Journal of Information Technology

, Volume 24, Issue 2, pp 172–185 | Cite as

Mobile word-of-mouth – A grounded theory of mobile viral marketing

  • Wolfgang Palka
  • Key Pousttchi
  • Dietmar G Wiedemann
Research Article


Mobile devices as personal communication tools are used as platforms for viral marketing within existing social networks. Although there is some evidence on the usefulness of mobile viral marketing from the marketers’ perspective, little is known about the motivations, attitudes, and behaviors of consumers engaged in this marketing instrument. The purpose of this research is to better understand the motivations behind a consumer's decision to engage in mobile viral marketing strategies. The outcome is a grounded theory of mobile viral marketing with respect to the consumer and his social network, decomposing the mobile viral effect and identifying the determinants of reception, usage, and forwarding of mobile viral content. This result helps researchers and marketers to better understand the critical components of mobile viral marketing strategies and prepares the ground for further research in this emerging field.


mobile viral marketing mobile word-of-mouth mobile marketing theoretical framework grounded theory 


  1. Ajzen, I. (1988). Attitudes, Personality, and Behavior, Chicago: The Dorsey Press.Google Scholar
  2. Ajzen, I. (1991). The Theory of Planned Behavior, Organizational Behavior and Human Decision Processes 50 (2): 179–211.CrossRefGoogle Scholar
  3. Arndt, J. (1967). Role of Product-Related Conversations in the Diffusion of a New Product, Journal of Marketing Research 4 (3): 291–295.CrossRefGoogle Scholar
  4. Bandura, A. (1982). Self-Efficacy Mechanism in Human Agency, American Psychologist 37: 122–147.CrossRefGoogle Scholar
  5. Barwise, P. and Strong, C. (2002). Permission-Based Mobile Advertising, Journal of Interactive Marketing 16 (1): 14–24.CrossRefGoogle Scholar
  6. Bauer, H.H., Barnes, S.J., Reichardt, T. and Neumann, M.M. (2005). Driving Consumer Acceptance of Mobile Marketing: A theoretical framework and empirical study, Journal of Electronic Commerce Research 6 (3): 181–192.Google Scholar
  7. Bazijanec, B., Pousttchi, K. and Turowski, K. (2004). An Approach for Assessment of Electronic Offers. Applying Formal Methods: Testing, performance, and M/Ecommerce, in M. Núñez, Z. Maamar, K. Pousttchi, F. Rubio and F.L. Pelayo (eds.) FORTE 2004 Workshops The Form EMC, EPEW, ITM, Toledo, Spain: Lecture Notes in Computer Science, pp. 44–57.Google Scholar
  8. Bone, P.F. (1992). Determinants of Word-of-Mouth Communication during Consumption, Advances in Consumer Research 19: 579–583.CrossRefGoogle Scholar
  9. Brown, J. and Reingen, P. (1987). Social Ties and Word-of-Mouth Referral Behavior, Journal of Consumer Research 14 (3): 350–362.CrossRefGoogle Scholar
  10. de Bruyn, A. and Lilien, G.L. (2008). A Multi-Stage Model of Word of Mouth Through Electronic Referrals, International Journal of Research in Marketing 25: 151–163.CrossRefGoogle Scholar
  11. Chen, W.-K., Huang, H.C. and Chou, S.C.T. (2008). Understanding Consumer Recommendation Behaviour in a Mobile Phone Service Context, in Proceedings of the 16th European Conference on Information Systems (Galway, Ireland), 1022–1033.Google Scholar
  12. Compeau, D.R. and Higgins, C.A. (1995). Computer Self-Efficacy: Development of a measure and initial test, MIS Quarterly 19 (2): 189–211.CrossRefGoogle Scholar
  13. Cunningham, S.M. (1967). The Major Dimensions of Perceived Risk, in D.F. Cox (ed.) Risk Taking and Information Handling in Consumer Behavior, Boston, MA: Harvard University Press, pp. 82–108.Google Scholar
