IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v8y1989i4p358-370.html
   My bibliography  Save this article

Optimal Advertising Strategies

Author

Listed:
  • Maurice W. Sasieni

    (Ealing College of Higher Education, London)

Abstract

This paper considers advertising policies for a very general class of response functions. It is shown that if a pulsing policy is used, awareness (or sales) eventually settle down to a steady cycle and the average response over the cycle is a decreasing function of the length of the cycle. When response shows increasing returns to scale, it is possible (in theory) to use a device called to replace the true response by a straight line which lies above the true response in the region in which chattering is used. A numerical example is given to show how the optimal policy can be computed when part of the response is linear and the results obtained are compared with those of the best practicable approximation to chattering. It is shown that the problem of maximising awareness or sales, subject to a budget constraint, is structurally identical with maximising profit after advertising, with or without a constraint. In either case it is possible that, for part of the time, the optimal policy involves chattering.

Suggested Citation

  • Maurice W. Sasieni, 1989. "Optimal Advertising Strategies," Marketing Science, INFORMS, vol. 8(4), pages 358-370.
  • Handle: RePEc:inm:ormksc:v:8:y:1989:i:4:p:358-370
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.8.4.358
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.
    2. C. Robert Clark & Ignatius J. Horstmann, 2005. "Advertising and Coordination in Markets with Consumption Scale Effects," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 14(2), pages 377-401, June.
    3. Saffer, Henry & Chaloupka, Frank, 2000. "The effect of tobacco advertising bans on tobacco consumption," Journal of Health Economics, Elsevier, vol. 19(6), pages 1117-1137, November.
    4. 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.
    5. 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.
    6. 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.
    7. Mesak, Hani I., 1999. "On the generalizability of advertising pulsation monopoly results to an oligopoly," European Journal of Operational Research, Elsevier, vol. 117(3), pages 429-449, September.
    8. Jonker, J-J. & Piersma, N. & Van den Poel, D., 2002. "Joint optimization of customer segmentation and marketing policy to maximize long-term profitability," Econometric Institute Research Papers EI 2002-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. 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.
    10. Mesak, Hani I. & Calloway, James A., 1995. "A pulsing model of advertising competition: A game theoretic approach, part A -- Theoretical foundation," European Journal of Operational Research, Elsevier, vol. 86(2), pages 231-248, October.

    More about this item

    Keywords

    advertising; pulsing; optimality; computation;

    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:inm:ormksc:v:8:y:1989:i:4:p:358-370. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.