政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/118234
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113160/144130 (79%)
Visitors : 50736782      Online Users : 497
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/118234


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/118234


    Title: 以心理帳戶理論與消費者價值理論探討行動應用程式消費之因素
    Why do people spend on mobile apps? An interpretation based on Mental Accounting Theory and Consumption Value Theory
    Authors: 陳曉恩
    Chen, Hsiao-En
    Contributors: 管郁君
    Eugenia Huang
    陳曉恩
    Chen, Hsiao-En
    Keywords: 行動應用程式
    行動應用程式購買
    行動應用程式內購
    消費者價值理論
    心理帳戶理論
    沈浸理論
    Mobile Apps
    App purchase
    Customer value
    Mental accounting theory
    Flow theory
    Date: 2018
    Issue Date: 2018-07-03 17:25:50 (UTC+8)
    Abstract: 行動應用程式發展蓬勃以及智慧型裝置普及性讓行動應用程式的市場變得更加競爭，因此對於行動應用程式的公司、行銷、工程師來說，專注於有效的市場溝通變得極為重要。 本研究旨在了解主要影響使用者決定花錢在應用程式上的因素為何。 本研究架構使用心理帳戶理論建構研究架構的基礎來調查消費者產生消費意圖的過程，除此之外，我們加入沈浸理論來調節意圖與實際購買之間的關係。本研究採用量化實證研究來驗證模型，並收集了729份有效問卷。研究結果顯示，在購買決策過程中的效用評估是刺激使用者產生消費意圖的關鍵，再者，對於購買應用程式和在行動應用程式內購的意圖並無顯著的差異性。最後，不同程度的沈浸程度可能會因為使用者對現階段的滿足，因此減少實際購買的可能性。本研究對行動應用程式的相關購買的研究對現在行動商務有一定的貢獻，期待透過本研究可以增加對行動應用程式相關花費的認識與了解。
    The development of mobile applications (apps) has increased significantly as smart devices have become widely available. With the app market expected to become increasingly competitive, it is crucial for app marketers to focus on effective marketing communications. This study aims to identify the key factors that influence mobile device users’ decisions to spend money on apps.

    Our study builds on mental accounting theory to formulate a fundamental framework and to investigate the process by which spending intentions are formed. We further introduce ‘flow’ as a moderator to help us better discern the explanatory power of actual purchases. Quantitative confirmatory investigations with a large-sample survey and logistics regressions are carried out in this study.

    The findings indicate that utility assessment (or the assessment of a product’s monetary worth in the purchase decision-making process) is extremely important for affecting spending intention. In addition, our research model and results indicate that app spending intention and in-app spending intention are formed in similar ways. Last but not least, we find that the level of flow state affects the likelihood of actual purchase, which helps to explain the necessity for app companies to update functions or to launch various new services if they hope to keep attracting consumers.