  14. Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly 13 (3): 319–340.CrossRefGoogle Scholar
  15. Dawason, E.M. and Chatman, E.A. (2001). Reference Group Theory with Implications for Information Studies: A theoretical essay, Information Research 6 (3) [WWW document] (accessed 19th January 2008).
  16. Dichter, E. (1966). How Word-of-Mouth Advertising Works, Harvard Business Review 44 (6): 147–166.Google Scholar
  17. Ducoffe, R.H. (1996). Advertising Value and Advertising on the Web, Journal of Advertising Research 36 (5): 21–36.Google Scholar
  18. Feick, L. and Price, L. (1987). The Market Maven: A diffuser of marketplace information, Journal of Marketing 51 (1): 83–97.CrossRefGoogle Scholar
  19. Feick, L.F., Guskey, A. and Price, L. (1995). Everyday Market Helping Behavior, Journal of Public Policy & Marketing 14 (2): 255–266.Google Scholar
  20. Fishbein, M. and Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An introduction to theory and research, Reading: Addison-Wesley.Google Scholar
  21. Gefen, D. (2002). Customer Loyalty in E-Commerce, Journal of the Association for Information Systems 3 (2): 27–51.Google Scholar
  22. Gefen, D., Karahanna, E. and Straub, D.W. (2003). Inexperience and Experience with Online Stores: The importance of TAM and trust, IEEE Transactions on Engineering Management 50 (3): 307–321.CrossRefGoogle Scholar
  23. Gilly, M.C., Graham, J.L., Wolfinbarger, M.F. and Yale, L.J. (1998). A Dyadic Study of Interpersonal Information Search, Academy of Marketing Science 26 (2): 83–100.CrossRefGoogle Scholar
  24. Glaser, B.G. and Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for qualitative research, Chicago: Aldine Publishing.Google Scholar
  25. Goffman, E. (1959). The Presentation of Self in Everyday Life, Garden City: Doubleday.Google Scholar
  26. Granovetter, M.S. (1973). The Strength of Weak Ties, American Journal of Sociology 78: 1360–1380.CrossRefGoogle Scholar
  27. Helm, S. (2000). Viral Marketing – Establishing consumer relationships by ‘word-of-mouse’, Electronic Markets 10 (3): 158–161.CrossRefGoogle Scholar
  28. Hennig-Thurau, T., Gwinner, K.P., Walsh, G. and Gremler, D.D. (2004). Electronic Word-of-Mouth via Consumer-Opinion Platforms: What motivates consumers to articulate themselves on the internet, Journal of Interactive Marketing 18 (1): 38–52.CrossRefGoogle Scholar
  29. Herr, P.M., Kardes, F.R. and Kim, J. (1991). Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An accessibility-diagnosticity perspective, Journal of Consumer Research 17 (4): 454–462.CrossRefGoogle Scholar
  30. Igbaria, M., Parasuraman, S. and Baroudi, J.J. (1996). A Motivational Model of Microcomputer Usage, Journal of Management Information Systems 13 (1): 127–143.CrossRefGoogle Scholar
  31. Intuitive Media Research Services (2006). Kids Go Mobile. Ownership and Use of Mobile Phones by Children aged 6 to 13 for ICT in Education Sector, 6th December 2006 [WWW document] (accessed 9th May 2007).
  32. I-play (2005). I-Play Outlines Collective Industry Action Required for Mobile Gaming Market to Reach True Potential, 1st August 2005 [WWW document] (accessed 9th May 2007).
  33. Jelassi, T. and Enders, A. (2004). Leveraging Wireless Technology for Mobile Advertising, in Proceedings of the 12th European Conference on Information Systems (Turku, Finland, 2004). Turku School of Economics and Business Administration.Google Scholar
  34. Jurvetson, S. (1997). What is Viral Marketing?, Original version published in the Netscape M-Files [WWW document] (accessed 1st November 2006).Google Scholar
  35. Karjaluoto, H. and Alatalo, T. (2007). Consumers Attitudes Towards and Intention to Participate in Mobile Marketing, International Journal of Services Technology and Management 8 (2/3): 155–173.CrossRefGoogle Scholar
