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Diffusion and Adoption Models

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Advanced Methods for Modeling Markets

Part of the book series: International Series in Quantitative Marketing ((ISQM))

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Abstract

In this chapter we discuss specific sets of models: diffusion models and adoption models. Diffusion models describe the spread of an innovation among a set of prospective adopters over time. A diffusion model depicts successive increases in the number of adopters and predicts the continued development of a diffusion process already in progress (Mahajan et al. 1993). The focus is generally on the generation of the product life cycle to forecast the first-purchase sales volume. Diffusion models are based on the assumption that the diffusion of a new product is a social process of imitation. For example, early adopters influence late adopters to purchase the new product. Positive interaction between current adopters and later adopters is assumed to bring about the (rapid) growth of the diffusion process.

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Notes

  1. 1.

    We closely follow Ruiz-Conde et al. (2014).

  2. 2.

    Sultan et al. (1990).

  3. 3.

    We closely follow Ruiz-Conde et al. (2006).

  4. 4.

    Be aware that p(t) is external influence and p t is a price variable, whereas \( \widetilde{p_t} \) is the relative price in (10.19).

  5. 5.

    We closely follow Muller et al. (2009, Chap. 4).

  6. 6.

    We follow Peres et al. (2010).

  7. 7.

    An example of a sophisticated international diffusion model is Gelper and Stremersch (2014).

  8. 8.

    We follow Muller et al. (2009).

  9. 9.

    See Urban et al. (1990) and Urban (1993).

  10. 10.

    These steps were identified by Rogers (1962).

  11. 11.

    See Mahajan et al. (2000).

  12. 12.

    Urban (1968).

  13. 13.

    Urban (1969, 1970) and Urban and Karash (1971).

  14. 14.

    Pringle et al. (1982).

  15. 15.

    Blackburn and Clancy (1980).

  16. 16.

    Silk and Urban (1978).

  17. 17.

    Urban (1993).

  18. 18.

    Urban and Katz (1983).

  19. 19.

    Lilien et al. (2007, p. 122).

  20. 20.

    For detailed descriptions see Lilien and Rangaswamy (2003, pp. 264–271) and Silk and Urban (1978).

  21. 21.

    The derivation of (10.36) can be found in, for example, Sect. 8.2.4.1 in Vol. I.

  22. 22.

    In Sect. 10.5.2 we extend this model.

  23. 23.

    See, for example, Tuten and Solomon (2015).

  24. 24.

    Muller et al. (2009, p. 9).

  25. 25.

    See, for example, Goldenberg et al. (2001).

  26. 26.

    We closely follow Ruiz-Conde et al. (2014).

References

  • Bass, F.: A new product growth for model consumer durables. Manag. Sci. 15, 215–227 (1969)

    Article  Google Scholar 

  • Bass, F., Krishnan, T.V., Jain, D.C.: Why the Bass model fits without decision variables. Mark. Sci. 13, 203–223 (1994)

    Article  Google Scholar 

  • Blackburn, J.D., Clancy, K.J.: LITMUS: A new product planning model. In: Leone, R.P. (ed.) Proceedings: Market Measurement and Analysis, pp. 182–193. The Institute of Management Sciences, Providence, RI (1980)

    Google Scholar 

  • Davies, S.W., Diaz-Rainey, I.: The patterns of induced diffusion: Evidence from the international diffusion of wind energy. Technol. Forecast. Soc. Change. 78, 1227–1241 (2011)

    Article  Google Scholar 

  • Dover, Y., Goldenberg, J., Shapira, D.: Network traces on penetrations: Uncovering degree distribution from adoption data. Mark. Sci. 31, 689–712 (2012)

    Article  Google Scholar 

  • Fischer, M., Leeflang, P.S.H., Verhoef, P.C.: Drivers of peak sales for pharmaceutical brands. Quant. Mark. Econ. 8, 429–460 (2010)

    Article  Google Scholar 

  • Fok, D., Franses, P.H.: Modeling the diffusion of scientific publications. J. Econ. 139, 376–390 (2007)

