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A segment-level hazard approach to studying household purchase timing decisions

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  • Demetrios Vakratsas

    (McGill University, Montreal, Canada)

  • Frank M. Bass

    (University of Texas at Dallas, Dallas, Texas, USA)

Abstract

The increasing availability of customer-level data and the willingness of marketers to customize the timing of their offers to consumers makes the accurate segment-level description of household purchase timing decisions a compelling issue. In this paper we employ a finite mixture accelerated failure time model to identify and characterize household segments in terms of their purchasing rates and their propensity to accelerate purchases due to marketing mix activities. Such an approach also promises to alleviate possible aggregation problems arising from the use of a common hazard rate for all households. An application to household panel data suggested that infrequent buyers show higher propensity to accelerate than frequent buyers do, and that positive duration effects are underestimated when not accounting for segment-specific hazard rates. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Demetrios Vakratsas & Frank M. Bass, 2002. "A segment-level hazard approach to studying household purchase timing decisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(1), pages 49-59.
    • Handle: RePEc:jae:japmet:v:17:y:2002:i:1:p:49-59
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    References listed on IDEAS

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    2. Fok, Dennis & Paap, Richard & Franses, Philip Hans, 2012. "Modeling dynamic effects of promotion on interpurchase times," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3055-3069.
    3. Hernández-Mireles, C. & Franses, Ph.H.B.F., 2010. "The Launch Timing of New and Dominant Multigeneration Technologies," ERIM Report Series Research in Management ERS-2010-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Franses, Ph.H.B.F. & Hernández-Mireles, C., 2006. "When Should Nintendo Launch its Wii? Insights From a Bivariate Successive Generation Model," ERIM Report Series Research in Management ERS-2006-032-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Lee, Backjin & Timmermans, Harry J.P., 2007. "A latent class accelerated hazard model of activity episode durations," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 426-447, May.
    6. Diansheng Dong & Harry M. Kaiser, 2010. "Investigating household food interpurchase behavior through market segmentation," Agribusiness, John Wiley & Sons, Ltd., vol. 26(3), pages 389-404.
    7. Bas Donkers & Richard Paap & Jedid‐Jah Jonker & Philip Hans Franses, 2006. "Deriving target selection rules from endogenously selected samples," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 549-562, July.
    8. Andreeva, Galina & Ansell, Jake & Crook, Jonathan, 2007. "Modelling profitability using survival combination scores," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1537-1549, December.
    9. Dong, Diansheng & Kaiser, Harry M., 2006. "Investigating Coupon Effects on Household Interpurchase Behavior for Cheese," 2006 Annual meeting, July 23-26, Long Beach, CA 21314, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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