عنوان مقاله [English]
In the new competitive world, companies use several types of tools and strategies to differentiate their products from competitors' products, one of which is promotional. Companies spend a large amount of their promotional budget on advertising. To increase the effectiveness of advertising budgeting, media planning must be properly developed and the manner allocation advertising be determined over a company's programming horizon. This paper investigates advertising media planning and budgeting for several products. Important aspects including life cycle stage, BCG matrix class, price, competitors' reaction, and budget constraint are considered in our model given uncertainty
and with the aim of maximizing profits at the end of the time horizon. This problem is formulated as a stochastic dynamic program and Approximate Dynamic Programming (ADP) algorithm is utilized to overcome the huge dimensionality. The mentioned problem is subject to considerable uncertainties. Approximate Dynamic Planning (ADP) is a powerful technique for solving discrete time problems under multistage stochastic control processes.
A numerical example was carried out on two products over the course of one year (12 monthly periods) with five different advertising packages. The results showed that 5 million iterations would be suitable for converging. Remaining budget analysis shows the percentage of selecting offensive packages in higher budgets for Product 2 and selection of such packages in the medium term for Product 1.The process of the life cycle shows that Product 1 does not most likely complete its life stages, while Product 2 completes its life cycle stages. Moreover, the BCG matrix confirms the results and Product 2 is in the final stages of dogs, while Product 1 is more likely in Cash Cows. Also, the total budget was examined in different quantities, which showed that as the amount of the budget increased, the target amount increased slowly. The
presented model offers the opportunity to managers by which they are able to compare different media for making advertising decisions on various products in an uncertain environment with different budgets.