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Mobile Information Systems
Volume 2017, Article ID 3906953, 12 pages
https://doi.org/10.1155/2017/3906953
Research Article

An Extended Technology Acceptance Model for Mobile Social Gaming Service Popularity Analysis

1State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China
2School of Computer Science and Engineering, Beihang University, Beijing 100191, China
3Jacobs Institute, Cornell Tech, Cornell University, New York, NY, USA

Correspondence should be addressed to Wenge Rong; nc.ude.aaub@gnor.w

Received 23 September 2016; Accepted 1 December 2016; Published 3 January 2017

Academic Editor: Qingchen Zhang

Copyright © 2017 Hui Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. T. M. Connolly, E. A. Boyle, E. MacArthur, T. Hainey, and J. M. Boyle, “A systematic literature review of empirical evidence on computer games and serious games,” Computers & Education, vol. 59, no. 2, pp. 661–686, 2012. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Papastergiou, “Digital game-based learning in high school computer science education: impact on educational effectiveness and student motivation,” Computers & Education, vol. 52, no. 1, pp. 1–12, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. G.-J. Hwang and P.-H. Wu, “Advancements and trends in digital game-based learning research: a review of publications in selected journals from 2001 to 2010,” British Journal of Educational Technology, vol. 43, no. 1, pp. E6–E10, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. A. M. Piper, E. O'Brien, M. R. Morris, and T. Winograd, “SIDES: a cooperative tabletop computer game for social skills development,” in Proceedings of the ACM Conference on Computer Supported Cooperative Work, pp. 1–10, 2006.
  5. A. Barnett, E. Cerin, and T. Baranowski, “Active video games for youth: a systematic review,” Journal of Physical Activity and Health, vol. 8, no. 5, pp. 724–737, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. CNNIC, “35th statistical report on Internet development in China,” 2016, https://cnnic.com.cn/IDR/ReportDownloads/201604/P020160419390562421055.pdf.
  7. C. López-Nicolás, F. J. Molina-Castillo, and H. Bouwman, “An assessment of advanced mobile services acceptance: contributions from TAM and diffusion theory models,” Information & Management, vol. 45, no. 6, pp. 359–364, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. D. M. Boyd and N. B. Ellison, “Social network sites: definition, history, and scholarship,” Journal of Computer-Mediated Communication, vol. 13, no. 1, pp. 210–230, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Nikou and H. Bouwman, “Ubiquitous use of mobile social network services,” Telematics and Informatics, vol. 31, no. 3, pp. 422–433, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. PwC, “Mobile advertising in China: what do Chinese consumers want and how should businesses be engaging with them?” 2014, http://www.pwccn.com/webmedia/doc/635358539404587393_mobile_ad_china_cut_may2014.pdf.
  11. G. Schwabe and C. Göth, “Mobile learning with a mobile game: design and motivational effects,” Journal of Computer Assisted Learning, vol. 21, no. 3, pp. 204–216, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, vol. 13, no. 3, pp. 319–340, 1989. View at Publisher · View at Google Scholar · View at Scopus
  13. J. C.-C. Lin and H. Lu, “Towards an understanding of the behavioural intention to use a web site,” International Journal of Information Management, vol. 20, no. 3, pp. 197–208, 2000. View at Publisher · View at Google Scholar · View at Scopus
  14. J.-W. Moon and Y.-G. Kim, “Extending the TAM for a world-wide-web context,” Information & Management, vol. 38, no. 4, pp. 217–230, 2001. View at Publisher · View at Google Scholar · View at Scopus
  15. M. Koufaris, “Applying the technology acceptance model and flow theory to online consumer behavior,” Information Systems Research, vol. 13, no. 2, pp. 205–223, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “User acceptance of computer technology: a comparison of two theoretical models,” Management Science, vol. 35, no. 8, pp. 982–1003, 1989. View at Publisher · View at Google Scholar
  17. D.-H. Shin and Y.-J. Shin, “Why do people play social network games?” Computers in Human Behavior, vol. 27, no. 2, pp. 852–861, 2011. View at Publisher · View at Google Scholar · View at Scopus
  18. K.-Y. Lin and H.-P. Lu, “Why people use social networking sites: an empirical study integrating network externalities and motivation theory,” Computers in Human Behavior, vol. 27, no. 3, pp. 1152–1161, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. T.-P. Liang and Y.-H. Yeh, “Effect of use contexts on the continuous use of mobile services: the case of mobile games,” Personal and Ubiquitous Computing, vol. 15, no. 2, pp. 187–196, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. E. Park, S. Baek, J. Ohm, and H. J. Chang, “Determinants of player acceptance of mobile social network games: an application of extended technology acceptance model,” Telematics and Informatics, vol. 31, no. 1, pp. 3–15, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. M. Fishbein and I. Ajzen, Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison-Wesley, 1975.
