Online experiences and virtual goods purchase intention

Internet Research

Volumn 22, Issue 3, 2012, Pages 252-274

  Huang, Echo ^a  

^a NATIONAL KAOHSIUNG UNIVERSITY OF APPLIED SCIENCES   (Taiwan)

Author keywords

Customer behaviour; Flow; Interactivity; Involvement; Purchase intention; Social identity; Social networks; Virtual goods

Indexed keywords

EID: 84861830455     PISSN: 10662243     EISSN: None     Source Type: Journal    
DOI: 10.1108/10662241211235644     Document Type: Article

References (97)

1. Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review and recommended two-step approach”, Psychological Bulletin, Vol. 103 No. 3, pp. 411-23.
2. Animesh, A.P., Yang, S.B. and Oh, W. (2011), “An odyssey into virtual words: exploring the impacts of technological and spatial environments on intention to purchase virtual products”, MIS Quarterly, Vol. 35 No. 3, pp. 780-810.
3. Ariely, D. (2000), “Controlling the information flow: effects on consumers' decision making and preferences”, Journal of Consumer Research, Vol. 27 No. 2, pp. 233-48.
4. Arnett, D.B., German, S.D. and Hunt, S.D. (2003), “The identity salience model of relationship marketing success: the case of non-profit marketing”, Journal of Marketing, Vol. 67, pp. 89-105.
5. Bagozzi, R.P. and Dholakia, U.M. (2006), “Open source software user communities: a study of participation in Linux user groups”, Management Science, Vol. 52 No. 7, pp. 1099-115.
6. Bagozzi, R.P., Yi, Y. and Phillips, L. (1991), “Assessing construct validity in organizational research”, Administrative Science Quarterly, Vol. 36 No. 3, pp. 421-58.
7. BBC News (2009), “Sales of virtual goods boom in US”, available at: http://news.bbc.co.uk/2/hi/8320184.stm (accessed 5 June 2011).
8. Berger, C.R. and Calabrese, R.J. (1975), “Some explorations in initial interaction and beyond: toward a developmental theory of interpersonal communication”, Human Communication Research, Vol. 1 No. 2, pp. 99-112.
9. Blattberg, R.C. and Deighton, J. (1991), “Interactive marketing: exploiting the age of addressability”, Sloan Management Review, Vol. 3 No. 1, pp. 5-14.
10. Celsi, R.L. and Olson, J.C. (1988), “The role of involvement in attention and comprehension processes”, Journal of Consumer Research, Vol. 15 No. 2, pp. 210-24.
11. Cheung, C.M.K. and Lee, M.K.O. (2010), “A theoretical model of intentional social action in online social networks”, Decision Support Systems, Vol. 49, pp. 24-30.
12. Chiou, W.B., Wan, C.S. and Lee, H.Y. (2008), “Virtual experience vs. brochures in the advertisement of scenic spots: how cognitive preferences and order effects influence advertising effects on consumers”, Tourism Management, Vol. 29 No. 1, pp. 146-50.
13. Chou, T.J. and Ting, C.C. (2003), “The role of flow experience in cyber-game addiction”, Cyber Psychology & Behavior, Vol. 6 No. 6, pp. 63-675.
14. Cobb, C.J. and Hoyer, W.D. (1985), “Direct observation of search behavior in the purchase of two nondurable products”, Psychology & Marketing, Vol. 2, pp. 161-79.
15. Csikszentmihalyi, M. (1975a), “Play and intrinsic rewards”, Humanistic Psychology, Vol. 15 No. 3, pp. 41-63.
16. Csikszentmihalyi, M. (1975b), Beyond Boredom and Anxiety, Jossey-Bass, San Francisco, CA.
17. Csikszentmihalyi, M. and Csikszentmihalyi, I.S. (1988), “Introduction to Part IV”, in Csikszentmihalyi, M. and Csikszentmihalyi, I.S. (Eds), Optimal Experience: Psychological Studies of Flow in Consciousness, Cambridge University Press, New York, NY.
