PSO Based Grey Bass Model for Simulating New Product Diffusion

Abstract

The Bass model is one of the basic models for new product diffusion analysis. But the Bass model requires a large quantity of raw data to determine parameters of Bass model and this model also uses the potential capacity of market based on the subjective experience. To solve the problem of necessity of large raw data of Bass model, Wang put forward the Grey Bass model. Wang used non-linear least square (NLS) method to find the parameters of Grey Bass model and to assess the potential capacity of market. In the present paper a more appropriate method for Grey Bass equation is offered which estimates potential capacity of market even if the sample size is small. The proposed model is based on the minimization of sum of square of error between actual and predicted data using Particle Swarm Optimization (PSO) technique. Using the case study data, as used by Wang, the accuracy of the improved method is investigated. The results show that the mean absolute percentage error (MAPE) in the present case is 6.52 % compared to 7.93% reported by Wang.