  22. R. L. Thompson, C. A. Higgins, and J. M. Howell, “Personal computing: toward a conceptual model of utilization,” MIS Quarterly, vol. 15, no. 1, pp. 125–143, 1991. View at Publisher · View at Google Scholar · View at Scopus
  23. F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “Extrinsic and intrinsic motivation to use computers in the workplace,” Journal of Applied Social Psychology, vol. 22, no. 14, pp. 1111–1132, 1992. View at Publisher · View at Google Scholar
  24. V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: toward a unified view,” MIS Quarterly, vol. 27, no. 3, pp. 425–478, 2003. View at Google Scholar · View at Scopus
  25. I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179–211, 1991. View at Publisher · View at Google Scholar · View at Scopus
  26. Q. Wang and X. Sun, “Investigating gameplay intention of the elderly using an extended technology acceptance model (ETAM),” Technological Forecasting and Social Change, vol. 107, pp. 59–68, 2016. View at Publisher · View at Google Scholar · View at Scopus
  27. C.-L. Hsu and H.-P. Lu, “Why do people play on-line games? An extended TAM with social influences and flow experience,” Information & Management, vol. 41, no. 7, pp. 853–868, 2004. View at Publisher · View at Google Scholar · View at Scopus
  28. M.-C. Lee, “Understanding the behavioural intention to play online games: an extension of the theory of planned behaviour,” Online Information Review, vol. 33, no. 5, pp. 849–872, 2009. View at Publisher · View at Google Scholar · View at Scopus
  29. M. Lee and T. Tsai, “What drives people to continue to play online games? An extension of technology model and theory of planned behavior,” International Journal of Human-Computer Interaction, vol. 26, no. 6, pp. 601–620, 2010. View at Publisher · View at Google Scholar
  30. J. Wu and D. Liu, “The effects of trust and enjoyment on intention to play online games,” Journal of Electronic Commerce Research, vol. 8, no. 2, pp. 128–140, 2007. View at Google Scholar
  31. Y. Liu and H. Li, “Exploring the impact of use context on mobile hedonic services adoption: an empirical study on mobile gaming in China,” Computers in Human Behavior, vol. 27, no. 2, pp. 890–898, 2011. View at Publisher · View at Google Scholar · View at Scopus
  32. I. Ha, Y. Yoon, and M. Choi, “Determinants of adoption of mobile games under mobile broadband wireless access environment,” Information & Management, vol. 44, no. 3, pp. 276–286, 2007. View at Publisher · View at Google Scholar · View at Scopus
  33. K. Petrova and H. Qu, “Playing mobile games: consumer perceptions: an empirical study,” in Proceedings of the International Conference on e-Business, pp. 209–214, 2007.
  34. K.-Y. Lin and H.-P. Lu, “Predicting mobile social network acceptance based on mobile value and social influence,” Internet Research, vol. 25, no. 1, pp. 107–130, 2015. View at Publisher · View at Google Scholar · View at Scopus
  35. S. J. Kwon, E. Park, and K. J. Kim, “What drives successful social networking services? A comparative analysis of user acceptance of Facebook and Twitter,” The Social Science Journal, vol. 51, no. 4, pp. 534–544, 2014. View at Publisher · View at Google Scholar · View at Scopus
  36. P. Rosen and P. Sherman, “Hedonic information systems: acceptance of social networking websites,” in Proceedings of the 12th Americas Conference on Information Systems, p. 162, Acapulco, Mexico, August 2006.
