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On the superiority of pulsing under a concave advertising market potential function


  • Mesak, Hani I.
  • Ellis, T. Selwyn


The authors study the superiority of advertising pulsing policy (turning advertising on and off in a cyclic fashion) over its uniform (constant spending) counterpart that costs the same under the assumption that sales dynamics follow a modified Vidale-Wolfe aggregate advertising model. The authors show that pulsing can be superior if the product of the concave market potential function and the linear or concave advertising response function is convex in advertising. Similar to previous studies in the literature, the average undiscounted profit over the infinite planning horizon is considered as a performance measure according to which alternative advertising pulsation policies are compared. Employing a well-known data set relating advertising to sales, the above convexity requirement is empirically supported and the superiority of pulsing is established numerically. The performance of the proposed model is found to be superior to two rival models using a one-step-ahead forecasting procedure. The analytical findings of the study are documented into six theoretical results for which proofs are relegated to a separate appendix. Managerial implications of the study and directions for future research are also discussed.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:194:y:2009:i:2:p:608-627

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    References listed on IDEAS

    1. Philip Kotler, 1965. "Competitive Strategies for New Product Marketing Over the Life Cycle," Management Science, INFORMS, vol. 12(4), pages 104-119, December.
    2. Joseph O. Eastlack, Jr. & Ambar G. Rao, 1986. "Modeling Response to Advertising and Pricing Changes for “V-8” Cocktail Vegetable Juice," Marketing Science, INFORMS, vol. 5(3), pages 245-259.
    3. Prasad A. Naik & Murali K. Mantrala & Alan G. Sawyer, 1998. "Planning Media Schedules in the Presence of Dynamic Advertising Quality," Marketing Science, INFORMS, vol. 17(3), pages 214-235.
    4. Fred M. Feinberg, 2001. "On Continuous-Time Optimal Advertising Under S-Shaped Response," Management Science, INFORMS, vol. 47(11), pages 1476-1487, November.
    5. Maurice W. Sasieni, 1971. "Optimal Advertising Expenditure," Management Science, INFORMS, vol. 18(4-Part-II), pages 64-72, December.
    6. Maurice W. Sasieni, 1989. "Optimal Advertising Strategies," Marketing Science, INFORMS, vol. 8(4), pages 358-370.
    7. Aneel Karnani, 1983. "Minimum Market Share," Marketing Science, INFORMS, vol. 2(1), pages 75-93.
    8. Minhi Hahn & Jin-Sok Hyun, 1991. "Advertising Cost Interactions and the Optimality of Pulsing," Management Science, INFORMS, vol. 37(2), pages 157-169, February.
    9. Vijay Mahajan & Eitan Muller, 1986. "Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 89-106.
    10. Fred M. Feinberg, 1992. "Pulsing Policies for Aggregate Advertising Models," Marketing Science, INFORMS, vol. 11(3), pages 221-234.
    11. Vijay Mahajan & Eitan Muller, 1986. "Reply—Reflections on Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 110-111.
    12. J. Miguel Villas-Boas, 1993. "Predicting Advertising Pulsing Policies in an Oligopoly: A Model and Empirical Test," Marketing Science, INFORMS, vol. 12(1), pages 88-102.
    13. 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.
    14. Kristian S. Palda, 1964. "The Measurement of Cumulative Advertising Effects," The Journal of Business, University of Chicago Press, vol. 38, pages 162-162.
    15. Hani I. Mesak, 1992. "An Aggregate Advertising Pulsing Model with Wearout Effects," Marketing Science, INFORMS, vol. 11(3), pages 310-326.
    16. 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.
    17. Dan Horsky, 1977. "An Empirical Analysis of the Optimal Advertising Policy," Management Science, INFORMS, vol. 23(10), pages 1037-1049, June.
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    Cited by:

    1. Martín-Herrán, Guiomar & Sigué, Simon P., 2017. "An integrative framework of cooperative advertising: Should manufacturers continuously support retailer advertising?," Journal of Business Research, Elsevier, vol. 70(C), pages 67-73.
    2. Mesak, Hani Ibrahim & Bari, Abdullahel & Lian, Qin, 2015. "Pulsation in a competitive model of advertising-firm's cost interaction," European Journal of Operational Research, Elsevier, vol. 246(3), pages 916-926.
    3. Huang, Jian & Leng, Mingming & Liang, Liping, 2012. "Recent developments in dynamic advertising research," European Journal of Operational Research, Elsevier, vol. 220(3), pages 591-609.
    4. Haase, Knut & Müller, Sven, 2014. "Upper and lower bounds for the sales force deployment problem with explicit contiguity constraints," European Journal of Operational Research, Elsevier, vol. 237(2), pages 677-689.


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