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The Shape of Advertising Response Functions Revisited: A Model of Dynamic Probabilistic Thresholds

Author

Listed:
  • Demetrios Vakratsas

    () (McGill University and ALBA, Faculty of Management, 1001 Sherbrooke Street West, Montreal, Quebec, Canada H3A 1G5)

  • Fred M. Feinberg

    (University of Michigan Business School, 701 Tappan Street, Ann Arbor, Michigan 48109)

  • Frank M. Bass

    () (School of Management, University of Texas at Dallas, P.O. Box 830688, Richardson, Texas, 75083-0688)

  • Gurumurthy Kalyanaram

    () (GK Associates)

Abstract

Prior work in marketing has suggested that advertising —levels beneath which there is essentially no sales response—are rarely encountered in practice. Because advertising policies settle into effective ranges through early trial and error, thresholds cannot be observed directly, and arguments for their existence must be based primarily on a "statistical footprint," that is, on relative fits of a range of model types. To detect possible threshold effects, we formulate a switching regression model with two "regimes," in only one of which advertising is effective. Mediating the switch between the two regimes is a logistic function of category-specific dynamic variables (e.g., order of entry, time in market, number of competitors) and advertising levels, nesting a variety of alternative formulations, among them both standard concave and S-shaped responses. A sequence of comparisons among parametrically related models strongly suggests: that threshold effects exist; that market share response to advertising is not necessarily globally concave; that superior fit cannot be attributed to model flexibility alone; and that dynamic, environmental, competitive, and brand-specific factors can influence advertising effectiveness. These effects are evident in two evolving durables categories (SUVs and minivans), although not in the one mature, nondurable category (liquid detergent) studied.

Suggested Citation

  • Demetrios Vakratsas & Fred M. Feinberg & Frank M. Bass & Gurumurthy Kalyanaram, 2004. "The Shape of Advertising Response Functions Revisited: A Model of Dynamic Probabilistic Thresholds," Marketing Science, INFORMS, vol. 23(1), pages 109-119, April.
  • Handle: RePEc:inm:ormksc:v:23:y:2004:i:1:p:109-119
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    File URL: http://dx.doi.org/10.1287/mksc.1030.0035
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    References listed on IDEAS

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    Cited by:

    1. Masataka Ban & Nobuhiko Terui & Makoto Abe, 2011. "A brand choice model for TV advertising management using single-source data," Marketing Letters, Springer, vol. 22(4), pages 373-389, November.
    2. Philippe Aurier & Anne Broz-Giroux, 2014. "Modeling advertising impact at campaign level: Empirical generalizations relative to long-term advertising profit contribution and its antecedents," Marketing Letters, Springer, vol. 25(2), pages 193-206, June.
    3. Adachi, Kenji & Liu, Donald J., 2006. "Estimating Threshold Effects of Generic Fluid Milk and Cheese Advertising," 2006 Annual meeting, July 23-26, Long Beach, CA 21333, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Toker Doganoglu & Daniel Klapper, 2006. "Goodwill and dynamic advertising strategies," Quantitative Marketing and Economics (QME), Springer, vol. 4(1), pages 5-29, March.
    5. Ashish Sinha & J. Jeffrey Inman & Yantao Wang & Joonwook Park & Gerard J. Tellis & Rajesh K. Chandy & Deborah MacInnis & Pattana Thaivanich, 2005. "Practice Prize Reports," Marketing Science, INFORMS, vol. 24(3), pages 351-366, September.
    6. Taaffe, Kevin & Geunes, Joseph & Romeijn, H. Edwin, 2008. "Target market selection and marketing effort under uncertainty: The selective newsvendor," European Journal of Operational Research, Elsevier, vol. 189(3), pages 987-1003, September.
    7. Srivastava, Vaibhav & Bullo, Francesco, 2014. "Knapsack problems with sigmoid utilities: Approximation algorithms via hybrid optimization," European Journal of Operational Research, Elsevier, vol. 236(2), pages 488-498.
    8. Trichy V. Krishnan & Dipak C. Jain, 2006. "Optimal Dynamic Advertising Policy for New Products," Management Science, INFORMS, vol. 52(12), pages 1957-1969, December.
    9. Steven M. Shugan, 2006. "Editorial: Errors in the Variables, Unobserved Heterogeneity, and Other Ways of Hiding Statistical Error," Marketing Science, INFORMS, vol. 25(3), pages 203-216, 05-06.
    10. Yoau-Chau Jeng & Fei-Rung Chiu, 2010. "Allocation model for theme park advertising budget," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(2), pages 333-343, February.
    11. repec:wsi:ijitdm:v:16:y:2017:i:04:n:s0219622014400045 is not listed on IDEAS
    12. Nobuhiko Terui & Masataka Ban & Greg M. Allenby, 2011. "The Effect of Media Advertising on Brand Consideration and Choice," Marketing Science, INFORMS, vol. 30(1), pages 74-91, 01-02.
    13. Jean-Pierre Dubé & Günter Hitsch & Puneet Manchanda, 2005. "An Empirical Model of Advertising Dynamics," Quantitative Marketing and Economics (QME), Springer, vol. 3(2), pages 107-144, June.
    14. Vahideh Sadat Abedi, 2017. "Allocation of advertising budget between multiple channels to support sales in multiple markets," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(2), pages 134-146, February.
    15. John C. Liechty & Duncan K. H. Fong & Wayne S. DeSarbo, 2005. "Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis," Marketing Science, INFORMS, vol. 24(2), pages 285-293, November.
    16. Prasad A. Naik & Ashutosh Prasad & Suresh P. Sethi, 2008. "Building Brand Awareness in Dynamic Oligopoly Markets," Management Science, INFORMS, vol. 54(1), pages 129-138, January.
    17. Frank M. Bass & Anand Krishnamoorthy & Ashutosh Prasad & Suresh P. Sethi, 2005. "Generic and Brand Advertising Strategies in a Dynamic Duopoly," Marketing Science, INFORMS, vol. 24(4), pages 556-568, February.
    18. Steven M. Shugan, 2004. "Endogeneity in Marketing Decision Models," Marketing Science, INFORMS, vol. 23(1), pages 1-3.
    19. Ganesh Iyer & David Soberman & J. Miguel Villas-Boas, 2005. "The Targeting of Advertising," Marketing Science, INFORMS, vol. 24(3), pages 461-476, May.
    20. Mesak, Hani I. & Ellis, T. Selwyn, 2009. "On the superiority of pulsing under a concave advertising market potential function," European Journal of Operational Research, Elsevier, vol. 194(2), pages 608-627, April.
    21. Benedetto Molinari & Francesco Turino, 2015. "Advertising and Aggregate Consumption: A Bayesian DSGE Assessment," Working Papers 15.02, Universidad Pablo de Olavide, Department of Economics.
    22. Nobuhiko Terui & Masataka Ban, 2008. "Modeling heterogeneous effective advertising stock using single-source data," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 415-438, December.
    23. Nadja Silberhorn & Lutz Hildebrandt, 2012. "Does umbrella branding really work? Investigating cross-category brand loyalty," SFB 649 Discussion Papers SFB649DP2012-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Vakratsas, Demetrios, 2008. "The effects of advertising, prices and distribution on market share volatility," European Journal of Operational Research, Elsevier, vol. 187(1), pages 283-293, May.
    25. Lee, Chih-Ming & Hsu, Shu-Lu, 2011. "The effect of advertising on the distribution-free newsboy problem," International Journal of Production Economics, Elsevier, vol. 129(1), pages 217-224, January.

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