    Article  Google Scholar 

  • Fourt, L.A., Woodlock, J.W.: Early prediction of market success for new grocery products. J. Mark. 25(4), 31–38 (1960)

    Article  Google Scholar 

  • Gelper, S., Stremersch, S.: Variable selection in international diffusion models. Int. J. Res. Mark. 31, 356–367 (2014)

    Article  Google Scholar 

  • Godes, S., Mayzlin, D.: Firm-created word-of-mouth communications: Evidence from a field test. Mark. Sci. 28, 721–739 (2009)

    Article  Google Scholar 

  • Goldenberg, J., Han, S., Lehmann, D.R., Hong, J.W.: The role of hubs in the adoption process. J.Mark. 73(2), 1–13 (2009)

    Article  Google Scholar 

  • Goldenberg, J., Libai, B., Muller, E.: Talk of the network: A complex systems look at the underlying process of word-of-mouth. Mark. Lett. 12, 211–223 (2001)

    Article  Google Scholar 

  • Goldenberg, J., Libai, B., Muller, E.: Riding the saddle: How cross-market communications can create a major slump in sales. J. Mark. 66(2), 1–16 (2002)

    Google Scholar 

  • Goldenberg, J., Libai, B., Muller, E.: The chilling effects of network externalities. Int. J. Res. Mark. 27, 4–15 (2010)

    Article  Google Scholar 

  • Golder, P.N., Tellis, G.J.: Will it ever fly? Modeling the takeoff of really new consumer durables. Mark. Sci. 16, 256–270 (1997)

    Article  Google Scholar 

  • Guidelin, M., Mortarino, C.: Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns. Technol. Forecast. Soc. Change. 77, 279–296 (2010)

    Article  Google Scholar 

  • Hahn, M., Park, S., Krishnamurthi, L., Zoltners, A.: Analysis of new product diffusion using a four-segment trial-repeat model. Mark. Sci. 13, 224–247 (1994)

    Article  Google Scholar 

  • Hu, Y., Van den Bulte, C.: Nonmonotonic status effect in new product adoption. Mark. Sci. 33, 509–533 (2014)

    Article  Google Scholar 

  • Iyengar, R., Van den Bulte, C., Valente, T.W.: Opinion leadership and social contagion in new product diffusion. Mark. Sci. 30, 195–212 (2011)

    Article  Google Scholar 

  • Iyengar, R., Van den Bulte, C., Lee, J.Y.: Social contagion in new product trial and repeat. Mark. Sci. 34, 408–429 (2015)

    Article  Google Scholar 

  • Jiang, Z., Jain, D.C.: A generalized Norton-Bass model for multigeneration diffusion. Manag. Sci. 58, 1887–1897 (2012)

    Google Scholar 

  • Kumar, V., Krishnan, T.V.: Multinational diffusion models: An alternative framework. Mark. Sci. 21, 318–330 (2002)

    Article  Google Scholar 

  • Libai, B., Muller, E., Peres, R.: The role of within-brand and cross-brand communications in competitive growth. J. Mark. 73(3), 19–34 (2009a)

    Article  Google Scholar 

  • Libai, B., Muller, E., Peres, R.: The diffusion of services. J. Mark. Res. 46, 163–175 (2009b)

    Article  Google Scholar 

  • Libai, B., Muller, E., Peres, R.: Decomposing the value of word-of-mouth seeding programs: Acceleration versus expansion. J. Mark. Res. 50, 161–176 (2013)

    Article  Google Scholar 

  • Lilien, G.L., Rangaswamy, A.: Marketing Engineering, 2nd ed. Prentice Hall, Upple Saddle River (2003)

    Google Scholar 

  • Lilien, G.L., Rangaswamy, A., DeBruyn, A.: Principles of Marketing Engineering. Trafford Publishing, State College (2007)

    Google Scholar 

  • Mahajan, V., Muller, E., Bass, F.M.: New product diffusion modes in marketing: A review and directions for research. J. Mark. 54(1), 1–26 (1990)

