IDEAS home Printed from https://ideas.repec.org/p/ags/aaea06/21314.html
   My bibliography  Save this paper

Investigating Coupon Effects on Household Interpurchase Behavior for Cheese

Author

Listed:
  • Dong, Diansheng
  • Kaiser, Harry M.

Abstract

In this study, a market segmentation approach is developed and applied to analyze U.S. household cheese purchases. The segmentation is based on household interpurchase time or the hazard rate of purchases. The hazard rate for a household belonging to a given segment is a function of household demographic and marketing-mix variables, and its baseline is assumed to follow a Weibull distribution. The model is flexible and is able to yield increasing, decreasing, or constant hazard rate functions. Four segments have been discovered in the U.S. household cheese purchase market. Two of the segments contain about 40% of the cheese purchase households, which are frequent buyers with an average interpurchase time of 2 weeks. These frequent cheese purchase households are larger in size, with higher income, less proportion of African Americans, and are insensitive to coupons. They are often referenced in the marketing literatures as loyal customers. In contrast, the other two segments contain about 60% of the households, which are infrequent buyers with an average interpurchase time of 6 weeks. These infrequent cheese purchase households are smaller in size, with lower income, higher proportion of African Americans, and are sensitive coupons. The infrequent purchase households are usually the targets of marketing promotions.

Suggested Citation

  • 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).
  • Handle: RePEc:ags:aaea06:21314
    DOI: 10.22004/ag.econ.21314
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/21314/files/sp06do03.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.21314?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-679, June.
    3. Deaton, Angus, 1988. "Quality, Quantity, and Spatial Variation of Price," American Economic Review, American Economic Association, vol. 78(3), pages 418-430, June.
    4. 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.
    5. Timothy J. Richards, 2000. "A discrete|continuous model of fruit promotion, advertising, and response segmentation," Agribusiness, John Wiley & Sons, Ltd., vol. 16(2), pages 179-196.
    6. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    7. Brian Gould, 1997. "Consumer promotion and purchase timing: the case of cheese," Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 445-457.
    8. Diansheng Dong & J.S. Shonkwiler & Oral Capps, 1998. "Estimation of Demand Functions Using Cross-Sectional Household Data: The Problem Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(3), pages 466-473.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Dong, Diansheng & Stewart, Hayden, 2008. "Household Food Purchase Patterns: The Case of Vegetables," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6428, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Dong, Diansheng & Stewart, Hayden & McLaughlin, Patrick W., 2017. "A New Approach for Modeling Household Food Demand with Panel Data: The Case of Cold Cereals," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258195, Agricultural and Applied Economics Association.
    4. Øystein Myrland & Diansheng Dong & Harry M. Kaiser, 2007. "Quantity versus quality effects of generic advertising: The case of Norwegian salmon," Agribusiness, John Wiley & Sons, Ltd., vol. 23(1), pages 85-100.
    5. 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.
    6. 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.
    7. Davis, Christopher G. & Dong, Diansheng & Blayney, Donald P. & Yen, Steven T. & Stillman, Richard, 2012. "U.S. Fluid Milk Demand: A Disaggregated Approach," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 15(1), pages 1-26, February.
    8. Dong, Diansheng & Kaiser, Harry M., 2003. "Estimation of a Censored AIDS Model: A Simulated Amemiya-Tobin Approach," Research Bulletins 122113, Cornell University, Department of Applied Economics and Management.
    9. 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.
    10. Crentsil, Christian & Gschwandtner, Adelina & Wahhaj, Zaki, 2020. "The effects of risk and ambiguity aversion on technology adoption: Evidence from aquaculture in Ghana," Journal of Economic Behavior & Organization, Elsevier, vol. 179(C), pages 46-68.
    11. Dimara, Efthalia & Skuras, Dimitris, 1999. "Regional Image and the Promotion of Quality Products," ERSA conference papers ersa99pa023, European Regional Science Association.
    12. Dennis Fok & Richard Paap, 2009. "Modeling category‐level purchase timing with brand‐level marketing variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 469-489, April.
    13. Bhat, Chandra R., 1996. "A hazard-based duration model of shopping activity with nonparametric baseline specification and nonparametric control for unobserved heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 189-207, June.
    14. Bhat, Chandra R. & Steed, Jennifer L., 2002. "A continuous-time model of departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 207-224, March.
    15. Meade, Nigel & Islam, Towhidul, 2010. "Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study," European Journal of Operational Research, Elsevier, vol. 200(3), pages 908-917, February.
    16. Gould, Brian W. & Dong, Diansheng, 2004. "Product Quality And The Demand For Food: The Case Of Urban China," 2004 Annual meeting, August 1-4, Denver, CO 20010, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Hayden Stewart & Noel Blisard, 2008. "Who Pays More for Food?," Journal of Agricultural Economics, Wiley Blackwell, vol. 59(1), pages 150-168, February.
    18. Iliescu, Dan C. & Garrow, Laurie A. & Parker, Roger A., 2008. "A hazard model of US airline passengers' refund and exchange behavior," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 229-242, March.
    19. Dong, Diansheng & Chung, Chanjin & Kaiser, Harry M., 2001. "Panel Data Double-Hurdle Model: An Application To Dairy Advertising," 2001 Annual meeting, August 5-8, Chicago, IL 20502, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Dong, Diansheng & Lin, Biing-Hwan, 2009. "Fruit and Vegetable Consumption by Low-Income Americans: Would a Price Reduction Make a Difference?," Economic Research Report 55835, United States Department of Agriculture, Economic Research Service.

    More about this item

    Keywords

    Consumer/Household Economics;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea06:21314. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.