Access the full text.
Sign up today, get DeepDyve free for 14 days.
L. Lodish (1971)
Considering Competition in Media PlanningManagement Science, 17
E. Hilgard, D. Marquis, G. Kimble (1961)
Hilgard and Marquis' Conditioning and learning
Hubert Zielske (1959)
The remembering and forgetting of advertising.Journal of Marketing, 23
G. Day (1970)
Using Attitude Change Measures to Evaluate New Product IntroductionsJournal of Marketing Research, 7
C. Hovland, I. Janis, H. Kelley (1953)
Communication And Persuasion
M. Ray, Alan Sawyer (1971)
Repetition in Media Models: A Laboratory TechniqueJournal of Marketing Research, 8
Alexander Biel, J. Haskins (1970)
How to Evaluate Mass CommunicationsJournal of Marketing Research, 7
J. Little (2011)
A Model of Adaptive Control of Promotional SpendingOper. Res., 14
P. Kotler (1964)
Toward an Explicit Model for Media SelectionJournal of Advertising Research, 4
D. Gensch (1970)
Media Factors: A Review ArticleJournal of Marketing Research, 7
J. Little, L. Lodish (1969)
A Media Planning CalculusOper. Res., 17
P. Tannenbaum (1967)
The Congruity Principle Revisited: Studies in the Reduction, Induction, and Generalization Of Persuasion1Advances in Experimental Social Psychology, 3
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.
Management Science – INFORMS
Published: Dec 1, 1971
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.