Article ID: | iaor19931799 |
Country: | United Kingdom |
Volume: | 20 |
Issue: | 1 |
Start Page Number: | 35 |
End Page Number: | 48 |
Publication Date: | Jan 1993 |
Journal: | Computers and Operations Research |
Authors: | Arsham H. |
Keywords: | behaviour, marketing, markov processes |
This paper deals with the problem of scheduling optimal advertising policy for a very general class of consumer buying behavior models. To avoid analysis of a complex multitude of social-psychological and cultural-environmental factors affecting the consumer’s decision, a stochastic model is constructed. Because of the diminishing effect of even advertising policy, advertising pulsing policy (APP) is considered as a means to increase advertising effectiveness. By reducing the probabilistic evolution of sales and consumers’ attitude over time to their means, multivariate linear least-square regression is used to estimate the market parameters and validate the model. The prescribed strategy scheduling maximizes the discounted profit function, which includes uncertainty in sales over a finite campaign duration. The superiority of APP over an even advertising policy is illustrated numerically.