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New Product Diffusion with Influentials and Imitators

  • Christophe Van den Bulte

    ()

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

  • Yogesh V. Joshi

    ()

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

Registered author(s):

    We model the diffusion of innovations in markets with two segments: who are more in touch with new developments and who affect another segment of whose own adoptions do not affect the influentials. This two-segment structure with asymmetric influence is consistent with several theories in sociology and diffusion research, as well as many “viral” or “network” marketing strategies. We have four main results. (1) Diffusion in a mixture of influentials and imitators can exhibit a dip or “chasm” between the early and later parts of the diffusion curve. (2) The proportion of adoptions stemming from influentials need not decrease monotonically, but may first decrease and then increase. (3) Erroneously specifying a mixed-influence model to a mixture process where influentials act independently from each other can generate systematic changes in the parameter values reported in earlier research. (4) Empirical analysis of 33 different data series indicates that the two-segment model fits better than the standard mixed-influence, the Gamma/Shifted Gompertz, and the Weibull-Gamma models, especially in cases where a two-segment structure is likely to exist. Also, the two-segment model fits about as well as the Karmeshu-Goswami mixed-influence model, in which the coefficients of innovation and imitation vary across potential adopters in a continuous fashion.

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    File URL: http://dx.doi.org/10.1287/mksc.1060.0224
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    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 26 (2007)
    Issue (Month): 3 (05-06)
    Pages: 400-421

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    Handle: RePEc:inm:ormksc:v:26:y:2007:i:3:p:400-421
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    1. Bart J. Bronnenberg & Carl F. Mela, 2004. "Market Roll-Out and Retailer Adoption for New Brands," Marketing Science, INFORMS, vol. 23(4), pages 500-518, September.
    2. 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.
    3. Christophe Van den Bulte & Gary L. Lilien, 1997. "Bias and Systematic Change in the Parameter Estimates of Macro-Level Diffusion Models," Marketing Science, INFORMS, vol. 16(4), pages 338-353.
    4. Gilles Laurent & G. L. Lilien & B. Pras, 1994. "Research Tradition in Marketing," Post-Print hal-00821717, HAL.
    5. Rajkumar Venkatesan & Trichy V. Krishnan & V. Kumar, 2004. "Evolutionary Estimation of Macro-Level Diffusion Models Using Genetic Algorithms: An Alternative to Nonlinear Least Squares," Marketing Science, INFORMS, vol. 23(3), pages 451-464, August.
    6. Williams, Ross A, 1972. "Growth in Ownership of Consumer Durables in the United Kingdom," Economica, London School of Economics and Political Science, vol. 39(153), pages 60-69, February.
    7. V. Srinivasan & Charlotte H. Mason, 1986. "Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models," Marketing Science, INFORMS, vol. 5(2), pages 169-178.
    8. Midgley, David F & Dowling, Grahame R, 1978. " Innovativeness: The Concept and Its Measurement," Journal of Consumer Research, Oxford University Press, vol. 4(4), pages 229-42, March.
    9. Davies, Stephen W., 1979. "Inter-firm diffusion of process innovations," European Economic Review, Elsevier, vol. 12(4), pages 299-317, October.
    10. Bernard Pras & Gilles Laurent & Gary L. Lilien, 1994. "Research Traditions in Marketing," Post-Print halshs-00150675, HAL.
    11. Gary L. Lilien & Ambar G. Rao & Shlomo Kalish, 1981. "Bayesian Estimation and Control of Detailing Effort in a Repeat Purchase Diffusion Environment," Management Science, INFORMS, vol. 27(5), pages 493-506, May.
    12. Tal Garber & Jacob Goldenberg & Barak Libai & Eitan Muller, 2004. "From Density to Destiny: Using Spatial Dimension of Sales Data for Early Prediction of New Product Success," Marketing Science, INFORMS, vol. 23(3), pages 419-428, August.
    13. Jonathan Beck, 2007. "The sales effect of word of mouth: a model for creative goods and estimates for novels," Journal of Cultural Economics, Springer, vol. 31(1), pages 5-23, March.
    14. repec:dau:papers:123456789/3445 is not listed on IDEAS
    15. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    16. Albert C. Bemmaor & Janghyuk Lee, 2002. "The Impact of Heterogeneity and Ill-Conditioning on Diffusion Model Parameter Estimates," Marketing Science, INFORMS, vol. 21(2), pages 209-220, November.
    17. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    18. Hernes, Gudmund, 1976. " Diffusion and Growth-The Non-homogeneous Case," Scandinavian Journal of Economics, Wiley Blackwell, vol. 78(3), pages 427-36.
    19. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October.
    20. William P. Putsis, Jr. & Sridhar Balasubramanian & Edward W. Kaplan & Subrata K. Sen, 1997. "Mixing Behavior in Cross-Country Diffusion," Marketing Science, INFORMS, vol. 16(4), pages 354-369.
    21. Frenzen, Jonathan & Nakamoto, Kent, 1993. " Structure, Cooperation, and the Flow of Market Information," Journal of Consumer Research, Oxford University Press, vol. 20(3), pages 360-75, December.
    22. Donald Lehmann & Mercedes Esteban-Bravo, 2006. "When giving some away makes sense to jump-start the diffusion process," Marketing Letters, Springer, vol. 17(4), pages 243-254, December.
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