18. Dholakia, R.R. and Chiang, K.P. (2003), “Shoppers in cyberspace: are they from Venus or Mars and does it matter?”, Journal of Consumer Psychology, Vol. 13 No. 1, pp. 171-6.
19. Duncan, T. and Moriarty, S.E. (1998), “A communication-based marketing models for managing relationships”, Journal of Marketing, Vol. 62 No. 2, pp. 1-13.
20. Dutton, J.E., Dukerich, J.M. and Harquail, C.V. (1994), “Organizational images and member identification”, Administrative Science Quarterly, Vol. 39 No. 2, pp. 239-63.
21. Ellemers, N., Kortekaas, P. and Ouwerkerk, J.W. (1999), “Self-care categorization, commitment to the group, and group self-esteem as related but distinct aspects of social identity”, European Journal of Social Psychology, Vol. 29 Nos 2/3, pp. 371-89.
22. Eroglu, S.A., Machleit, K.A. and Davis, L.M. (2003), “Empirical testing of a model of online store atmospherics and shopper responses”, Psychology & Marketing, Vol. 20 No. 2, pp. 139-50.
23. Fornell, C. and Larcker, D.F. (1981), “Structural equation models with unobservable variables and measurement error: algebra and statistics”, Journal of Marketing Research, Vol. 18 No. 3, pp. 382-8.
24. Guo, Y. and Barnes, S. (2007), “Why people buy virtual items in virtual worlds with real money”, ACM SIGMIS Database, Vol. 38, pp. 69-76.
25. Guo, Y. and Barnes, S. (2009), “Virtual item purchase behavior in virtual worlds”, Electronic Commerce Research, Vol. 9, pp. 77-96.
26. Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis, 7th ed., Prentice Hall, Upper Saddle River, NJ.
27. Hoffman, D.L. and Novak, T.P. (2009), “Flow online: lessons learned and future prospects”, Journal of Interactive Marketing, Vol. 23 No. 1, pp. 23-34.
28. Hoffman, D.L. and Novak, T.P. (1996), “Marketing in hypermedia computer-mediated environments: conceptual foundations”, Journal of Marketing, Vol. 60 No. 3, pp. 50-68.
29. Hoffman, L.D., Novak, P.T. and Duhachek, A. (2003), “The influence of goal-directed and experiential activities on online flow experiences”, Journal of Consumer Psychology, Vol. 13 Nos 1/2, pp. 3-16.
30. Hsu, C.L. and Lu, H.P. (2004), “Why do people play on-line games? An extended TAM with social influences and flow experience”, Information & Management, Vol. 41 No. 7, pp. 853-68.
31. Hu, L.T. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives”, Structural Equation Modeling, Vol. 6 No. 1, pp. 1-55.
32. Huang, A.H., Yen, D.C. and Zhang, X. (2008), “Exploring the potential effects of emoticons”, Information & Management, Vol. 45, pp. 466-73.
33. Huang, M.-H. (2003), “Modeling virtual exploratory and shopping dynamics: an environmental psychology approach”, Information & Management, Vol. 41, pp. 39-47.
34. Jacoby, J. (2002), “Stimulus-organism-response reconsidered: an evolutionary step in modeling (consumer) behavior”, Journal of Consumer Psychology, Vol. 12 No. 1, pp. 51-7.
35. Jiang, Z., Chan, J., Tan, B.C.Y. and Chua, W.S. (2010), “Effects of interactivity on web site involvement and purchase intention”, Journal of the Association for Information Systems, Vol. 11 No. 1, pp. 34-59.
36. Jin, S.A. (2009), “Avatars mirroring the actual self versus projecting the ideal self: the effects of self-priming on interactivity and immersion in an exergame, Wii Fit”, Cyberpsychology & Behavior, Vol. 12 No. 6, pp. 761-8.
37. Johnson, G.J., Bruner, G.C. and Kumar, A. (2006), “Interactivity and its facets revisited”, Journal of Advertising, Vol. 35 No. 4, pp. 35-52.
