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Optimal advertising pulsation policies: a dynamic programming approach

Author

Listed:
  • H I Mesak

    (Louisiana Tech University)

  • H Zhang

    (East Central University)

Abstract

This study formulates and solves an advertising pulsation problem for a monopolistic firm using dynamic programming (DP). The firm aims at maximising profit through an optimal allocation of the advertising budget in terms of rectangular pulses over a finite planning horizon. Aggregate sales response to the advertising effort is assumed to be governed by a modified version of the Vidale–Wolfe model in continuous time proposed by Little. Using a numerical example in which a planning horizon of one year is divided into one, two through ten equal time periods, computing routines are developed to solve 150 DP problems. Computational results show among other findings that the performance yielded by the DP policy dominates the uniform advertising policy (constant spending) for a concave advertising response function and the advertising pulsing policy (turning advertising on and off) for a linear or convex response function.

Suggested Citation

  • H I Mesak & H Zhang, 2001. "Optimal advertising pulsation policies: a dynamic programming approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(11), pages 1244-1255, November.
  • Handle: RePEc:pal:jorsoc:v:52:y:2001:i:11:d:10.1057_palgrave.jors.2601219
    DOI: 10.1057/palgrave.jors.2601219
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    Citations

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    Cited by:

    1. Alexander E. Saak, 2012. "Dynamic Informative Advertising of New Experience Goods," Journal of Industrial Economics, Wiley Blackwell, vol. 60(1), pages 104-135, March.
    2. Mercedes Esteban-Bravo & José Múgica & Jose Vidal-Sanz, 2005. "Optimal Duration of Magazine Promotions," Marketing Letters, Springer, vol. 16(2), pages 99-114, April.
    3. H Zhang & H I Mesak, 2010. "Optimal multi-period service capacity allocation and pricing allowing for uncertain competitive entry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(5), pages 780-789, May.
    4. Yanwu Yang & Baozhu Feng & Joni Salminen & Bernard J. Jansen, 2022. "Optimal advertising for a generalized Vidale–Wolfe response model," Electronic Commerce Research, Springer, vol. 22(4), pages 1275-1305, December.
    5. Parham Fami Tafreshi & Mohammad Hasan Aghdaie & Majid Behzadian & Mahdieh Ghani Abadi, 2016. "Developing a Group Decision Support System for Advertising Media Evaluation: A Case in the Middle East," Group Decision and Negotiation, Springer, vol. 25(5), pages 1021-1048, September.
    6. Zakaria Babutsidze, 2009. "Learning How to Consume and Returns to Product Promotion," Papers on Economics and Evolution 2009-05, Philipps University Marburg, Department of Geography.
    7. Zakaria Babutsidze, 2011. "Returns to product promotion when consumers are learning how to consume," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 783-801, December.

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