    Article  Google Scholar 

  • Mahajan, V., Muller, E., Bass, F.M.: New-product diffusion models. In: Birge, J.R., Linetsky, V. (eds.) Handbooks in Operations Research and Management Science, vol. 5, 349–408 (1993)

    Google Scholar 

  • Mahajan, V., Muller, E., Wind, Y.: New-Product Diffusion Models. Springer, New York (2000)

    Google Scholar 

  • Muller, E., Mahajan, V., Peres, R.: Innovation Diffusion and New Product Growth. Marketing Science Institute, Boston (2009)

    Google Scholar 

  • Norton, J.A., Bass, F.M.: A diffusion theory model of adoption and substitution for successive generations of high-technology products. Manag. Sci. 33(9), 1069–1086 (1987)

    Google Scholar 

  • Nijkamp, W.G.: New productmacroflow models – Specification and analysis. Unpublished Ph.D. thesis, Groningen, The Netherlands (1993)

    Google Scholar 

  • Parfitt, J.H., Collins, B.J.K.: Use of consumer panels for brand-share prediction. J. Mark. Res. 5, 131–145 (1968)

    Article  Google Scholar 

  • Parker, P., Gatignon, H.: Specifying competitive effects in diffusion models: an empirical analysis. Int. J. Res. Mark. 11, 17–39 (1994)

    Article  Google Scholar 

  • Peers, Y., Fok, D., Franses, P.H.: Modeling seasonality in new product diffusion. Mark. Sci. 31, 351–364 (2012)

    Article  Google Scholar 

  • Peres, R., Muller, E., Mahajan, V.: Innovation diffusion and new product growth models: A critical review and research directions. Int. J. Res. Mark. 27, 91–106 (2010)

    Article  Google Scholar 

  • Pringle, G.L., Wilson, R.D., Brody, E.I.: NEWS: A decision-oriented model for new product analysis and forecasting. Mark. Sci. 1, 1–29 (1982)

    Article  Google Scholar 

  • Prins, R., Verhoef, P.C.: Marketing communication drivers of adoption timing of a new e-service among existing customers. J. Mark. 71(2), 169–183 (2007)

    Article  Google Scholar 

  • Reber, K., Wieringa, J.E., Leeflang, P.S.H. and Stern, P.: Marketing new pharmaceuticals: When should which doctors be detailed?, Working paper, University of Groningen (2013)

    Google Scholar 

  • Risselada, H., Verhoef, P.C., Bijmolt, T.H.A.: Dynamic effects of social influence and direct marketing on the adoption of high-technology products. J. Mark. 78(2), 52–68 (2014)

    Article  Google Scholar 

  • Rogers, R.: Diffusion of Innovations. The Free Press, New York (1962)

    Google Scholar 

  • Ruiz-Conde, E., Leeflang, P.S.H.: Diffusion of franchising as an innovation of managerial organization. Mark Journal of Res. and Man. 2, 65–75 (2006)

    Google Scholar 

  • Ruiz-Conde, E., Leeflang, P.S.H., Wieringa, J.E.: Marketing variables in macro-level diffusion models. Journal für Betriebswirtschaft. 56, 155–183 (2006)

    Article  Google Scholar 

  • Ruiz-Conde, E., Wieringa, J.E., Leeflang, P.S.H.: Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment. Technol. Forecast. Soc. Change. 88, 49–63 (2014)

    Article  Google Scholar 

  • Shen, W., Duenyas, I., Kapuscinski, R.: New product diffusion decisions under supply constraints. Manag. Sci. 57, 1802–1810 (2011)

    Article  Google Scholar 

  • Silk, A.J., Urban, G.L.: Pre-test-market evaluation of new packaged goods: A model and measurement methodology. J. Mark. Res. 15, 171–191 (1978)

    Article  Google Scholar 

  • Sood, A., James, G.M., Tellis, J.: Functional regression: A new model for predicting market penetration of new products. Mark. Sci. 28, 36–51 (2009)

    Article  Google Scholar 

  • Sood, A., James, G.M., Tellis, G.J., Zhu, J.: Predicting the path of technological innovation: SAW vs. Moore, Bass, Gompertz, and Kryder. Mark. Sci. 31, 964–979 (2012)

