A Study on Antecedents of Game User Participation Intention in User Community in an Era of Convergence

융복합 시대 게임 사용자들의 유저 커뮤니티 참여 의도에 영향을 미치는 선행 요인에 관한 연구

  • Received : 2016.06.30
  • Accepted : 2016.08.20
  • Published : 2016.08.28


Several game developers or publishers adopt open innovation strategies to reduce R&D costs and increase user loyalty about their games. User communities play an important role in increasing users' interests in the game because they can share game information and skills in user communities. In this regard, this study explored key antecedents of game user participation intention in user community. We developed a research model by integrating perceived risk into theory of planned action. The theoretical model was tested by using survey data collected from 110 "Suddenattack" game users. Partial least squares (PLS) was utilized to analysis the research model. The findings of this study indicate that both perceived usefulness and perceived enjoyment play an important role in forming attitude toward community. However, contrast to our expectations, perceived risk has no signifiant effect on perceived usefulness, perceived enjoyment, attitude toward community and participation intention. While attention toward community significantly influences community participation intention, social norms are not significantly related to it. The analysis results help game developers or publishers establish effective strategies and policies to increase user participation intention in user community.


Online Game;User Community;Theory of Reasoned Action;Perceived Risk;Convergence


Grant : BK21플러스

Supported by : 영남대학교


  1. J. S. Kim, T. Y. Lee, T. G. Kim and H. W. Jung, “Studies on the development scheme and the current state of Korea game industry,” Journal of Digital Convergence, Vol. 13, No. 1, pp. 439-447, 2015.
  2. E. Von Hippel and G. Von Krogh, “Open source software and the private collective innovation model,” Organization Science, Vol. 14, No. 2, pp. 209-223, 2003.
  3. Y. S. Hau and Y. G. Kim, “Why would online gamers share their innovation-conductive knowledge in the online game user community? Integrating individual motivations and social capital perspectives,” Computer in Human Behavior, Vol. 27, No. 2, pp. 956-970, 2011.
  4. H. Cho, “Study on effect of characteristics of financial professionals on knowledge sharing, job satisfaction, and firm innovation,” Journal of Digital Convergence, Vol. 11, No. 10, pp. 225-240, 2013.
  5. D. S. Kwon and J. H. Kim, “An effects of self-determination theory on social presence in online community,” Journal of Digital Convergence, Vol. 9, No. 2, pp. 81-94, 2011.
  6. B. W. Yu and S. B. Park, “The effect of online game community efficiency on online game community commitment,” Korean Management Consulting Review, Vol. 9, No. 3, pp. 105-125, 2009.
  7. S. B. Park and N. H. Jung, “A factors affecting self presentation desire and participation intention in online game,” The E-Business Studies, Vol. 11, No. 5, pp. 291-308, 2010.
  8. J. H. Wi and I. S. Song, “An empirical study on community effect of MMORPG guild,” Journal of Korea Game Society, Vol. 10, No. 4, pp. 49-61, 2010.
  9. C. J. Yang, “Study on the juvenile culture of community within online game,” Korean Journal of Youth Studies, Vol. 13, No. 6, pp. 386-409, 2006.
  10. H. I. Kwon and Y. S. Choi, "A study on on-line game market segmentation classification and discrimination variable," Journal of the Korean Society for Computer Game, Vol. 14, pp. 53-61, 2008.
  11. Y. Han, S Shim, D., Kong, E. Hwang, S. Rim, “The impact of online game interactivity on user loyalty: Focused on the type of games,” Journal of Business Research, Vol. 28, No. 1, pp. 57-84, 2013.
  12. J. J. Jung, C. M. Chang and T. U. Kim, “An exploratory study for identifying key factors in online gamers development strategy utilizing Web community,” The KIPS transactions: PartD, Vol. 11D, No. 4, pp. 991-1002, 2004.
  13. G. P. Pisano and R. Verganti, “Which kind of collaboration is right for you?,” Harvard Business Review, Vol. 86, No. 12, pp. 78-86, 2008.
  14. E. H. Hwang, A Study on the Impact of Online Game Community Characteristics and Interactivity on User Satisfaction, Yeungnam University Master's Degree, 2009.
  15. M. Fishbein and I. Ajzen, Understanding Attitude and Predicting Social Behaviour, Prentice-Hall, Englewood Cliffs, NJ, 1980.
  16. I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, Vol. 50, No. 2, pp. 179-211, 1991.
  17. M. S. Yeom, “Understanding of showrooming behavior based on the theory of reasoned action,” Journal of Channel and Retailing, Vol. 20, No. 4, pp. 79-103, 2015.
  18. S. Hong, B. Li and B. Kim, “Consumer purchase decision in a mobile shopping mall: An integrative view of trust and theory of planned behavior,” Information Systems Review, Vol. 18, No. 2, pp. 151-171, 2016.
  19. E. J. Yang, “Study on the behavioral intention of Chinese cosmetic surgery tourists applied to the extended theory of reasoned action,” The Journal of Tourism Studies, Vol. 26, No. 2, pp. 127-151, 2014.
  20. L. S. L. Chen, “The impact of perceived risk, intangibility and consumer characteristics on online game playing,” Computers in Human Behavior, Vol. 26, No. 6, pp. 1607-1613, 2010.
  21. J. C. C. Lin and H. Lu, “Towards an understanding of the behaviour intention to use a web site,” International Journal of Information Management, Vol. 20, No. 3, pp. 197-208, 2000.
  22. K. Y. Lee, “Operation strategy in online knowledge sharing community,” The Journal of Society for e-Business Studies, Vol. 14, No. 4, pp. 95-118, 2009.
  23. V. Venkatesh and F. D. Davis, “A theoretical extension of the technology acceptance model: four longitudinal field studies,” Management Science, Vol. 46, No. 2, pp. 186-204, 1997.
  24. B. Kim and M. Kang, “Effect of MMS Addiction on user's health and academic performance in an era of convergence,” Journal of Digital Convergence, Vol. 14, No. 1, pp. 131-139, 2016.
  25. K. Yang, “Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior,” Journal of Retailing and Consumer Services, Vol. 19, No. 5, pp. 484-49, 2012.
  26. W. S. Jung and S. J. Yoon, “Predicting purchase intent on social commerce: Use of TPB(Theory of Planned Behavior), and TRI(Technology Readiness),” Journal of the Korea Service Management Society, Vol. 14, No. 2, pp. 1-24, 2013.
  27. J. F. Hair, G. T. M. Hult, C. M. Ringle and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage, Thousand Oaks, 2013.
  28. J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate Data Analysis, 7th Edition. London: Prentice Hall, 2009.
  29. C. Fornell and D. F. Larcker, “Evaluating structural evaluation models with unobservable variables and measurement error,” Journal of Marketing Research, Vol. 18, No. 1, pp. 39-50, 1981.