attitude-behaviour relations: A theoretical analysis and review of empirical research.” Psychological Bulletin, 84, 888-918.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior: Prentice Hall.
Ajzen, I., & Madden, T. J. (1985). “Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control.” Journal of Experimental Social Psychology, pp.453-474.
Armitage, C. J., & Conner, M. (2001). “Efficacy of the theory of planned behavior: A meta-analytic review.” British Journal of Social Psychology, 40, 471-499.
Bagozzi, R. P., & Yi, Y.(1988). “On the evaluation structural equation models.” Academic of Marketing Science, 16, 74-94.
Bagozzi,R.P., & Lee, K. H. (2002). “Multiple routes for social influence: The role of compliance, internalization, and social identity.” Social Psychology Quarterly, 65(3), 226-247.
Bala, R., & Carr, S. (2009). “Pricing Software Upgrades: The Role of Product Improvement and User Costs.” Production and Operations Management, 18(5), 560-580.
Beck, L., & Ajzen, I. (1991). “ Predicting dishonest actions using the theory of planned behavior.” Journal of Research in Personality, 24, 285-301.
Blackwell, R. D., Miniard, P. W. & Engel, J. F. (2001), Consumer Behavior. 9th ed., Harcourt.
Choi, D., & Kim, J. (2004). “Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents.” CyberPsychology & Behavior, 7(1), 11-24.
Csikszentmihalyi, M. (1975). “Beyond boredom and anxiety.” San Francisco, CA: Jossey-Bass.
Csikszentmihalyi, M. (1988). “Introduction. In Csikszentmihalyi, M., & Csikszentmihalyi, I. S.” Optimal experience: psychological studies of flow in consciousness. Cambridge,UK: Cambridge University Press, 3-14.
Csikszentmihalyi, M. (1990). “Flow: The psychology of optimal experience.” New York: Harper & Row.
Csikszentmihalyi, M., & Massimini, F. (1985). “On the psychological selection of bio- cultural information.” New Ideas in Psychology, 3, 115-138.
Cunningham, S. (1967). “The major dimensions of perceived risk.” Risk taking and information handling in consumer behavior, 82-108.
Cialdini, R. B., Kallgren, C. A., & Reno, R. R. (1991). “A focus theory of normative conduct.” Advances in Experimental Social Psychology, 24, 201-234.
Cialdini, R. B., Reno, R. R., & Kallgren, C. A. (1990). “A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places.” Journal of Personality and Social Psychology, 58(6), 1015-1026.
Charlton, J. P., & Danforth, I. D. W. (2010). “Validating the distinction between computer addiction and engagement: online game playing and personality.” Behaviour & Information Technology, 29(6), 601-613.
Chen, L. S. L. (2010). “The impact of perceived risk, intangibility and consumer characteristics on online game playing.” Computers in Human Behavior, 26(6), 1607-1613.
Chiang, Y. T., Lin, S. S. J., Cheng, C. Y., & Liu, E. Z. F. (2011). “Exploring Online Game Players'' Flow Experiences and Positive Affect.” Turkish Online Journal of Educational Technology, 10(1), 106-114.
Conner, M., & McMillan, B. (1999). “Interaction effects in the theory of planned behavior: Studying cannabis use.” British Journal of Social Psychology, 38, 195-222.
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.
Downing, S. (2009). “Attitudinal and Behavioral Pathways of Deviance in Online Gaming.” Deviant Behavior, 30(3), 293-320.
Eagly, A. H., & Chaiken, S. (1993). The Psychology of Attitude, NY: Harcourt, Brace, Jovonovich.
Elek, E., Miller-Day, M., & Hecht, M. L. (2006). “Influences of personal, injunctive, and descriptive norms on early adolescent substance use.” Journal of Drug Issues, 36(1), 147-172.
Fornell, C., & Larcker, D. F. (1981). “Evaluating structural equation models with unobservable variables and measurement error.” Journal of Marketing Research, 18(3), 39-50.
Gao, Y. (2005). “Factors influencing user trust in online games.” Proceedings Paper. Electronic Library, 23(5), 533-538.
Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2004). “Online computer gaming: a comparison of adolescent and adult gamers.” Journal of Adolescence, 27(1), 87-96.
Heberlein, T. A., & Black, J. S. (1976) “Attitudinal Specificity and the Prediction of Behavior in a Field setting.” Journal of Personality and Social Psychology, 33, pp.474-479.
Hsu, C. L., & Lu, H. P. (2004). “Why do people play on-line games? An extended TAM with social influences and flow experience.” Information & Management, 41(7), 853-868.
Huang, L. Y., & Hsieh, Y. J. (2011). “Predicting online game loyalty based on need gratification and experiential motives.” Internet Research, 21(5), 581-598.
Hui, K. L., & Tam, K. Y. (2002). “Software functionality: A game theoretic analysis.” Journal of Management Information Systems, 19(1), 151-184.
Isen, A. (1984). “The influence of positive affect on decision making and cognitive organization.” Advances in consumer research, 11(1), 534-537.
