Skip to main content
Log in

Virtual world brand experience and its impact on real world purchasing behavior

  • Original Article
  • Published:
Journal of Brand Management Aims and scope Submit manuscript

Abstract

Using survey data from registered users of the popular virtual world Second Life, this research extends the theory of planned behavior model. In addition to the theory's basic predictors (attitudes, subjective norms and perceived control), the extended model includes virtual world brand experience, self-image congruence and perceived diagnosticity to improve the model's predictive power for explaining how virtual world brand experience affects real world purchase intentions and behavior. The study results show that virtual world brand experience has an impact on real world purchasing intentions and behaviors, and this relationship is moderated by self-image congruence and perceived diagnosticity. When a virtual world brand experience is considered to be helpful for evaluation and is consistent with the consumer's self-concept, the experience is found to have a stronger influence on real world purchase intentions and behavior. Overall, the findings indicate that multichannel effects exist between virtual world brand experiences and real world purchasing decisions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1

Similar content being viewed by others

References

  • Aiken, L.S. and West, S.G. (1991) Multiple Regression: Testing and Interpreting Interactions. Newbury Park, CA: Sage.

    Google Scholar 

  • Ajzen, I. (1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes 50 (2): 179–211.

    Article  Google Scholar 

  • Ajzen, I. (2002) Residual effects of past on later behavior: Habituation and reasoned action perspectives. Personality and Social Psychology Review 6 (2): 107–122.

    Article  Google Scholar 

  • Arakji, Y.R. and Lang, K.R. (2008) Avatar business value analysis: A method for the evaluation of business value creation in virtual commerce. Journal of Electronic Commerce Research 9 (3): 207–218.

    Google Scholar 

  • Armitage, C.J. and Conner, M. (2001) Efficacy of the theory of planned behavior: A meta-analytic review. British Journal of Social Psychology 40 (4): 471–499.

    Article  Google Scholar 

  • Bamberg, S., Ajzen, I. and Schmidt, P. (2003) Choice of travel mode in the theory of planned behavior: The roles of past behavior, habit, and reasoned action. Basic and Applied Social Psychology 25 (3): 175–187.

    Article  Google Scholar 

  • Baron, R.M. and Kenny, D.A. (1986) The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51 (6): 1173–1182.

    Article  Google Scholar 

  • Brakus, J.J., Schmitt, B.H. and Zarantonello, L. (2009) Brand experience: What is it? How is it measured? Does it affect loyalty? Journal of Marketing 73 (3): 52–68.

    Article  Google Scholar 

  • Chattopadhyay, A. and Laborie, J.L. (2005) Managing brand experience: The market contact audit. Journal of Advertising Research 45 (1): 9–16.

    Article  Google Scholar 

  • Chebat, J., Sirgy, J.M. and St-James, V. (2006) Upscale image transfer from malls to stores: A self-image congruence explanation. Journal of Business Research 59 (12): 1288–1296.

    Article  Google Scholar 

  • Clemons, E. (2008) The complex problem of monetizing virtual electronic social networks. Decision Support Systems 48 (1): 46–56.

    Article  Google Scholar 

  • Conner, M. and Sparks, P. (1996) The Theory of Planned Behaviour and Health Behaviors. Buckingham, England: Open University Press, pp. 121–162.

    Google Scholar 

  • Conner, M., Warren, R., Close, S. and Sparks, P. (1999) Alcohol consumption and the theory of planned behavior: An examination of the cognitive mediation of past behavior. Journal of Applied Social Psychology 29 (8): 1676–1704.

    Article  Google Scholar 

  • Griffith, D.A. and Chen, Q. (2004) The influence of virtual direct experience (VDE) on on-line ad message effectiveness. Journal of Advertising 33 (1): 55–68.

    Article  Google Scholar 

  • Hair Jr, J.F., Anderson, R., Tatham, R. and Black, W.C. (1998) Multivariate Data Analysis. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Hamilton, K. and White, K.M. (2008) Extending the theory of planned behavior: The role of self and social influences in predicting adolescent regular moderate-to-vigorous physical activity. Journal of Sport & Exercise Psychology 30 (1): 56–74.

    Article  Google Scholar 

  • Holzwarth, M., Janiszewski, C. and Neumann, M.N. (2006) The influence of avatars on online consumer shopping behavior. Journal of Marketing 70 (4): 19–36.

    Article  Google Scholar 

  • Jiang, Z. and Benbasat, I. (2005) Virtual product experience: Effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. Journal of Management Information Systems 21 (3): 111–147.

    Google Scholar 

  • Kempf, D.S. and Smith, R.E. (1998) Consumer processing of product trial and the influence of prior advertising: A structural modeling approach. Journal of Marketing Research 35 (3): 325–338.

    Article  Google Scholar 

  • Kressmann, F., Sirgy, J.M., Herrmann, A., Huber, F., Huber, S. and Lee, D.J. (2006) Direct and indirect effects of self-image congruence on brand loyalty. Journal of Business Research 59 (9): 955–964.

    Article  Google Scholar 

  • Kwon, W. and Lennon, S.J. (2009) Reciprocal effects between multichannel retailers’ offline and online brand images. Journal of Retailing 85 (3): 376–390.

    Article  Google Scholar 

  • KZero Consulting. (2007) 5 rules for virtual brand management, http://www.brandchannel.com/images/papers/359_5_rules_v1.pdf, accessed 29 March 2011.