  37. D. Sledgianowski and S. Kulviwat, “Social network sites: antecedents of user adoption and usage,” in Proceedings of the 14th Americas Conference on Information Systems, p. 83, Toronto, Canada, August 2008.
  38. O. Kwon and Y. Wen, “An empirical study of the factors affecting social network service use,” Computers in Human Behavior, vol. 26, no. 2, pp. 254–263, 2010. View at Publisher · View at Google Scholar · View at Scopus
  39. R. Rauniar, G. Rawski, J. Yang, and B. Johnson, “Technology acceptance model (TAM) and social media usage: an empirical study on Facebook,” Journal of Enterprise Information Management, vol. 27, no. 1, pp. 6–30, 2014. View at Publisher · View at Google Scholar · View at Scopus
  40. Y. Kim, D. Sohn, and S. M. Choi, “Cultural difference in motivations for using social network sites: a comparative study of American and Korean college students,” Computers in Human Behavior, vol. 27, no. 1, pp. 365–372, 2011. View at Publisher · View at Google Scholar · View at Scopus
  41. C. Feijoo, J.-L. Gómez-Barroso, J.-M. Aguado, and S. Ramos, “Mobile gaming: industry challenges and policy implications,” Telecommunications Policy, vol. 36, no. 3, pp. 212–221, 2012. View at Publisher · View at Google Scholar
  42. A. Voida and S. Greenberg, “Wii all play: the console game as a computational meeting place,” in Proceedings of the 27th International Conference on Human Factors in Computing Systems, pp. 1559–1568, Boston, Mass, USA, April 2009.
  43. J. Kim, Y. Chang, and M. Park, “Why do people like to play social network games with their friends? A focus on sociability and playability,” in Proceedings of the 17th Pacific Asia Conference on Information Systems, p. 78, 2013.
  44. J. Hamari and L. Keronen, “Why do people buy virtual goods? A literature review,” in Proceedings of the 49th Hawaii International Conference on System Sciences, pp. 1358–1367, Koloa, Hawaii, USA, January 2016.
  45. T. Lin, H. Lu, H. Hsu, S. Hsing, and T. Ho, “Why do people continue to play social network game (SNG)? An empirical study by social and emotional perspectives,” International Journal of E-Adoption, vol. 5, no. 4, pp. 22–35, 2013. View at Publisher · View at Google Scholar
  46. P.-S. Wei and H.-P. Lu, “Why do people play mobile social games? An examination of network externalities and of uses and gratifications,” Internet Research, vol. 24, no. 3, pp. 313–331, 2014. View at Publisher · View at Google Scholar · View at Scopus
  47. Y. Ding, Y. Zhou, and A. Kankanhalli, “Why do I invite friends to join: an empirical study of mobile social network game,” in Proceedings of the 18th Pacific Asia Conference on Information Systems, p. 137, June 2014.
  48. Q. Zhang, L. T. Yang, and Z. Chen, “Privacy preserving deep computation model on cloud for big data feature learning,” IEEE Transactions on Computers, vol. 65, no. 5, pp. 1351–1362, 2016. View at Publisher · View at Google Scholar · View at MathSciNet
  49. S. Trepte, L. Reinecke, and K. Juechems, “The social side of gaming: how playing online computer games creates online and offline social support,” Computers in Human Behavior, vol. 28, no. 3, pp. 832–839, 2012. View at Publisher · View at Google Scholar · View at Scopus
  50. O. Curry, S. G. B. Roberts, and R. I. M. Dunbar, “Altruism in social networks: evidence for a ‘kinship premium’,” British Journal of Psychology, vol. 104, no. 2, pp. 283–295, 2013. View at Publisher · View at Google Scholar · View at Scopus
  51. P. Legris, J. Ingham, and P. Collerette, “Why do people use information technology? A critical review of the technology acceptance model,” Information & Management, vol. 40, no. 3, pp. 191–204, 2003. View at Publisher · View at Google Scholar · View at Scopus
  52. J. Doll and I. Ajzen, “Accessibility and stability of predictors in the theory of planned behavior,” Journal of Personality and Social Psychology, vol. 63, no. 5, pp. 754–765, 1992. View at Publisher · View at Google Scholar · View at Scopus
  53. H. van der Heijden, “Factors influencing the usage of websites: the case of a generic portal in The Netherlands,” Information & Management, vol. 40, no. 6, pp. 541–549, 2003. View at Publisher · View at Google Scholar · View at Scopus
  54. L. van de Wijngaert and H. Bouwman, “Would you share? Predicting the potential use of a new technology,” Telematics and Informatics, vol. 26, no. 1, pp. 85–102, 2009. View at Publisher · View at Google Scholar · View at Scopus
  55. N. Mallat, “Exploring consumer adoption of mobile payments—a qualitative study,” The Journal of Strategic Information Systems, vol. 16, no. 4, pp. 413–432, 2007. View at Publisher · View at Google Scholar · View at Scopus
  56. M. Csikszentmihalyi and I. Csikszentmihalyi, Optimal Experience: Psychological Studies of Flow in Consciousness, Cambridge University Press, 2000.