    This study contributes to the understanding of app purchasing, which is an important aspect of mobile commerce. We consider that the study’s findings can increase our knowledge and conceptualisation of app purchases.
    Reference: Al-Jabri, I. M., & Sohail, M. S. (2012). Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, Vol. 13, No. 4, pp. 379-391.
    Ajzen, I. (2012). The theory of planned behavior”, in van Lange, P.A.M., Kruglanski, A.W. and Higgins, E.T. (Eds). Handbook of Theories of Social Psychology, Vol. 1, Sage, London, pp. 438-459.
    Bonk, C. J., & Kim, K. J. (2006). The future of online teaching and learning in higher education: The survey says. EDUCAUSE Quarterly Magazine, Vol. 29, No. 4, pp. 22-30.
    Business2community (2017), ‘The 2017 Mobile App Market: Statistics, Trends, and Analysis’, available at https://www.business2community.com/mobile-apps/2017-mobile-app-market-statistics-trends-analysis-01750346#iqxI1RkIxAkGXSpD.97 (accessed 8 October 2017).
    Bagozzi, R.P. (1992). The self-regulation of attitudes, intentions, and behavior. Social Psychology Quarterly, Vol. 55 No. 2, pp. 178-204.
    Chong, A.Y.L., Chan, F.T., & Ooi, K.B. (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems, Vol. 53, No. 1, pp. 34-43.
    Csikszentmihalyi, M. (1975). Play and intrinsic rewards. Journal of humanistic psychology, Vol. 15, No. 3, pp. 41-63.
    Csikszentmihalyi, M., & LeFevre, J. (1989). Optimal experience in work and leisure. Journal of personality and social psychology, Vol. 56, No. 5, pp. 815.
    Csikszentmihalyi, M. (1990). Flow: The psychology of optimal performance.
    Csikszentmihalyi, M. (1996). Flow and the psychology of discovery and invention. New York: Harper Collins.
    Csikszentmihalyi, M. (2000). Beyond boredom and anxiety. Jossey-Bass.
    Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of marketing research, Vol. 43, No. 3, pp. 345-354.
    Chen, H., Wigand, R. T. and Nilan, M. S. (2000). Exploring Web Users’ Optimal Flow Experiences, Information Technology & People, Vol. 13, No. 4, pp. 263-283.
    Donthu, N., & arcia, A. (1999). The internet shopper. Journal of advertising research, Vol. 39, No. 3, pp. 52-52.
    Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management science, Vol. 49, No. 10, pp. 1407-1424.
    Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers` product evaluations. Journal of marketing research, pp. 307-319.
    eMarketer (2016), ‘Mobile Taiwan: A Look at a Highly Mobile Market’, available at
    https://www.emarketer.com/Article/Mobile-Taiwan-Look-Highly-Mobile-
    Market/1014877 (accessed 16 October 2017).
    Efron, B. (1979). Computers and the theory of statistics: thinking the unthinkable. SIAM review, Vol. 21, No. 4, pp. 460-480.
    Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, pp. 39-50.
    Fishbein, M. and Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA.
    Gartner (2017), ‘Gartner Says Worldwide Sales of Smartphones Grew 9 Percent in First Quarter of 2017’, available at https://www.gartner.com/newsroom/id/3725117 (accessed 15 October 2017).
    Gartner (2016), ‘Gartner Mobile App Survey Reveals 24 Percent More Spending on In-App Transactions Than on Upfront App Payments’, available at https://www.gartner.com/newsroom/id/3331117 (accessed 9 April 2018).
    Gartner (2011), ‘Gartner Customer 360 Summit 2011’, available athttps://www.gartner.com/imagesrv/summits/docs/na/customer-360/C360_2011_brochure_FINAL
    .pdf (accessed 19 October 2017).
    Ghani, J.A., Supnick, R., & Rooney, P. (1991). The Experience of Flow in Computer-mediated and in Face-to-face Groups. ICIS, Vol. 91, pp. 229-237.
    Grinblatt, M., & Han, B. (2005). Prospect theory, mental accounting, and momentum. Journal of financial economics, Vol. 78, No.2, pp. 311-339.
    Hyman, H.H. (1942). The psychology of status. Archives of Psychology, Columbia University.

    Holbrook, M.B. (1994). The nature of customer value: an axiology of services in the consumption experience. Service quality: New directions in theory and practice, Vol. 21, pp. 21-71.
    Hoelter, J. W. (1983). The analysis of covariance structures: Goodness-of-fit indices. Sociological Methods & Research, Vol. 11, No. 3, pp. 325-344.
    Kim, H.W., Gupta, S., & Koh, J. (2011). Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Information & Management, Vol .48, No. 6, pp. 228-234.
    Kim, H.W., Xu, Y., & Gupta, S. (2012). Which is more important in Internet shopping, perceived price or trust? Electronic Commerce Research and Applications, Vol. 11, No. 3, pp. 241-252.
    Kim, H.W., Kankanhalli, A., & Lee, H.L. (2016). Investigating decision factors in mobile application purchase: A mixed-methods approach. Information & Management, Vol .53, No. 6, pp. 727-739.
    Keith, M.J., Babb Jr, J.S., Furner, C.P., & Abdullat, A. (2011). The role of mobile self-efficacy in the adoption of location-based applications: An iPhone experiment. In System Sciences (HICSS), 2011 44th Hawaii International Conference on, IEEE, pp. 1-10.
    Lee, J., Lee, J.N., Shi, H. (2011). The long tail or the short tail: the category-specific impact of eWOM on sales distribution. Decision Support System, Vol. 51, No. 3, pp. 466-479.
    Laurillard, D. (2010). Effective use of technology in teaching and learning in HE. In: International Encyclopedia of Education, pp. 419-426.
    The Newslens (2017). ‘Behavioral Economist Celler Wins 2017 Nobel Prize’, available at https://www.thenewslens.com/article/80685 (accessed 28 of March 2018)
    Mäntymäki, M., & Salo, J. (2015). Why do teens spend real money in virtual worlds? A consumption values and developmental psychology perspective on virtual consumption. International Journal of Information Management, Vol. 35, No. 1, pp. 124-134.
    Moore, G.C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, Vol. 2, No. 3, pp. 192-222.

