Modeling seasonal effects in the Bass Forecasting Diffusion Model

Abstract

The Bass Forecasting Diffusion Model is one of the most used models to forecast the sales of a new product. It is based on the idea that the probability of an initial sale is a function of the number of previous buyers. Almost all products exhibit seasonality in their sales patterns and these seasonal effects can be influential in forecasting the weekly/monthly/quarterly sales of a new product, which can also be relevant to making different decisions concerning production and advertising. The objective of this paper is to estimate these seasonal effects using a new family of distributions for circular random variables based on nonnegative trigonometric sums and to use this family of circular distributions to define a seasonal Bass model. Additionally, comparisons in terms of one-step-ahead forecasts between the Bass model and the proposed seasonal Bass model for products such as iPods, DVD players, and Wii Play video game are included.