  57. Y. Lu, T. Zhou, and B. Wang, “Exploring Chinese users' acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory,” Computers in Human Behavior, vol. 25, no. 1, pp. 29–39, 2009. View at Publisher · View at Google Scholar · View at Scopus
  58. M. Csikszentmihalyi and J. LeFevre, “Optimal experience in work and leisure,” Journal of Personality and Social Psychology, vol. 56, no. 5, pp. 815–822, 1989. View at Publisher · View at Google Scholar · View at Scopus
  59. J. A. Ghani, “Human factors in information systems,” in Flow in Human-Computer Interactions: Test of a Model, J. M. Carey, Ed., pp. 291–311, Ablex, 1995. View at Google Scholar
  60. D. Li and G. J. Browne, “The role of need for cognition and mood in online flow experience,” Journal of Computer Information Systems, vol. 46, no. 3, pp. 11–17, 2006. View at Google Scholar · View at Scopus
  61. D. Choi and J. Kim, “Why people continue to play online games: in search of critical design factors to increase customer loyalty to online contents,” CyberPsychology & Behavior, vol. 7, no. 1, pp. 11–24, 2004. View at Publisher · View at Google Scholar · View at Scopus
  62. M. C. Ashton, S. V. Paunonen, E. Helmes, and D. N. Jackson, “Kin altruism, reciprocal altruism, and the big five personality factors,” Evolution and Human Behavior, vol. 19, no. 4, pp. 243–255, 1998. View at Publisher · View at Google Scholar · View at Scopus
  63. H. Rachlin, “Altruism and selfishness,” Behavioral and Brain Sciences, vol. 25, no. 2, pp. 239–250, 2002. View at Publisher · View at Google Scholar · View at Scopus
  64. N. Folbre and R. E. Goodin, “Revealing altruism,” Review of Social Economy, vol. 62, no. 1, pp. 1–25, 2004. View at Publisher · View at Google Scholar · View at Scopus
  65. S. H. Burton, R. G. Morris, C. G. Giraud-Carrier, J. H. West, and R. Thackeray, “Mining useful association rules from questionnaire data,” Intelligent Data Analysis, vol. 18, no. 3, pp. 479–494, 2014. View at Publisher · View at Google Scholar · View at Scopus
  66. Y. Hong and Y. Li, “The research on index system optimization of graduation design based on cronbach coefficient,” in Proceedings of the 5th International Conference on Computer Science and Education, pp. 1843–1845, Hefei, China, August 2010. View at Publisher · View at Google Scholar · View at Scopus
  67. B. Williams, A. Onsman, and T. Brown, “Exploratory factor analysis: a five-step guide for novices,” Australasian Journal of Paramedicine, vol. 8, no. 3, 2010. View at Google Scholar
  68. C.-L. Hsu and H.-P. Lu, “Consumer behavior in online game communities: a motivational factor perspective,” Computers in Human Behavior, vol. 23, no. 3, pp. 1642–1659, 2007. View at Publisher · View at Google Scholar · View at Scopus
  69. H. van der Heijden, M. Ogertschnig, and L. van der Gaast, “Effects of context relevance and perceived risk on user acceptance of mobile information services,” in Proceedings of the 13th European Conference on Information Systems, pp. 286–296, 2005.