Cited by 171Technology Adoption and User BehaviourHealth, Technology, Consumer BehaviorMobile and Web Applications

The DOI matches its Crossref record, with a small difference in title or year; 5 of the 5 references it cites were found in a registry or an index.

Antecedents of mobile app usage among smartphone users

Kim, Sang Chon, Yoon, Doyle, Han, Eun Kyoung·2016·Journal of Marketing Communications

Abstract

Although mobile apps are already an influential medium in the new media industry as a whole, these apps have received little academic attention within the communication and marketing literature. This study develops and tests a hypothesized model to explain antecedents affecting app usage among smartphone users. The analysis of the structural equation model determined a final model with four significant factors (perceived informative and entertaining usefulness, perceived ease of use, and user review). Cost-effectiveness, a key variable of this study due to the particularity of 99-cent app price, had no influence on app usage. This study not only includes marketing implications but also offers insight into various theoretical applications to the field of mobile communication research by suggesting a conceptual model for the acceptance of mobile apps.

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Cites

Research works printed but not linked: 34

  1. 10.1002/dir.10000 · DOI
  2. Bauer, H. H., S. J.Barnes, T.Reichardt, and M. M.Neuman. 2005. “Driving Consumer Acceptance of Mobile Marketing: A Theoretical Framework and Empirical Study.” Journal of Electronic Commerce Research6: 181–192.
  3. 10.2753/MIS0742-1222290107 · DOI
  4. 10.1177/002224378702400406 · DOI
  5. 10.1509/jmkr.43.3.345 · DOI · Paper page
  6. 10.2753/MIS0742-1222230207 · DOI
  7. 10.1016/j.jretai.2008.04.005 · DOI
  8. Fishbein M. and I.Ajzen. 1975. Belief Attitude Intention and Behavior: An Introduction to Theory and Research. Reading MA: Addison-Wesley.
  9. Fogelgren-Pedersen A. K. V. Anderson and C. Jelbo. 2003. “The Paradox of the Mobile Internet: Acceptance of Gadgets and Rejections of Innovations.”Paper presented at the 16th Bled eCommerce Conference eTransformation Bled June.
  10. 10.1002/mar.10045 · DOI
  11. 10.1016/j.jbusres.2009.01.015 · DOI
  12. Hanley, M., M.Becker, and J.Martinsen. 2006. “Factors Influencing Mobile Advertising Acceptance: Will Incentives Motivate College Student to Accept Mobile Advertisements?” International Journal of Mobile Marketing1: 50–58.
  13. 10.1016/S1567-4223(03)00008-5 · DOI
  14. Lella A.2013 November 5. “ComScore Reports September 2013 U.S. Smartphone Subscriber Market Share.” Accessed July 12 2014. https://www.comscore.com/Insights/Press-Releases/2013/11/comScore-Reports-September-2013-U.S.-Smartphone-Subscriber-Market-Share.
  15. 10.1177/002224379303000208 · DOI
  16. 10.2104/tja10059 · DOI
  17. 10.1016/S0378-7206(00)00061-6 · DOI · Paper page
  18. Nittala, R.2011. “Registering for Incentivized Mobile Advertising: Discriminant Analysis of Mobile Users.” International Journal of Mobile Marketing6: 42–53.
  19. 10.1177/0092070305276149 · DOI
  20. 10.2501/JAR-51-1-057-071 · DOI
  21. 10.1002/dir.20011 · DOI
  22. Pagani, M.2011. “When Usefulness Does Not Matter: Affective Versus Cognitive Components in the Adoption of Mobile TV Services.” International Journal of Mobile Marketing6: 5–27.
  23. 10.1016/j.jretai.2011.05.002 · DOI
  24. 10.2753/JEC1086-4415110405 · DOI
  25. Patel, K.2011, January 11. “Whatever 4G Means, the Ad Battle has Begun.” Ad Age. Accessed September 29, 2012. http://adage.com.
  26. Rogers E. M.2003. Diffusion of Innovations. New York: Free Press.
  27. Simmel G.1964. The Sociology of Georg Simmel edited by K. H. Wolff. New York: Free Press.
  28. 10.2307/1884852 · DOI · Paper page
  29. 10.1016/j.omega.2003.08.005 · DOI
  30. Yang, H., L.Zhou, and H.Liu. 2010. “A Comparative Study of American and Chinese Young Consumers' Acceptance of Mobile Advertising: A Structural Equation Modeling Approach.” International Journal of Mobile Marketing5: 60–76.
  31. 10.1080/15252019.2002.10722063 · DOI
  32. 10.2307/1251446 · DOI · Paper page
  33. 10.1002/mar.20239 · DOI
  34. 10.1509/jm.74.2.133 · DOI

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Metadata

Authors
Kim, S. C., Yoon, D., & Han, E. K.
Affiliations
  • University of Oklahoma (US)
  • Sungkyunkwan University (KR)
Corresponding author
Kim, Sang Chon
Venue
Journal of Marketing Communications
Published
2014-08-22
Volume
22
Issue
6
Pages
653-670
ISSN
  • 1352-7266 (ISSN-L)
  • 1466-4445
OpenAlex
W2000359217
Cited by
171
References
5
Citations by year
2026: 6 · 2025: 17 · 2024: 13 · 2023: 22 · 2022: 29 · 2021: 18 · 2020: 22 · 2019: 12 · 2018: 15 · 2017: 6 · 2016: 4 · 2015: 6 · 2014: 1
FWCI
10.81
Type
journal article
Language
en
Open access
closed
Locations
Journal of Marketing Communications (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
  • Physical Sciences › Computer Science › Information Systems › Mobile and Web Applications
Keywords
mobile app usage, smartphone users, perceived usefulness, perceived ease of use, online reviews, app pricing, cost-effectiveness, technology acceptance, new media, mobile communication

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