Decision Sciences Journal
Volume 27, Number 3
Summer 1996
Determining Optimal Advertising Strategies: A Markov Decision
Model Approach
Vijay S. Desai
McIntire School of Commerce, University of Virginia,
Charlottesville, VA 22903
Amit Gupta
Graduate School of Business, University of Wisconsin, Madison, WI
53706
ABSTRACT
This study falls in the class of models in which advertising
wearout and the differences between the learning and forgetting of
advertisements are explicitly included. A discrete time Markov
decision modeling approach is used to obtain optimal control limit
policies, and an algorithm is provided to identify these policies.
A control limit policy specifies whether or not to advertise in a
specific time period on the basis of the level of awareness in that
time period. Thus, the duration for which advertising is not done
is determined endogenously, and the algorithm helps determine this
duration for a given set of parameters. This is a particularly
desirable feature, since advertising practitioners are interested
in determining the optimal duration of advertising pulses.
Computational experience suggests that the algorithm is very fast
and easy to implement. Also, conditions on model parameters
indicating the relative efficacy of pulsing versus uniform
advertising are provided.
Subject Areas: Marketing, Mathematics and Quantitative
Techniques/Methodology.
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