  36. Karjaluoto, H., Lehto, H., Leppäniemi, M and Jayawardhena, C. (2008). Customers Intention to Engage in Permission Based Mobile Marketing Communications, in Proceedings of the European Marketing Academy (EMAC) Conference (Brighton, United Kingdom, 2008).Google Scholar
  37. Katz, E. and Lazarsfeld, P.F. (1955). Personal influence: The part played by people in the flow of mass communications, New York: Free Press.Google Scholar
  38. Katz, M.L. and Shapiro, C. (1985). Network Externalities, Competition and Compatibility, American Economic Review 75 (3): 424–440.Google Scholar
  39. Kavassalis, P., Spyropoulou, N., Drossos, D., Mitrokostas, V., Gikas, G. and Hatzistamatiou, A. (2002). Mobile Permission Marketing – Framing the Market Inquiry, in Proceedings 13th International Telecommunications Society's (ITS) European Regional Conference (Madrid, Spain, 2002).Google Scholar
  40. Krippendorf, K. (1980). Content Analysis. An Introduction to its Methodology, Beverly Hills: Sage Publications.Google Scholar
  41. Ling, R. and Yttri, B. (2005). Control, Emancipation and Status: The mobile telephone in the teen's parental and peer group control relationships, in R. Kraut (ed.) Information Technology at Home, Oxford: Oxford University Press.Google Scholar
  42. Marini, S. and Wiedemann, D.G. (2006). Entwicklungen im Bereich Mobile Advertising aus der Sicht von Experten, in K. Pousttchi (ed.) Ergebnisse der Expertenbefragung MM 1. Studienpapiere der Arbeitsgruppe Mobile Commerce, Augsburg, Germany: Wi-mobile Research Groups, University of Augsburg, pp. 1–49.Google Scholar
  43. Martin, P.Y. and Turner, B.A. (1986). Grounded Theory and Organizational Research, Journal of Applied Behavioral Science 22 (2): 141–157.CrossRefGoogle Scholar
  44. Maxwell, J.A. (1996). Qualitative Research Design: An interactive approach, Thousand Oaks: Sage.Google Scholar
  45. McCracken, G. (1989). Who is the Celebrity Endorser? Cultural Foundation of the Endorsement Process, Journal of Consumer Research 16 (3): 310–321.CrossRefGoogle Scholar
  46. Mitchell, V.-W. (1999). Consumer Perceived Risk: Conceptualisations and models, European Journal of Marketing 33 (1): 163–196.CrossRefGoogle Scholar
  47. Montgomery, A.L. (2001). Applying Quantitative Marketing Techniques to the Internet, Interfaces 31 (2): 90–108.CrossRefGoogle Scholar
  48. Mort, G.S. and Drennan, J. (2005). Marketing M-Services: Establishing a usage benefit typology related to mobile user characteristics, Journal of Database Marketing & Customer Strategy Management 12 (4): 327–341.CrossRefGoogle Scholar
  49. Norman, A.T. and Russell, C.A. (2006). The Pass-Along Effect: Investigating word-of-mouth effects on online survey procedures, Journal of Computer-Mediated Communication 11 (4) [WWWdocument] (accessed 9th February, 2008).
  50. Nysveen, H., Pedersen, P.E. and Thorbjørnsen, H. (2005). Intentions to Use Mobile Services: Antecedents and cross-service comparisons, Journal of the Academy of Marketing Science 33 (3): 330–346.CrossRefGoogle Scholar
  51. Okazaki, S. (2005). New Perspectives on M-Commerce Research, Journal of Electronic Commerce Research 6 (3): 160–164.Google Scholar
  52. Oliver, R.L. (1997). Satisfaction: A behavioral perspective on the consumer, New York: Irwin/McGraw-Hill.Google Scholar
  53. Pagani, M. (2004). Determinants of Adoption of Third Generation Mobile Multimedia Services, Journal of Interactive Marketing 18 (3): 46–59.CrossRefGoogle Scholar
