The Influence of Individual Affective Factors on the Continuous Use of Mobile Apps

  • Yi-Hsuan YehEmail author
  • Belinda Chen
  • Nien-Chu Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9191)


Mobile apps have attracted a substantial amount of attention in mobile commerce. Usage behavior of consumers is always an important issue in this research area. The objective of this study is to explore what factors will affect an individual’s continuance intention to use mobile apps. We proposes a research model that integrates the Task-Technology Fit (TTF) and Theory of Reasoned Action (TRA), which are augmented with concepts of affective factors. We conduct an online survey and the results show that a higher degree of TTF and VTF (Value-Technology Fit) resulted in a more positive attitude towards using the mobile app. SN and attitude had strong significant impacts on users’ continuance intention to use the app. However, TTF and VTF had no significant effect on the continuance intention to use the app.


Mobile apps Task-Technology Fit Value-Technology Fit Subjective norm 



This study is conducted under the ‟Smart LOHAS Service Development/Technology Applications and Multi-field Validation Project (2/4)” of the Institute for Information Industry which is financially supported by the Ministry of Economy Affairs of the Republic of China.


  1. 1.
    Ajzen, I., Fishbein, M.: Understanding Attitudes and Predicting Social Behavior. Prentice-Hall, Englewood Cliffs (1980)Google Scholar
  2. 2.
    Bohlen, J.M.: The adoption and diffusion of ideas in agriculture. In: Copp, James H. (ed.) Our Changing Rural Society: Perspectives and Trends, pp. 265–287. Iowa State University Press, Ames (1964)Google Scholar
  3. 3.
    Bohlen, J.M.: Research needed on adoption models. In.: Diffusion Research Needs. Columbia: Missouri Agricultural Experiment Station, North Central Regional Research Bulletin, vol. 186, pp. 15–21 (1968)Google Scholar
  4. 4.
    Clarke, I.: Emerging value propositions for M-Commerce. J. Bus. Strat. 18(2), 133–147 (2001)Google Scholar
  5. 5.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–342 (1989)CrossRefGoogle Scholar
  6. 6.
    Dennis, A.R., Wixom, B.H., Vandenberg, R.J.: Understanding fit and appropriation effects in group support systems via meta-analysis. MIS Q. 25(2), 167–193 (2001)CrossRefGoogle Scholar
  7. 7.
    Fishbein, M., Ajzen, I.: Belief, Attitude, Intentions and Behavior: An Introduction to Theory and Research. Addison-Wesley, MA (1975)Google Scholar
  8. 8.
    Goodhue, D.L.: Understanding user evaluations of information systems. Manage. Sci. 41(12), 1827–1844 (1995)CrossRefGoogle Scholar
  9. 9.
    Goodhue, D.L.: Development and measurement validity of a task-technology fit instrument for user evaluations of information systems. Decis. Sci. 29(1), 105–138 (1998)CrossRefGoogle Scholar
  10. 10.
    Goodhue, D.L., Thompson, R.L.: Task-technology fit and individual performance. MIS Q. 19(2), 213–236 (1995)CrossRefGoogle Scholar
  11. 11.
    Govers, P.C.M.: Product Personality. Unpublished doctoral dissertation, University of Delft, Delft (2004)Google Scholar
  12. 12.
    Gotzsch, J.: Managing product expressions: Identifying conditions and methods for the creation of meaningful consumer home products. Unpublished doctoral dissertation, Brunel University, London (2003)Google Scholar
  13. 13.
    Kandinsky, W.: Concerning the Spiritual in Art. Online Distributed Proofreaders. Retrieved from Project Gutenberg, Oxford (1977)Google Scholar
  14. 14.
    Klonglan, G.E., Coward, E.W.: The concept of symbolic adoption: a suggested interpretation. Rural Sociol. 35(1), 77–83 (1970)Google Scholar
  15. 15.
    Kreitler, H., Kreitler, S.: Psychology of the Arts. Duke University Press, Durham (1972)Google Scholar
  16. 16.
    Liang, T.P., Wei, C.P.: Introduction to the special issue: a framework for mobile commerce applications. Int. J. Electron. Commer. 8(3), 7–17 (2004)Google Scholar
  17. 17.
    Lin Y.L., Liang, T.P., Ho, S.C., Yeh, Y.H.: The impact of situation influences on the intention to use mobile value-added services. In: Paper Presented at the 6th Workshop on e-Business (WeB2007), Montreal, 9 December 2007Google Scholar
  18. 18.
    Penny, G.: Use Mobile Apps to Provide Customer Value, and Revenue Will Follow. Gartner (2014)Google Scholar
  19. 19.
    Rogers, E.M.: A communication research approach to the diffusion of innovations. In: Diffusion Research Needs, Columbia: Missouri Agricultural Experiment Station, North Central Regional Research Bulletin, vol. 186, pp. 27–30 (1968)Google Scholar
  20. 20.
    Shiau, W.L., Liou, T.R.: Understanding the effects of consumer’s value technology fit on a mobile shopping website: the case of Rakuten Ichiba. In: Pacific Asia Conference on Information Systems (PACIS 2014)Google Scholar
  21. 21.
    Stuart, D.: Mobile apps revenues tipped to reach $26bn in 2013. the guardian (2013).
  22. 22.
    Sian, R.: Over 160 Billion Consumer Apps to be Downloaded in 2017, Driven by Free-To-Play Games. Juniper Research (2013).
  23. 23.
    Tornatzky, L.G., Fleischer, M.: The Processes of Technological Innovation. Lexington Books, Lexington (1990)Google Scholar
  24. 24.
    Wang, W.T., Wang, B., Wei, Y.T.: Examining the impacts of website complexities on user satisfaction based on the task-technology fit model: an experimental research using an eye-tracking device. In: Pacific Asia Conference on Information Systems (PACIS 2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Innovative DigiTech-Enabled Applications and Services InstituteInstitute for Information IndustryTaiwanRepublic of China
  2. 2.Service Systems Technology CenterIndustrial Technology Research InstituteTaiwanRepublic of China

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