Isen, A., & Levin, P. (1972). “Effects of feeling good and helping: Cookies and kindness.” Journal of Personality and Social Psychology, 3, 384-388.
Jeng, S. P., & Teng, C. I. (2008). “PERSONALITY AND MOTIVATIONS FOR PLAYING ONLINE GAMES.” Social Behavior and Personality, 36(8), 1053-1059.
Joe, S. W., & Chiu, C. K. (2009). “Proposing online game loyalty and its antecedents considering gender as a moderator: a qualitative study.” Quality & Quantity, 43(5), 731-741.
Khoo, H. M., Chua, C. E. H., & Robey, D. (2011). “How organizations motivate users to participate in support upgrades of customized packaged software.” Information & Management, 48(8), 328-335.
Kotler, P. (1997), Marketing Management. 9th ed., New Jersey: Prentice Hall Inc.
Lee, M. C. (2009). “Understanding the behavioural intention to play online games An extension of the theory of planned behaviour.” Online Information Review, 33(5), 849-872.
Lin, H., & Sun, C. T. (2011). “Cash Trade in Free-to-Play Online Games.” Games and Culture, 6(3), 270-287.
Lin, J. Y. C., Wang, E. S. T., Kao, L. L. Y., & Cheng, J. M. S. (2007). “A study of the perceived recognition affecting the adoption of innovation with respect to the online game in Taiwan.” Cyberpsychology & Behavior, 10(6), 813-815.
Lu, H. P., & Wang, S. M. (2008). “The role of Internet addiction in online game loyalty: an exploratory study.” Internet Research, 18(5), 499-519.
Park, B. W., & Lee, K. C. (2011). “Exploring the value of purchasing online game items.” Computers in Human Behavior, 27(6), 2178-2185.
Park, J. C. (2007). “Play between worlds: Exploring online game culture.” New Media & Society, 9(3), 548-550.
Raghunathan, S. (2000). “Software editions: An application of segmentation theory to the packaged software market.” Journal of Management Information Systems, 17(1), 87-113.
Rau, P. L. P., Peng, S. Y., & Yang, C. C. (2006). “Time distortion for expert and novice online game players.” Cyberpsychology & Behavior, 9(4), 396-403.
Rivis, A., & Shreeran, P. (2003). “Descriptive norms as an additional predictor in the theory of planned behaviour: A meta- analysis.” Current Psychology: Developmental, Learning, Personality, Social, 22(3), 218-233
Rotter, Julian B (1971). “Generalized expectancies for interpersonal trust.” American Psychologist, Vol 26(5), May 1971, 443-452.
Sheu, J. J., Su, Y. H., & Chu, K. T. (2009). “Segmenting online game customers - The perspective of experiential marketing.” Expert Systems with Applications, 36(4), 8487-8495.
Taylor, S., & Todd, P. (1995). “Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions.” International Journal of Research in Marketing, 12, 137-155.
Taylor, S., & Todd, P. A. (1995a). “Decomposition and cross effects in the theory of planned behavior: A study of consumer adoption intentions.” International Journal of Research in Marketing, 12, 137-155.
Taylor, S., & Todd, P. A. (1995b). “Understanding information technology usage: A test of competing models.” Information Systems Research, 6(2), 144-177.
Thompson, J. (2008). “Free online games, open source software and library technical roles, what do they have in common?” Profesional De La Informacion, 17(6), 679-680.
Tseng, F. C. (2011). “Segmenting online gamers by motivation.” Expert Systems with Applications, 38(6), 7693-7697.
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.
Viard, V. B. (2007). “Information goods upgrades: Theory and evidence.” B E Journal of Theoretical Economics, 7(1), 34. doi: 3
Voiskounsky, A. E., Mitina, O. V., & Avetisova, A. A. (2004). “Playing online games: Flow experience.” Psychnology Journal, 2(3), 259-281.
White, K., Smith, J., Terry, D., Greenslade, J., & McKimmie, B. (2009). “Social influence in the theory of planned behaviour: The role of descriptive, injunctive, and in-group norms.” British Journal of Social Psychology, 48(1), 135-158.
Wu, J., & Liu, D. (2007). “The effects of trust and enjoyment on intention to play online games.” Journal of Electronic Commerce Research, 8(2), 128-140.
Yang, H. E., Wu, C. C., & Wang, K. C. (2009). “An empirical analysis of online game service satisfaction and loyalty.” Expert Systems with Applications, 36(2), 1816-1825.
Yi-Chun Huang, Yen-Chun Jim Wu, Yu-Chun Wang, Nolan Christopher Boulanger, (2011) "Decision making in online auctions", Management Decision, 49(5), 784-800
范錚強，計畫和非計畫行為，未出版手稿，2010年。
王渝薇，「玩線上遊戲是計畫行為嗎？－以沉浸經驗延伸計畫行為理論」，國立中央大學資訊管理研究所碩士論文，2011年。