    Müller, R.M., Kijl, B., & Martens, J.K. (2011). A comparison of inter-organizational business models of mobile app stores: There is more than open vs. closed. Journal of theoretical and applied electronic commerce research, Vol. 6, No. 2, pp. 63-76.
    MIC (a) (2016), ‘Mobile App Consumer Survey: Taiwan mobile users average 16 apps per person’, available at https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=424 (accessed 18 October 2017).
    MIC (b) (2016), ‘Mobile App Consumer Survey: Mainly Social Mobile App stickers’, available at https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=422 (accessed 18 October).
    Moore, G.C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, Vol. 2, No. 3, pp. 192-222.
    Miyazaki, A.D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. Journal of Consumer affairs, Vol. 35, No.1, pp. 27-44.
    Milkman, K.L., & Beshears, J. (2009). Mental accounting and small windfalls: Evidence from an online grocer. Journal of Economic Behavior & Organization, Vol. 71, No. 2, pp. 384-394.
    Novak, T.P., & Hoffman, D.L. (1997). Measuring the flow experience among web users. Interval Research Corporation, Vol. 31, pp. 1-36.
    Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing science, Vol. 19, No. 1, pp. 22-42.
    Nunnally, J. C. (1994). The assessment of reliability. Psychometric theory.
    Ono, A., Nakamura, A., Okuno, A., & Sumikawa, M. (2012). Consumer motivations in browsing online stores with mobile devices. International Journal of Electronic Commerce, Vol. 16, No. 4, pp. 153-178.
    Privette, G., & Bundrick, C.M. (1987). Measurement of experience: Construct and content validity of the experience questionnaire. Perceptual and motor skills, Vol. 65, No. 1, pp. 315-332.

    Petrova, K. (2006). Mobile learning as a mobile business application. International Journal of Innovation and Learning, Vol. 4, No. 1, pp. 1-13.
    Pura, M. (2005). Linking perceived value and loyalty in location-based mobile services. Managing Service Quality: An International Journal, 15(6), 509-538.
    Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.
    Sweeney, J.C., Soutar, G.N., & Johnson, L.W. (1999). The role of perceived risk in the quality-value relationship: a study in a retail environment. Journal of retailing, Vol. 75, No. 1, pp. 77-105.
    Sweeney, J.C., & Soutar, G.N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of retailing, Vol. 77, No. 2, pp. 203-220.
    Schwab, D.P. (1980). Construct validity in organizational behavior. Research in organizational behavior, Vol. 2, No. 1, pp. 3-43.
    Sheth, J.N., Newman, B.I., & Gross, B.L. (1991). Why we buy what we buy: A theory of consumption values. Journal of business research, Vol. 22, No. 2, pp. 159-170.
    Schepman, A., Rodway, P., Beattie, C., & Lambert, J. (2012). An observational study of undergraduate students’ adoption of (mobile) note-taking software. Computers in Human Behavior, Vol. 28, No. 2, pp. 308-317.
    Statista (2017), ‘Mobile App Usage - Statistics & Facts’, available at https://www.statista.com/topics/1002/mobile-app-usage/ (accessed 17 of October 2017)
    Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors’ flow experience while browsing a Web site: its measurement, contributing factors and consequences. Computers in human behavior, Vol. 20, No. 3, pp. 403-422.
    Thaler, R. (1985). Mental accounting and consumer choice. Marketing science, Vol. 4, No. 3, pp. 199-214.
    Thaler, R.H. (1999). Mental accounting matters. Journal of Behavioral decision making, Vol. 12, No. 3, pp. 183.
    Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS quarterly, pp. 695-704.
    Verkasalo, H., López-Nicolás, C., Molina-Castillo, F.J., & Bouwman, H. (2010). Analysis of users and non-users of smartphone applications. Telematics and Informatics, Vol. 27, No. 3, pp. 242-255.

    Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, Vol. 46, No. 2, pp. 186-204.
    Webster, E. J. (1989). Playfulness and computers at work.
    Webster, J., Trevino, L.K., & Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interactions. Computers in human behavior, Vol. 9, No. 4, pp. 411-426.
    Zeithaml, V.A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of marketing, Vol. 2-22.
    Description: 碩士
    國立政治大學
    資訊管理學系
    105356004
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G1053560041
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.MIS.001.2018.A05
    Appears in Collections:[Department of MIS] Theses

    Files in This Item:

    File SizeFormat
    004101.pdf2626KbAdobe PDF264View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback