Demand forecasting of technological products considering re-purchasing and dynamic pricing: a modified diffusion model

Accurately predicting the growth curve of technological innovations during their product life cycle is essential for a firm’s strategic planning and survival in an ever-increasing competitive environment. The dissemination of innovation among prospective customers is commonly measured using the diffusion process. Despite considerable research on modeling the diffusion dynamics of innovation, no sustainable model focuses on repurchasing behavior under the effect of price change and time-varying adoption rate. Consequently, the present study develops a new sales forecast model to analyze the propagation of technological products using the two-dimensional framework that integrates the effect of price change and its continuation time in the market. A Cobb–Douglas function has been utilized to mathematically relate the dynamic price and goodwill of the innovation to the product’s value. The dynamic behavior of the adoption rate is described using the concept of change-point. A control chart (or c-chart) is utilized to identify the change-point location in the diffusion process of the technological products. The proposed model is fitted to the historical data from two industries, Electronics and Automobiles, using a non-linear least square (NLS) estimation procedure to demonstrate its practical applicability. The empirical analysis shows that the proposed model fits better than well-established diffusion models.