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Dynamic changepoints revisited: An evolving process model of new product sales

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  • Schweidel, David A.
  • Fader, Peter S.

Abstract

This paper posits a new framework to model the trial of and repeat purchasing of a new product. While much research has examined underlying shifts in consumer purchasing patterns, the typical assumption has been that the underlying purchasing process remains the same although the purchasing rate may change over time. Motivated by Fader, Hardie, and Huang's development of a dynamic changepoint model [Fader, P. S., Hardie, B. G. S., & Huang, C. -Y. (2004). A Dynamic Changepoint Model for New Product Sales Forecasting. Marketing Science, 23 (1), 50–65], we consider an evolving process as consumers gain more experience with a new product.

Suggested Citation

  • Schweidel, David A. & Fader, Peter S., 2009. "Dynamic changepoints revisited: An evolving process model of new product sales," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 119-124.
  • Handle: RePEc:eee:ijrema:v:26:y:2009:i:2:p:119-124
    DOI: 10.1016/j.ijresmar.2008.12.005
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    1. Abel P. Jeuland & Frank M. Bass & Gordon P. Wright, 1980. "A Multibrand Stochastic Model Compounding Heterogeneous Erlang Timing and Multinomial Choice Processes," Operations Research, INFORMS, vol. 28(2), pages 255-277, April.
    2. West, Patricia M & Brown, Christina L & Hoch, Stephen J, 1996. "Consumption Vocabulary and Preference Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(2), pages 120-135, September.
    3. Barbara E. Kahn & Donald G. Morrison, 1989. "A Note on ‘Random’ Purchasing: Additional Insights from Dunn, Reader and Wrigley," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(1), pages 111-114, March.
    4. Peter S. Fader & Bruce G. S. Hardie & Ka Lok Lee, 2005. "“Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 24(2), pages 275-284, August.
    5. Bruce G. S. Hardie & Peter S. Fader & Robert Zeithammer, 2003. "Forecasting new product trial in a controlled test market environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 391-410.
    6. Meyer, Robert J, 1987. "The Learning of Multiattribute Judgment Policies," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(2), pages 155-173, September.
    7. Jerome Herniter, 1971. "A Probablistic Market Model of Purchase Timing and Brand Selection," Management Science, INFORMS, vol. 18(4-Part-II), pages 102-113, December.
    8. Peter S. Fader & Bruce G. S. Hardie & Chun-Yao Huang, 2004. "A Dynamic Changepoint Model for New Product Sales Forecasting," Marketing Science, INFORMS, vol. 23(1), pages 50-65, October.
    9. Sunil Gupta & Donald G. Morrison, 1991. "Estimating Heterogeneity in Consumers' Purchase Rates," Marketing Science, INFORMS, vol. 10(3), pages 264-269.
    10. Timothy J. Gilbride & Greg M. Allenby, 2004. "A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules," Marketing Science, INFORMS, vol. 23(3), pages 391-406, October.
    11. Sha Yang & Gerg M. Allenby & Geraldine Fennel, 2002. "Modeling Variation in Brand Preference: The Roles of Objective Environment and Motivating Conditions," Marketing Science, INFORMS, vol. 21(1), pages 14-31, May.
    12. David C. Schmittlein & Donald G. Morrison & Richard Colombo, 1987. "Counting Your Customers: Who-Are They and What Will They Do Next?," Management Science, INFORMS, vol. 33(1), pages 1-24, January.
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    Cited by:

    1. David A. Schweidel & George Knox, 2013. "Incorporating Direct Marketing Activity into Latent Attrition Models," Marketing Science, INFORMS, vol. 32(3), pages 471-487, May.
    2. Yanwen Wang & Chunhua Wu & Ting Zhu, 2019. "Mobile Hailing Technology and Taxi Driving Behaviors," Marketing Science, INFORMS, vol. 38(5), pages 734-755, September.
    3. Holtrop, Niels & Wieringa, Jaap E., 2023. "Timing customer reactivation initiatives," International Journal of Research in Marketing, Elsevier, vol. 40(3), pages 570-589.
    4. Michael Platzer & Thomas Reutterer, 2016. "Ticking Away the Moments: Timing Regularity Helps to Better Predict Customer Activity," Marketing Science, INFORMS, vol. 35(5), pages 779-799, September.
    5. Eric M. Schwartz & Eric T. Bradlow & Peter S. Fader, 2014. "Model Selection Using Database Characteristics: Developing a Classification Tree for Longitudinal Incidence Data," Marketing Science, INFORMS, vol. 33(2), pages 188-205, March.
    6. David A. Schweidel & Eric T. Bradlow & Peter S. Fader, 2011. "Portfolio Dynamics for Customers of a Multiservice Provider," Management Science, INFORMS, vol. 57(3), pages 471-486, March.
    7. Reutterer, Thomas & Platzer, Michael & Schröder, Nadine, 2021. "Leveraging purchase regularity for predicting customer behavior the easy way," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 194-215.

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