38. Jung, Y. and Pawlowski, S. (2009), “Consuming bits: an exploratory study of user goals for virtual consumption”, ICIS 2009 Proceedings, p. 31, available at: http://aisel.aisnet.org/icis2009/31 (accessed 12 August 2011).
39. Kalakota, R. and Whinston, A.B. (1996), Frontiers of Electronic Commerce, Addison Wesley Longman, Redwood City, CA.
40. Kelman, H.C. (1958), “Compliance, identification, and internalization: three processes of attitude change”, Journal of Con?ict Resolution, Vol. 2 No. 1, pp. 51-60.
41. Keng, C.-J., Ting, H.-Y. and Chen, Y.-T. (2011), “Effects of virtual-experience combinations on consumer-related “sense of virtual community””, Internet Research, Vol. 21 No. 4, pp. 408-34.
42. Kim, H.W., Koh, J. and Lee, H.L. (2009), “Investigating the intention of purchasing digital items in virtual communities”, Proceedings of the Pacific Asia Conference on Information Systems, Hyderabad.
43. Kim, H.W., Gupta, S. and Koh, J. (2011), “Investigation the intention to purchase digital items in social networking communities: a customer value perspective”, Information & Management, Vol. 48, pp. 228-34.
44. Koufaris, M. (2002), “Applying the technology acceptance model and flow theory to online consumer behavior”, Information Systems Research, Vol. 13 No. 2, pp. 205-23.
45. Kwon, O. and Wen, Y. (2009), “An empirical study of the factors affecting social network service use”, Computers in Human Behaviour, Vol. 26 No. 2, pp. 254-63.
46. Lee, S.M. and Chen, L. (2010), “The impact of flow on online consumer behavior”, of Computer Information Systems, Summer, pp. 1-11.
47. Lehdonvirta, V. (2005), “Real-money trade of virtual assets: new strategies for virtual world operators”, Proceedings of the 2005 Conference on Future Play (Future Play 2005), Lansing, MI, 13-15 October, pp. 1-10.
48. Lehdonvirta, V. (2009), “Virtual item sales as a revenue model identifying attributes that drive purchase decisions”, Electronic Commerce Research, Vol. 9 Nos 1/2, pp. 97-113.
49. Li, H., Daugherty, T. and Biocca, F. (2002), “Impact of 3-D advertising on product knowledge, brand attitude, and purchase intention: the mediating role of presence”, Journal of Advertising, Vol. 31 No. 3, pp. 43-57.
50. Liu, Y. (2003), “Developing a scale to measure the interactivity of web sites”, Journal of Advertising Research, Vol. 43, pp. 207-16.
51. Liu, Y. and Shrum, L.J. (2009), “A dual-process model of interactivity effects”, Journal of Advertising, Vol. 38 No. 2, pp. 53-68.
52. Lowry, P.B., Spaulding, T., Wells, T., Moody, G., Moffit, K. and Madariaga, S. (2006), “A theoretical model and empirical results linking web site interactivity and usability satisfaction”, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS-39), Kauai, HI, p. 123a.
53. Lu, Y., Zhou, T. and Wang, B. (2008), “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.
54. Manganari, E.E., Siomkos, G.J., Rigopoulou, I.D. and Vrechopoulos, A.P. (2011), “Virtual store layout effects on consumer behaviour: applying an environmental psychology approach in the online travel industry”, Internet Research, Vol. 21 No. 3, pp. 326-46.
55. Markus, H.R. and Wurf, E. (1987), “The dynamic self-concept: a social-psychological perspective”, in Rosenzweig, M.R. and Porter, L.W. (Eds), Annual Review of Psychology, Annual Reviews, Palo Alto, CA, pp. 299-337.
56. Martin, J. (2008), “Consuming code: use-value, exchange-value, and the role of virtual goods in Second Life”, Journal of Virtual Worlds Research, Vol. 1 No. 2, pp. 1-21.