  54. Phelps, J.E., Lewis, R., Mobilio, L. and Perry, D. (2004). Viral Marketing or Electronic Word-of-Mouth Advertising: Examining consumer responses and motives to pass along email, Journal of Advertising Research 45 (4): 333–348.CrossRefGoogle Scholar
  55. Pousttchi, K. and Wiedemann, D.G. (2006). A Contribution to Theory Building for Mobile Marketing: Categorizing mobile marketing campaigns through case study research, in Proceedings of the 5th International Conference on Mobile Business (Copenhagen, Denmark, 2006). IEE Computer Society.Google Scholar
  56. Pousttchi, K. and Wiedemann, D.G. (2007). Success Factors in Mobile Viral Marketing: A multi-case study approach, in Proceedings of the 6th International Conference on Mobile Business (Toronto, Canada, 2007). IEE Computer Society.Google Scholar
  57. Schiffman, L.G. and Kanuk, L.L. (1997). Consumer Behavior, 9th edn, Upper Saddle River: Prentice Hall.Google Scholar
  58. Song, J. and Walden, E. (2007). How Consumer Perceptions of Network Size and Social Interactions Influence the Intention to Adopt Peer-to-Peer Technologies, International Journal of E-Business Research 3 (4): 49–66.CrossRefGoogle Scholar
  59. Strauss, A. and Corbin, J. (1990). Basics of Qualitative Research: Grounded theory techniques and procedures, Newbury Park: Sage.Google Scholar
  60. Subramani, M.R. and Rajagopalan, B. (2003). Knowledge-Sharing and Influence in Online Social Networks via Viral Marketing, Communications of the ACM 46 (12): 300–307.CrossRefGoogle Scholar
  61. Sundaram, D.S., Mitra, K. and Webster, C. (1998). Word-of-Mouth Communications: A motivational analysis, Advances in Consumer Research 25: 527–531.Google Scholar
  62. Swan, J.E. and Oliver, R.L. (1989). Postpurchase Communications by Consumers, Journal of Retailing 65 (4): 516–533.Google Scholar
  63. Tsang, M.M., Ho, S.-C. and Liang, T.-P. (2004). Consumer Attitudes toward Mobile Advertising: An empirical study, International Journal of Electronic Commerce 8 (3): 65–78.Google Scholar
  64. Venkatesh, V. and Davis, F.D. (2000). Theoretical Extension of the Technology Acceptance Model: Four longitudinal field studies, Management Science 46 (2): 186–204.CrossRefGoogle Scholar
  65. Weimann, G. (1991). The Influentials: Back to the concept of opinion leaders? Public Opinion Quarterly 55 (2): 268–279.CrossRefGoogle Scholar
  66. Wiedemann, D.G. (2007). Exploring the Concept of Mobile Viral Marketing through Case Study Research, in Proceedings of the 2nd Conference on Mobility and Mobile Information Systems (Aachen, Germany). Bonn: Lecture Notes in Informatics pp. 49–60.Google Scholar
  67. Wiedemann, D.G., Haunstetter, T. and Pousttchi, K. (2008). Analyzing the Basic Elements of Mobile Viral Marketing. An Empirical Study, in IEEE Computer Society (ed.), Proceedings of the 7th International Conference on Mobile Business (Barcelona, 2008); Silver Spring, MD: IEEE Computer Society.Google Scholar
  68. Wojnicki, A.C. and Godes, D.B. (2004). Word-of-Mouth and the Self-Concept: The effects of satisfaction and subjective expertise on inter-consumer communication, Working Paper, Harvard University, USA.Google Scholar
  69. Wu, J. and Wang, S. (2005). What Drives Mobile Commerce? An Empirical Evaluation of the Revised Technology Acceptance Model, Information and Management 42 (5): 719–729.CrossRefGoogle Scholar
  70. Zaichkowsky, J.L. (1985). Measuring the Involvement Construct, Journal of Consumer Research 12 (3): 341–352.CrossRefGoogle Scholar

Copyright information

© Association for Information Technology Trust 2009

Authors and Affiliations

  • Wolfgang Palka
    • 1
  • Key Pousttchi
    • 1
  • Dietmar G Wiedemann
    • 1
  1. 1.wi-mobile Research Group, University of Augsburg, Universitaetsstrasse 16AugsburgGermany

Personalised recommendations