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A Multivariate Polya Model of Brand Choice and Purchase Incidence

Author

Listed:
  • Udo Wagner

    (University of Economics, Vienna)

  • Alfred Taudes

    (University of Economics, Vienna)

Abstract

In this paper we develop an integrated stochastic model of purchase timing and brand selection which incorporates the influence of marketing mix variables, seasonality and trend, and also allows for various individual choice mechanisms. Our approach rests on the assumptions of a zero-order choice process, a Poisson timing process and purchase rates following a multivariate Gamma Distribution over the population, the scale parameters of which vary according to marketing activities and time. The resulting model is a , and the distribution of brand choice probabilities turns out to be a . Thus, most currently used zero-order models can be considered to be special cases of this approach. Furthermore, we derive a number of market diagnostics which provide insights into market structure and demonstrate the model's use for marketing strategy simulation. Based on extensive testing of the underlying hypotheses we finally validate the model using empirical data and show that it fits the market in question.

Suggested Citation

  • Udo Wagner & Alfred Taudes, 1986. "A Multivariate Polya Model of Brand Choice and Purchase Incidence," Marketing Science, INFORMS, vol. 5(3), pages 219-244.
    • Handle: RePEc:inm:ormksc:v:5:y:1986:i:3:p:219-244
    DOI: 10.1287/mksc.5.3.219
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    Citations

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    Cited by:

    1. Juin-Kuan Chong & Teck-Hua Ho & Christopher S. Tang, 2001. "A Modeling Framework for Category Assortment Planning," Manufacturing & Service Operations Management, INFORMS, vol. 3(3), pages 191-210, January.
    2. Ehrenberg, Andrew S. C. & Uncles, Mark D. & Goodhardt, Gerald J., 2004. "Understanding brand performance measures: using Dirichlet benchmarks," Journal of Business Research, Elsevier, vol. 57(12), pages 1307-1325, December.
    3. Park, Changwon & Senauer, Benjamin, 1996. "Estimation Of Household Brand-Size Choice Models For Spaghetti Products With Scanner Data," Working Papers 14336, University of Minnesota, The Food Industry Center.
    4. Trinh, Giang & Lam, Desmond, 2016. "Understanding the attendance at cultural venues and events with stochastic preference models," Journal of Business Research, Elsevier, vol. 69(9), pages 3538-3544.
    5. Bruno J.D. Jacobs & Bas Donkers & Dennis Fok, 2016. "Model-Based Purchase Predictions for Large Assortments," Marketing Science, INFORMS, vol. 35(3), pages 389-404, May.
    6. Park, Chang Hee & Park, Young-Hoon & Schweidel, David A., 2014. "A multi-category customer base analysis," International Journal of Research in Marketing, Elsevier, vol. 31(3), pages 266-279.
    7. Alfred Taudes & Martin Natter & Olivier Reimann, 2017. "Udo Wagner zum 65. Geburtstag," Schmalenbach Journal of Business Research, Springer, vol. 69(4), pages 477-482, November.
    8. Wu, Couchen & Chen, Hsiu-Li, 2000. "Counting your customers: Compounding customer's in-store decisions, interpurchase time and repurchasing behavior," European Journal of Operational Research, Elsevier, vol. 127(1), pages 109-119, November.

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