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Regularity in individual shopping trips: implications for duration models in marketing

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  • Govert Bijwaard

Abstract

Most models for purchase-timing behavior of households do not take into account that many households have regular and non-shopping days. We propose a statistical model for purchase timing that exploits information on the shopping days of households. The model is formulated in a counting process framework that counts the recurrent purchases for each household over (calendar) time. In our empirical application of yogurt and detergent purchases from the ERIM1 database, we show that calendar time effects and regular and non-shopping days are important features to include in models for purchase-timing behavior. We find, for instance, that for these product categories the probability of purchasing is 50-60% higher on Saturdays and 70% higher on regular shopping days. We highlight the managerial implications of these model features by simulating some promotional actions.

Suggested Citation

  • Govert Bijwaard, 2010. "Regularity in individual shopping trips: implications for duration models in marketing," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1931-1945.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:11:p:1931-1945
    DOI: 10.1080/02664760903186064
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    1. Dipak C. Jain & Naufel J. Vilcassim, 1991. "Investigating Household Purchase Timing Decisions: A Conditional Hazard Function Approach," Marketing Science, INFORMS, vol. 10(1), pages 1-23.
    2. Jeongwen Chiang & Ching-Fan Chung & Emily Cremers, 2001. "Promotions and the pattern of grocery shopping time," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(7), pages 801-819.
    3. R. Dunn & S. Reader & N. Wrigley, 1983. "An Investigation of the Assumptions of the Nbd Model as Applied to Purchasing at Individual Stores," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 32(3), pages 249-259, November.
    4. Kristiaan Helsen & David C. Schmittlein, 1993. "Analyzing Duration Times in Marketing: Evidence for the Effectiveness of Hazard Rate Models," Marketing Science, INFORMS, vol. 12(4), pages 395-414.
    5. Bijwaard, Govert E. & Franses, Philip Hans & Paap, Richard, 2006. "Modeling Purchases as Repeated Events," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 487-502, October.
    6. Seetharaman, P B & Chintagunta, Pradeep K, 2003. "The Proportional Hazard Model for Purchase Timing: A Comparison of Alternative Specifications," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 368-382, July.
    7. Rita D. Wheat & Donald G. Morrison, 1990. "Assessing Purchase Timing Models: Whether or Not is Preferable to When," Marketing Science, INFORMS, vol. 9(2), pages 162-170.
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