IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v23y1977i12p1284-1294.html
   My bibliography  Save this article

Determining Sample Size for Pretesting Comparative Effectiveness of Advertising Copies

Author

Listed:
  • Siddhartha R. Dalal

    (Rutgers University)

  • V. Srinivasan

    (Stanford University)

Abstract

This paper considers the problem of determining optimal sample sizes in advertising pretests, where two or more copies are compared for their relative advertising effectiveness measured on a dichotomous (0 or 1) scale. As the sample size is increased, sampling variations decrease so that the pretest has a better chance of identifying the truly best ad. Consequently, increasing the sample size decreases the opportunity costs of not selecting the best ad which, however, have to be balanced against the increased sampling costs. Taking these two considerations into account, three approaches (indifference zone, minimizing maximum loss and Bayesian) for determining sample size are discussed. The minimizing maximum loss approach seems to offer the best compromise in terms of realistic modelling and practical implementability. Extensions of the approaches to the case where advertising effectiveness is measured on an interval scale are outlined.

Suggested Citation

  • Siddhartha R. Dalal & V. Srinivasan, 1977. "Determining Sample Size for Pretesting Comparative Effectiveness of Advertising Copies," Management Science, INFORMS, vol. 23(12), pages 1284-1294, August.
  • Handle: RePEc:inm:ormnsc:v:23:y:1977:i:12:p:1284-1294
    DOI: 10.1287/mnsc.23.12.1284
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.23.12.1284
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.23.12.1284?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
    ---><---

    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:ormnsc:v:23:y:1977:i:12:p:1284-1294. 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.