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Social Contagion in New Product Trial and Repeat

Author

Listed:
  • Raghuram Iyengar

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, 19104)

  • Christophe Van den Bulte

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, 19104)

  • Jae Young Lee

    (School of Business, Yonsei University, Seoul 120-749, Republic of Korea)

Abstract

The notion of peer influence in new product adoption or trial is well accepted. We propose that peer influence may affect repeat behavior as well, though the process and source of influence are likely to differ between trial and repeat. Our analysis of the acceptance of a risky prescription drug by physicians provides three novel findings. First, there is evidence of contagion not only in trial but also in repeat. Second, who is most influential varies across stages. Physicians with high centrality in the discussion and referral network and with high prescription volume are influential in trial but not repeat. In contrast, immediate colleagues, few of whom are nominated as a discussion or referral partner, are influential in both trial and repeat. Third, who is most influenceable also varies across stages. For trial, it is physicians who do not consider themselves to be opinion leaders, whereas for repeat, it is those located towards the middle of the status distribution as measured by network centrality. The pattern of results is consistent with informational social influence reducing risk in trial and normative social influence increasing conformity in repeat.

Suggested Citation

  • Raghuram Iyengar & Christophe Van den Bulte & Jae Young Lee, 2015. "Social Contagion in New Product Trial and Repeat," Marketing Science, INFORMS, vol. 34(3), pages 408-429, May.
  • Handle: RePEc:inm:ormksc:v:34:y:2015:i:3:p:408-429
    DOI: 10.1287/mksc.2014.0888
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    as
    1. Szymanowski, Maciej & Gijsbrechts, Els, 2013. "Patterns in consumption-based learning about brand quality for consumer packaged goods," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 219-235.
    2. Yansong Hu & Christophe Van den Bulte, 2014. "Nonmonotonic Status Effects in New Product Adoption," Marketing Science, INFORMS, vol. 33(4), pages 509-533, July.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    4. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Bicchieri,Cristina, 2006. "The Grammar of Society," Cambridge Books, Cambridge University Press, number 9780521574907, January.
    6. Levin, Sharon G & Levin, Stanford L & Meisel, John B, 1992. "Market Structure, Uncertainty, and Intrafirm Diffusion: The Case of Optical Scanners in Grocery Stores," The Review of Economics and Statistics, MIT Press, vol. 74(2), pages 345-350, May.
    7. Yingda Lu & Kinshuk Jerath & Param Vir Singh, 2013. "The Emergence of Opinion Leaders in a Networked Online Community: A Dyadic Model with Time Dynamics and a Heuristic for Fast Estimation," Management Science, INFORMS, vol. 59(8), pages 1783-1799, August.
    8. Lien, Da-Hsiang Donald & Rearden, David, 1990. "A Remark on 'An Advantage of the Linear Probability Model over Probit or Logit.'," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 223-225, May.
    9. Haenlein, Michael, 2013. "Social interactions in customer churn decisions: The impact of relationship directionality," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 236-248.
    10. Christophe Van den Bulte & Raghuram Iyengar, 2011. "Tricked by Truncation: Spurious Duration Dependence and Social Contagion in Hazard Models," Marketing Science, INFORMS, vol. 30(2), pages 233-248, 03-04.
    11. David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
    12. Bearden, William O & Netemeyer, Richard G & Teel, Jesse E, 1989. "Measurement of Consumer Susceptibility to Interpersonal Influence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(4), pages 473-481, March.
    13. Poirier, Dale J. & Ruud, Paul A., 1981. "On the appropriateness of endogenous switching," Journal of Econometrics, Elsevier, vol. 16(2), pages 249-256, June.
    14. Emily Oster & Rebecca Thornton, 2012. "Determinants Of Technology Adoption: Peer Effects In Menstrual Cup Take-Up," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1263-1293, December.
    15. Martin, William C. & Lueg, Jason E., 2013. "Modeling word-of-mouth usage," Journal of Business Research, Elsevier, vol. 66(7), pages 801-808.
    16. David Bell & Sangyoung Song, 2007. "Neighborhood effects and trial on the internet: Evidence from online grocery retailing," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 361-400, December.
    17. Herbert C. Kelman, 1958. "Compliance, identification, and internalization three processes of attitude change," Journal of Conflict Resolution, Peace Science Society (International), vol. 2(1), pages 51-60, March.
    18. Christophe Van den Bulte & Yogesh V. Joshi, 2007. "New Product Diffusion with Influentials and Imitators," Marketing Science, INFORMS, vol. 26(3), pages 400-421, 05-06.
    19. Sinan Aral, 2011. "Commentary--Identifying Social Influence: A Comment on Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 217-223, 03-04.
    20. Molitor, Dominik & Hinz, Oliver & Wegmann, Sarah, 2011. "The Interplay between Psychometric and Sociometric Data and the Willingness to Adopt New Products," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56547, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Ricardo Montoya & Oded Netzer & Kamel Jedidi, 2010. "Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability," Marketing Science, INFORMS, vol. 29(5), pages 909-924, 09-10.
    22. Aral, Sinan & Muchnik, Lev & Sundararajan, Arun, 2013. "Engineering social contagions: Optimal network seeding in the presence of homophily," Network Science, Cambridge University Press, vol. 1(2), pages 125-153, August.
    23. Prabhakant Sinha & Andris A. Zoltners, 2001. "Sales-Force Decision Models: Insights from 25 Years of Implementation," Interfaces, INFORMS, vol. 31(3_supplem), pages 8-44, June.
    24. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    25. Anderson, G. J., 1987. "Prediction tests in limited dependent variable models," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 253-261.
    26. Nicholas A. Christakis & James H. Fowler, 2011. "Commentary--Contagion in Prescribing Behavior Among Networks of Doctors," Marketing Science, INFORMS, vol. 30(2), pages 213-216, 03-04.
    27. Minhi Hahn & Sehoon Park & Lakshman Krishnamurthi & Andris A. Zoltners, 1994. "Analysis of New Product Diffusion Using a Four-Segment Trial-Repeat Model," Marketing Science, INFORMS, vol. 13(3), pages 224-247.
    28. Prosser, Helen & Walley, Tom, 2006. "New drug prescribing by hospital doctors: The nature and meaning of knowledge," Social Science & Medicine, Elsevier, vol. 62(7), pages 1565-1578, April.
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