IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v28y1980i2p321-347.html
   My bibliography  Save this article

Experimentation and Budgeting in Advertising: An Adaptive Control Approach

Author

Listed:
  • Dov Pekelman

    (Tel Aviv University, Tel Aviv, Israel)

  • Edison Tse

    (Stanford University, Stanford, California)

Abstract

This paper demonstrates how a general adaptive control scheme combines experimentation in advertising levels, estimation of sales advertising relationships, and the determination of advertising budgets. Various assumptions of current practices in experimentation and estimation are discussed and it is shown how these can be improved. A set of equations describing the sales-advertising system is proposed, its stochastic nature is analyzed, and an algorithm for calculating the adaptive control policies for this system is developed. To test the performance of the adaptive control scheme, the system is simulated under various conditions which include constant parameters, parameters which are varying over time, different initial estimates, and noise levels. Simulations of actual markets are then run and the amount of learning obtained by the adaptive control scheme is analyzed. Various extensions which can be easily incorporated in the general adaptive control scheme are specified.

Suggested Citation

  • Dov Pekelman & Edison Tse, 1980. "Experimentation and Budgeting in Advertising: An Adaptive Control Approach," Operations Research, INFORMS, vol. 28(2), pages 321-347, April.
  • Handle: RePEc:inm:oropre:v:28:y:1980:i:2:p:321-347
    DOI: 10.1287/opre.28.2.321
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.28.2.321
    Download Restriction: no

    File URL: https://libkey.io/10.1287/opre.28.2.321?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
    ---><---

    Citations

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


    Cited by:

    1. Fruchter, Gila E., 2001. "A dual control problem and application to marketing," European Journal of Operational Research, Elsevier, vol. 130(1), pages 99-110, April.
    2. Günter J. Hitsch, 2006. "An Empirical Model of Optimal Dynamic Product Launch and Exit Under Demand Uncertainty," Marketing Science, INFORMS, vol. 25(1), pages 25-50, 01-02.
    3. Mark G. Tang, 1993. "A stochastic machine maintenance and sale problem: Results with different production functions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(5), pages 677-696, August.

    More about this item

    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:oropre:v:28:y:1980:i:2:p:321-347. 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.

    We have no bibliographic 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.

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