  • Li, H., Daugherty, T. and Biocca, F. (2001) Characteristics of virtual experience in electronic commerce: A protocol analysis. Journal of Interactive Marketing 15 (3): 13–30.

    Article  Google Scholar 

  • 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 31 (3): 43–57.

    Article  Google Scholar 

  • Pavlou, P.A. and Fygenson, M. (2006) Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly 30 (1): 115–143.

    Google Scholar 

  • Podsakoff, P., MacKenzie, S., Lee, J. and Podsakoff, N. (2003) Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88 (5): 879–903.

    Article  Google Scholar 

  • Sirgy, J.M. et al (1997) Assessing the predictive validity of two methods of measuring self-image congruence. Journal of the Academy of Marketing Science 25 (3): 229–241.

    Article  Google Scholar 

  • Smith, J.R., Terry, D.J., Manstead, A.S., Louis, W.R., Kotterman, D. and Wolfs, J. (2007) Interaction effects in the theory of planned behavior: The interplay of self-identity and past behavior. Journal of Applied Social Psychology 37 (11): 2726–2750.

    Article  Google Scholar 

  • Sparks, P. and Guthrie, C.A. (1998) Self-identity and the theory of planned behaviour: A useful addition of an unhelpful artifice? Journal of Applied Social Psychology 28 (15): 1393–1410.

    Article  Google Scholar 

  • Suh, K. and Lee, Y. (2005) The effects of virtual reality on consumer learning: An empirical investigation. MIS Quarterly 29 (4): 673–697.

    Google Scholar 

  • Suh, K.S. and Chang, S. (2006) User interfaces and consumer perceptions of online stores: The role of telepresence. Behaviour & Information Technology 25 (2): 99–113.

    Article  Google Scholar 

  • Terry, D.J., Hogg, M.A. and White, K.M. (1999) The theory of planned behavior self-identity, social identity, and group norms. British Journal of Social Psychology 38 (3): 225–244.

    Article  Google Scholar 

  • Thogerson, J. (2002) Direct experience and the strength of the personal norm-behavior relationship. Psychology and Marketing 19 (10): 881–893.

    Article  Google Scholar 

  • Wang, L.C., Baker, J., Wagner, J.A. and Wakefield, K. (2007) Can a retail web site be social? Journal of Marketing 71 (3): 143–157.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Appendix

Appendix

Measurement scales

Attitude (α=0.969, four items; Smith et al, 2007)

  • ‘In general, how would you rate this brand?’

Unpleasant–pleasant, bad–good, negative–positive, unfavorable–favorable (rated on a 7-point scale ranging from 1 to 7).

Subjective norm (α=0.832, two items; Bamberg et al, 2003)

  • ‘In the real world, most people who are important to me would support me in buying products with this brand’ (1=strongly disagree to 7=strongly agree).

  • ‘In the real world, most people who are important to me think that I should buy products with this brand’ (1=strongly disagree to 7=strongly agree).

Perceived behavioral control (α=0.894, two items; Smith et al, 2007)

  • ‘For me to buy product with this brand in the real world would be’: (1=difficult to 7=easy).

  • ‘If I wanted to, I could easily buy products with this brand in the real world’ (1=strongly disagree to 7=strongly agree).

Self-image congruence (α=0.823, four items; Sirgy et al, 1997)

  • ‘I can identify with avatars who use products with this brand in Second Life’ (1=strongly disagree to 7=strongly agree).

  • ‘I am very much like the typical avatar that uses products with this brand in Second Life’ (1=strongly disagree to 7=strongly agree).

  • ‘The brand image is highly consistent with how I see myself in Second Life’ (1=strongly disagree to 7=strongly agree).

  • ‘I do not have anything in common with the typical avatar that uses this brand in Second Life’ (reverse scored, 1=strongly disagree to 7=strongly agree).

Perceived diagnosticity (α=0.886, two items; Kempf and Smith, 1998; Jiang and Benbasat, 2005)

  • ‘How helpful would you rate your experience with this brand in Second Life?’ (1=not helpful at all to 7=extremely helpful).

  • ‘Overall, how helpful would you rate your experience with the brand in Second Life for judging the quality and performance of products with this brand in real life?’ (1=not helpful at all to 7=extremely helpful).

Virtual world brand experience (α=0.807, four items)

  • ‘Have you spent time looking at products in Second Life with this brand?’ (1=Yes, 0=No).

  • ‘Have you tried out any products in Second Life with this brand?’ (1=Yes, 0=No).

  • ‘Have you considered purchasing any products in Second Life with this brand?’ (1=Yes, 0=No).

  • ‘Have you purchased any products in Second Life with this brand?’ (1=Yes, 0=No).

Real world purchase intention (α=0.905, two items; Holzwarth et al, 2006)

  • ‘I would be very interested in buying products with this brand in the real world’ (1=strongly disagree to 7=strongly agree).

  • ‘I would consider buying products with this brand in the real world’ (1=strongly disagree to 7=strongly agree).

Real world purchase behavior (α=0.791, three items)

  • ‘Have you spent time looking at products with this brand in the real world?’ (1=Yes, 0=No).

  • ‘Have you tried out products with this brand in the real world?’ (1=Yes, 0=No).

  • ‘Have you purchased products with this brand in the real world?’ (1=Yes, 0=No).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gabisch, J. Virtual world brand experience and its impact on real world purchasing behavior. J Brand Manag 19, 18–32 (2011). https://doi.org/10.1057/bm.2011.29

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/bm.2011.29

Keywords

Navigation