57. Mehrabian, A. and Russell, J.A. (1980s), “The mediating role of emotions in environmental psychology”, paper presented at Psychology and the Environment in the 1980s, symposium conducted at the University of Missouri, Columbia, MO.
58. Mittal, B. (1989), “Measuring purchase-decision involvement”, Psychology & Marketing, Vol. 6 No. 2, pp. 147-62.
59. Mittal, B. (1995), “A comparative analysis of four scales of involvement”, Psychology & Marketing, Vol. 12 No. 7, pp. 663-82.
60. Moon, J.W. and Kim, Y.G. (2001), “Extending the TAM for a world-wide-web context”, Information & Management, Vol. 38, pp. 217-30.
61. Nel, V., van Niekerk, R., Berthon, J. and Davies, T. (1999), “Going with the flow: web sites and customer involvement”, Internet Research: Electronic Networking Applications and Policy, Vol. 9 No. 2, pp. 109-16.
62. Nelson, R. (2011), “Journey of Moses for Facebook is a social take on the Old Testament”, available at: www.insidesocialgames.com/ (accessed 9 September 2011).
63. Nojima, M. (2007), “Pricing models and motivations for MMO play”, Proceedings of the DiGRA 2007 Conference, Tokyo, pp. 672-681.
64. Novak, T.P., Hoffman, D.L. and Yung, Y.F. (2000), “Measuring the customer experience in online environments: a structural modeling approach”, Marketing Science, Vol. 19 No. 1, pp. 22-44.
65. Nunnally, J. (1978), Psychometric Theory, McGraw-Hill, New York, NY.
66. Parboteeah, D.V., Valacich, J.S. and Wells, J.D. (2009), “The influence of web site characteristics on a consumer's urge to buy impulsively”, Information Systems Research, Vol. 20 No. 1, pp. 60-78.
67. Pavlou, P.A. and El Sawy, O.A. (2006), “From IT leveraging competence to competitive advantage in turbulent environments: the case of new product development”, Information Systems Research, Vol. 17 No. 3, pp. 198-227.
68. Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003), “Common method biases in behavioral research: a critical review of the literature and recommended remedies”, Journal of Applied Psychology, Vol. 88 No. 5, pp. 879-903.
69. Richins, M.L., Bloch, P.H. and McQuarrie, E.F. (1992), “How enduring and situational involvement combine to create involvement responses”, Journal of Consumer Psychology, Vol. 1 No. 2, pp. 143-53.
70. Rothschild, M.L. and Gaidis, W.C. (1981), “Behavioral learning theory: its relevance to marketing and promotions”, Journal of Marketing, Vol. 45 No. 2, pp. 70-8.
71. Sharma, R., Yetton, P. and Crawford, J. (2009), “Estimating the effect of common method variance: the method-method pair technique with an illustration from TAM research”, MIS Quarterly, Vol. 33 No. 3, pp. 473-90.
72. Sherman, C. (2010), “Plan Span and Magid: 13 percent of Americans buy virtual goods”, Engage Digital, available at: www.engagedigital.com/blog/2010/05/28/playspan-and-magid-13-of-americans-buy-virtual-goods/ (accessed 6 June 2011).
73. Siekpe, J.S. (2005), “An examination of the multidimensionality of flow construct in a computer-mediated environment”, Journal of Electronic Commerce Research, Vol. 6 No. 1, pp. 31-43.
74. Simon, B. (2004), Identity in Modern Society: A Social Psychological Perspective, Blackwell, Oxford.
75. Sohn, D. and Lee, B.K. (2005), “Dimensions of interactivity: differential effects of social and psychological factors”, Journal of Computer-Mediated Communication, Vol. 10 No. 3, available at: http://jcmc.indiana.edu/vol10/issue3/sohn.html.
76. Song, J. and Kim, Y.J. (2006), “Social influence process in the acceptance of a virtual community service”, Information Systems Frontiers, Vol. 8 No. 3, pp. 241-52.
