IDEAS home Printed from https://ideas.repec.org/p/vnm/wpaper/176.html
   My bibliography  Save this paper

Modelling smoothly the joint effect of several advertising media on sales in a homogeneous market

Author

Listed:
  • Annamaria Sorato

    () (Department of Applied Mathematics, University of Venice)

  • Bruno Viscolani

    () (Department of Pure and Applied Mathematics, University of Padua)

Abstract

Decision on the use of different advertising media is a critical issue in marketing. Drawing on some literature related to the dynamic Nerlove-Arrow model, we propose a nonlinear programming framework for discussing how different advertising media may jointly affect the demand for a good. Starting from the idea that different advertising efforts may not simply add (linearly) to produce the demand result, we examine a few special media combination mechanisms which can be represented by smooth functions.

Suggested Citation

  • Annamaria Sorato & Bruno Viscolani, 2008. "Modelling smoothly the joint effect of several advertising media on sales in a homogeneous market," Working Papers 176, Department of Applied Mathematics, Universit√† Ca' Foscari Venezia.
  • Handle: RePEc:vnm:wpaper:176
    as

    Download full text from publisher

    File URL: http://virgo.unive.it/wpideas/storage/2008wp176.pdf
    File Function: First version, 2008
    Download Restriction: no

    References listed on IDEAS

    as
    1. repec:wsi:igtrxx:v:09:y:2007:i:04:n:s0219198907001606 is not listed on IDEAS
    2. Pradeep K. Chintagunta & Dipak Jain, 1992. "A Dynamic Model of Channel Member Strategies for Marketing Expenditures," Marketing Science, INFORMS, vol. 11(2), pages 168-188.
    3. Prasad A. Naik & Kalyan Raman & Russell S. Winer, 2005. "Planning Marketing-Mix Strategies in the Presence of Interaction Effects," Marketing Science, INFORMS, vol. 24(1), pages 25-34, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Marketing; Advertising; Production; Nonlinear programming;

    JEL classification:

    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:vnm:wpaper:176. 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: (Marco LiCalzi). General contact details of provider: http://edirc.repec.org/data/dmvenit.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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.