Electronic Markets

, Volume 24, Issue 1, pp 57–66 | Cite as

Understanding Chinese users’ continuance intention toward online social networks: an integrative theoretical model

  • Yuan Sun
  • Ling Liu
  • Xinmin Peng
  • Yi Dong
  • Stuart J. Barnes
General Research

Abstract

This study explores users’ continuance intention in online social networks by synthesizing Bhattacherjee’s IS continuance theory with flow theory, social capital theory, and the unified theory of acceptance and use of technology (UTAUT) to consider the special hedonic, social and utilitarian factors in the online social network environment. The integrated model was empirically tested with 320 online social network users in China. The results indicated that continuance intention was explained substantially by all hypothesized antecedents including perceived enjoyment, perceived usefulness, usage satisfaction, effort expectancy, social influence, tie strength, shared norms and trust. Based on the research findings, we offer discussions of both theoretical and practical implications.

Keywords

Online social network Continuance intention IS continuance theory Flow theory UTAUT Social capital theory 

JEL classification

M19 - Other 

References

  1. Baker, R. K., & White, K. M. (2010). Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective. Computers in Human Behavior, 26(6), 1591–1597.CrossRefGoogle Scholar
  2. Benbasat, I., & Zmud, R. W. (2003). The identity crisis within the is discipline: defining and communicating the discipline’s core properties. MIS Quarterly, 27(2), 183–194.Google Scholar
  3. Bhattacherjee, A. (2001a). Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351–370.CrossRefGoogle Scholar
  4. Bhattacherjee, A. (2001b). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214.CrossRefGoogle Scholar
  5. Boyd, D. M., & Ellison, N. B. (2008). Social network sites: definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230.CrossRefGoogle Scholar
  6. Butler, B. S. (2001). Membership size, communication activity, and sustainability: a resource-based model of online social structures. Information Systems Research, 12(4), 346–362.CrossRefGoogle Scholar
  7. Coleman, J. S. (1990). Foundations of social theory. Cambridge, MA: Harvard University Press.Google Scholar
  8. Csikszentmihalyi, M. (1977). Beyond boredom and anxiety. San Francisco: Jossey-Bass.Google Scholar
  9. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.CrossRefGoogle Scholar
  10. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003.CrossRefGoogle Scholar
  11. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132.CrossRefGoogle Scholar
  12. Deng, Z., Lu, Y., Wei, K. K., & Zhang, J. (2010). Understanding customer satisfaction and loyalty: an empirical study of mobile instant messages in china. International Journal of Information Management, 30(4), 289–300.CrossRefGoogle Scholar
  13. Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80.CrossRefGoogle Scholar
  14. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRefGoogle Scholar
  15. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and tam in online shopping: an integrated model. MIS Quarterly, 27(1), 51–90.Google Scholar
  16. Granovetter, M. S. (1973). The strength of weak ties. The American Journal of Sociology, 78(6), 1360–1380.CrossRefGoogle Scholar
  17. He, W., Qiao, Q., & Wei, K.-K. (2009). Social relationship and its role in knowledge management systems usage. Information & Management, 46(3), 175–180.CrossRefGoogle Scholar
  18. Helliwell, J. F., & Putnam, R. D. (2004). The social context of well-being. Philosophical Transactions of the Royal Society B: Biological Sciences, 359(1449), 1435–1446.CrossRefGoogle Scholar
  19. Hu, T., & Kettinger, W. J. (2008). Why people continue to use social networking services: Developing a comprehensive model. Twenty Ninth International Conference on Information Systems, Paris, 1–11.Google Scholar
  20. Kang, Y., & Lee, H. (2010). Understanding the role of an it artifact in online service continuance: an extended perspective of user satisfaction. Computers in Human Behavior, 26(3), 353–364.CrossRefGoogle Scholar
  21. Kim, B. (2011). Understanding antecedents of continuance intention in social-networking services. Cyberpsychology, Behavior and Social Networking, 14(4), 199–205.CrossRefGoogle Scholar
  22. Kwon, O., & Wen, Y. (2010). An empirical study of the factors affecting social network service use. Computers in Human Behavior, 26(2), 254–263.CrossRefGoogle Scholar
  23. Levin, D. Z., & Cross, R. (2004). The strength of weak ties you can trust: the mediating role of trust in effective knowledge transfer. Management Science, 50(11), 1477–1490.CrossRefGoogle Scholar