    Article  Google Scholar 

  • Stremersch, S., Muller, E., Peres, R.: Does new product growth accelerate across technology generations? Mark. Lett. 21, 103–120 (2010)

    Article  Google Scholar 

  • Sultan, F., Farley, J.U., Lehmann, D.R.: A meta-analysis of applications of diffusion models. J.Mark. Res. 27, 70–77 (1990)

    Article  Google Scholar 

  • Tellis, G.J., Stremersch, S., Yin, E.: The international takeoff of new products: The role of economics, culture, and country innovativeness. Mark. Sci. 22, 188–208 (2003)

    Article  Google Scholar 

  • Toubia, O., Goldenberg, J., Garcia, R.: Improving penetration forecasts using social interactions data. Manag. Sci. 60, 3049–3066 (2014)

    Article  Google Scholar 

  • Trusov, M., Rand, W., Joshi, Y.V.: Improving prelaunch diffusion forecasts: Using synthetic networks as simulated priors. J. Mark. Res. 50, 675–690 (2013)

    Article  Google Scholar 

  • Tuten, T.L., Solomon, M.R.: Social Media Marketing. Sage Publications Ltd, London (2015)

    Google Scholar 

  • Urban, G.L.: A new product analysis and decision model. Manag. Sci. 14, 490–517 (1968)

    Article  Google Scholar 

  • Urban, G.L.: SPRINTER Mod. II: Basic new product analysis model. In: Morin, B.A. (ed. ), Proceedings of the National Conference of the American Marketing Association, pp. 139–150 (1969)

    Google Scholar 

  • Urban, G.L.: SPRINTER Mod. III: A model for the analysis of new frequently purchased consumer products. Oper. Res. 18, 805–854 (1970)

    Article  Google Scholar 

  • Urban, G.L.: Pretest market forecasting. In: Eliashberg, J., Lilien, G.L. (eds.) Handbooks in Operations Research and Management Science 5, pp. 315–348, Marketing, North-Holland, Amsterdam (1993)

    Google Scholar 

  • Urban, G.L., Hauser, J.R., Roberts, J.H.: Prelaunch forecasting of new automobiles: Models and implementation. Manag. Sci. 36, 401–421 (1990)

    Article  Google Scholar 

  • Urban, G.L., Karash, R.: Evolutionary model building. J. Mark. Res. 8, 62–66 (1971)

    Article  Google Scholar 

  • Urban, G.L., Katz, M.: Pre-test-markets models: Validation and managerial implications. J. Mark. Res. 20, 221–234 (1983)

    Article  Google Scholar 

  • Van den Bulte, C.: New product diffusion acceleration: Measurement and analysis. Mark. Sci. 19, 366–380 (2000)

    Article  Google Scholar 

  • Van Eck, P.S., Jager, W., Leeflang, P.S.H.: Opinion leaders’ role in innovations diffusion: A simulation study. J. Prod. Innov. Manag. 28, 187–203 (2011)

    Article  Google Scholar 

  • Van Everdingen, Y.M., Aghina, W.B., Fok, D.: Forecasting cross-population innovation diffusion: A Bayesian approach. Int. J. Res. Mark. 22, 293–308 (2005)

    Article  Google Scholar 

  • Viard, V.B., Economides, N.: The effect of content on global internet adoption and the global “digital divide”. Manag. Sci. 61, 665–687 (2015)

    Article  Google Scholar 

  • Wuyts, S., Stremersch, S., Van den Bulte, C., Franses, P.H.: Vertical marketing systems for compley products: A triadic perspective. J. Mark. Res. 41, 479–487 (2004)

    Article  Google Scholar 

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Leeflang, P.S.H., Wieringa, J.E. (2017). Diffusion and Adoption Models. In: Leeflang, P., Wieringa, J., Bijmolt, T., Pauwels, K. (eds) Advanced Methods for Modeling Markets. International Series in Quantitative Marketing. Springer, Cham. https://doi.org/10.1007/978-3-319-53469-5_10

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