77. Song, J.H. and Zinkhan, G.M. (2008), “Determinants of perceived web site interactivity”, Journal of Marketing, Vol. 72, pp. 99-113.
78. Tajfel, H. (1969), “Cognitive aspects of prejudice”, Journal of Social Issues, Vol. 25 No. 4, pp. 79-97.
79. Tajfel, H. (1972) in Moscovici, S. (Ed.), “La catégorisation sociale” (Social categorization), Introduction à la psychologie sociale, Vol. 1, Larousse, Paris, pp. 272-302.
80. Tajfel, H., Billig, M.G., Bundy, R.P. and Flament, C. (1971), “Social categorization and intergroup behavior”, European Journal of Social Psychology, Vol. 1 No. 2, pp. 149-78.
81. Trevino, L.K. and Webster, J. (1992), “Flow in computer-mediated communication”, Communication Research, Vol. 19 No. 5, pp. 539-73.
82. Turner, J.C. (1982), “Towards a cognitive redefinition of the social group”, in Tajfel, H. (Ed.), Social Identity and Intergroup Relationships, Cambridge University Press, Cambridge.
83. Vakratsas, D. and Ambler, T. (1999), “How advertising works: what do we really know?”, Journal of Marketing, Vol. 63 No. 1, pp. 26-43.
84. Walker, K. (2003), “It's difficult to hide it: the presentation of self on internet home pages”, Qualitative Sociology, Vol. 23 No. 1, pp. 99-120.
85. Wang, K., Wang, E.T.G. and Farn, C.K. (2009), “Influence of web advertising strategies, consumer goal-directedness, and consumer involvement on web advertising effectiveness”, International Journal of Electronic Commerce, Vol. 13 No. 4, pp. 67-95.
86. Wu, J.H. and Wang, S.C. (2005), “What drives mobile commerce? An empirical evaluation of the revised technology acceptance model”, Information & Management, Vol. 42 No. 5, pp. 719-29.
87. Yujong, H. (2008), “A preliminary examination of the factors for knowledge sharing in technology-mediated learning”, Journal of Information Systems Education, Vol. 19 No. 4, pp. 419-30.
88. Zaichkowsky, J.L. (1985), “Measuring the involvement construct”, Journal of Consumer Research, Vol. 12, pp. 341-54.
89. Zaichkowsky, J.L. (1986), “Conceptualizing involvement”, Journal of Advertising, Vol. 15 No. 6, pp. 1-14.
90. Zaichkowsky, J.L. (1994), “The personal involvement inventory: reduction, revision and application to advertising”, Journal of Advertising, Vol. 23 No. 4, pp. 59-70.
91. Zmud, R.W. and Boynton, A.C. (1991), “Survey measures and instruments in MIS: inventory and appraisal”, in Kraemer, K. (Ed.), The Information Systems Research Challenge: Survey Research Methods, Harvard Business School Press, Boston, MA, pp. 149-80.
92. Bagozzi, R.P. and Lee, K.H. (2002), “Multiple routes for social influence: the role of compliance, internalization, and social identity”, Social Psychology Quarterly, Vol. 65 No. 3, pp. 226-47.
93. Koufaris, M. (2002), “Applying the technology acceptance model and flow theory to online consumer behavior”, Information Systems Research, Vol. 13 No. 2, pp. 205-23.
94. Ma, A. and Agrarwal, R. (2007), “Through a glass darkly: information technology design, identity verification, and knowledge contribution in online communities”, Information Systems Research, Vol. 18 No. 1, pp. 42-67.
95. Park, J., Lennon, S.J. and Stoel, L. (2005), “On-line product presentation: effects on mood, perceived risk, and purchase intention”, Psychology & Marketing, Vol. 22 No. 9, pp. 695-719.
96. Premkumar, G. and Bhattacherjee, A. (2008), “Explaining information technology usage: a test of competing models”, Omega, Vol. 36 No. 1, pp. 64-75.
97. Taiwan Facebook Statistics (2011), available at: www.socialbakers.com/facebook-statistics/taiwan (accessed 20 November 2011).