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Behavioral Measurement for Marketing Models: Estimating the Effects of Advertising Repetition for Media Planning

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  • Michael L. Ray

    (Stanford University)

  • Alan G. Sawyer

    (State University of New York at Buffalo)

Abstract

As management science models are developed in marketing, they make demands for more sophisticated inputs from the behavioral sciences. This is particularly true in the area of advertising media models. A continuing behavioral research program to develop estimates of repetition response functions for media models is reviewed. The program finds functions which differ importantly in level, slope and shape depending on the measure of response, market segment, product type, brand, advertising format, advertising illustration, advertisement color, media scheduling, ad appeal, and competitive situation. It is argued that such response function variations, found in both laboratory and field research, should be represented in media models. To illustrate this point, the results of a study of repetitive effects of one-sided (supportive) and two-sided (refutational) competitive advertisements are applied to runs of the MEDIAC planning system. Inclusion of the behavioral data produces favorable changes in MEDIAC output in terms of schedules and schedule results. The potential of further interaction between behavioral data and management science models is discussed.

Suggested Citation

  • Michael L. Ray & Alan G. Sawyer, 1971. "Behavioral Measurement for Marketing Models: Estimating the Effects of Advertising Repetition for Media Planning," Management Science, INFORMS, vol. 18(4-Part-II), pages 73-89, December.
    • Handle: RePEc:inm:ormnsc:v:18:y:1971:i:4-part-ii:p:p73-p89
    DOI: 10.1287/mnsc.18.4.P73
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    Cited by:

    1. Prasad A. Naik & Murali K. Mantrala & Alan G. Sawyer, 1998. "Planning Media Schedules in the Presence of Dynamic Advertising Quality," Marketing Science, INFORMS, vol. 17(3), pages 214-235.
    2. Frank M. Bass & Norris Bruce & Sumit Majumdar & B. P. S. Murthi, 2007. "Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship," Marketing Science, INFORMS, vol. 26(2), pages 179-195, 03-04.
    3. Donald G. Morrison & Jagmohan S. Raju, 2004. "50th Anniversary Article: The Marketing Department in Management Science: Its History, Contributions, and the Future," Management Science, INFORMS, vol. 50(4), pages 425-428, April.

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