Technology forecasting using a diffusion model incorporating replacement purchases

Abstract

Understanding the nature of the diffusion process is crucial for sustainable development of a new technology and product. This study introduces a replacement diffusion model that leads to a better understanding of the growth dynamics of a technology. The model operates in an environment with multiple competitors and overcomes the limitations of existing models. The model (1) consists of a diffusion model and an additional time series model; (2) separately identifies the diffusion of first-time purchases and that of replacement purchases; (3) incorporates players' marketing-mix variables, affecting a new technology diffusion; and (4) characterizes consumers' different replacement cycles. The proposed model is applied to South Korea's mobile handset market. The model performs well in terms of its fit and forecasting capability when compared with other diffusion models incorporating replacement and repeat purchases. The usefulness of the model stems from its ability to describe complicated environments and its flexibility in including multiple factors that drives diffusion in the regression analysis.