  24. Liao, C., Palvia, P., & Lin, H. N. (2010). Stage antecedents of consumer online buying behavior. Electronic Markets, 20(1), 53–65.CrossRefGoogle Scholar
  25. Limayem, M., & Cheung, C. M. K. (2008). Understanding information systems continuance: the case of internet-based learning technologies. Information & Management, 45(4), 227–232.CrossRefGoogle Scholar
  26. Lin, C. P., & Bhattacherjee, A. (2008). Learning online social support: an investigation of network information technology based on utaut. Cyberpsychology & Behavior, 11(3), 268–272.CrossRefGoogle Scholar
  27. Lin, K.-Y., & Lu, H.-P. (2011). Why people use social networking sites: an empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27(3), 1152–1161.CrossRefGoogle Scholar
  28. Loebbecke, C., Powell, P., & Weiss, T. (2010). Repeated use of online auctions: investigating individual seller motivations. Electronic Markets, 20(2), 105–117.CrossRefGoogle Scholar
  29. Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709–734.Google Scholar
  30. Mcknight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: an integrative typology. Information Systems Research, 13(3), 334–359.CrossRefGoogle Scholar
  31. Mishra, A. K. (1996). Organizational responses to crisis: The centrality of trust. In R. M. Kramer & T. R. Tyler (Eds.), Trust in organizations: Frontiers of theory and research (pp. 261–287). Thousand Oaks: Sage.CrossRefGoogle Scholar
  32. Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of management review, 23(2), 242–266.Google Scholar
  33. Nielsen Company, Inc. (2009). Global faces and networked places: a Nielsen report on social networking’s new global footprint. New York: The Nielsen Company [http://www.nielsen.com/us/en/newswire/2009/social-networking-new-global-footprint.html].
  34. Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill.Google Scholar
  35. Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of Retailing, 57(3), 25–48.Google Scholar
  36. Powell, J. (2009). 33 million people in the room: How to create, influence, and run a successful business with social networking. New Jersey: FT Press.Google Scholar
  37. Putnam, R. D., Leonardi, R., & Nanetti, R. Y. (1993). Making democracy work: Civic traditions in modern italy. Princeton: Princeton University Press.Google Scholar
  38. Reagans, R., & Mcevily, B. (2003). Network structure and knowledge transfer: the effects of cohesion and range. Administrative Science Quarterly, 48(2), 240–267.CrossRefGoogle Scholar
  39. Sharp, H., Rogers, Y., & Preece, J. (2007). Interaction design: Beyond human computer interaction. England: John Wiley & Sons.Google Scholar
  40. Shi, N., Lee, M., Cheung, C., & Chen, H., (2010). The continuance of online social networks: How to keep people using facebook? 43rd Hawaii International Conference on System Sciences, Hawaii IEEE Computer Society, 1–10.Google Scholar
  41. Sledgianowski, D., & Kulviwat, S. (2009). Using social network sites: the effects of playfulness, critical mass and trust in a hedonic context. The Journal of Computer Information Systems, 49(4), 74–83.Google Scholar
  42. Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: the role of intrafirm networks. Academy of Management Journal, 41(4), 464–476.CrossRefGoogle Scholar
  43. van Der Heijden, H. (2004). User acceptance of hedonic information systems. Management Information Systems Quarterly, 28(4), 695–704.Google Scholar
  44. Vassileva, J. (2012). Motivating participation in social computing applications: a user modeling perspective. User Modeling and User-Adapted Interaction, 22(1–2), 177–201.CrossRefGoogle Scholar
  45. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.CrossRefGoogle Scholar
  46. Venkatesh, V., & Brown, S. A. (2001). A longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges. MIS Quarterly, 25(1), 71–102.CrossRefGoogle Scholar
  47. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.Google Scholar

Copyright information

© Institute of Information Management, University of St. Gallen 2013

Authors and Affiliations

  • Yuan Sun
    • 1
  • Ling Liu
    • 2
  • Xinmin Peng
    • 3
  • Yi Dong
    • 4
  • Stuart J. Barnes
    • 5
  1. 1.School of Business AdministrationZhejiang Gongshang UniversityHangzhouPeople’s Republic of China
  2. 2.Department of Accounting and FinanceUniversity of Wisconsin-Eau ClaireEau ClaireUSA
  3. 3.Department of Public Administration, School of LawZhejiang Wanli UniversityNingboPeople’s Republic of China
  4. 4.School of Banking and FinanceUniversity of International Business and EconomicsBeijingPeople’s Republic of China
  5. 5.Kent Business SchoolUniversity of KentKentUK

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