Investigating diffusion dynamics of disruptive technologies: leapfrogging, cannibalisation and coexistence

Purpose Understanding how customers transition to newer technologies is crucial for demand forecasts, pricing decisions and production planning. This study develops a computational framework to help firms address challenges like cannibalisation, leapfrogging and coexistence. Design/methodology/approach A two-dimensional diffusion model is proposed that captures how users disengage from an existing product and adopt its successor. The model employs the Cobb-Douglas production function to establish the relationship between dynamic pricing and innovation goodwill. Our model is benchmarked against the leading models in the literature, utilising sales data from the electronics (personal computers and tablet PCs) and automotive (passenger cars and electric vehicles) industries. Parameters are estimated using a genetic algorithm, and the model’s effectiveness is assessed in nowcasting and forecasting adoption dynamics through experimental testing and rolling cross-validation. Findings The proposed model delivers forecasts superior to those of existing diffusion models and offers a deeper understanding of how pricing and user behaviour affect the adoption of new technologies. It offers businesses the insights needed to anticipate shifts in market demand and plan more effectively. Practical implications The model provides a systematic approach to support decisions in lifecycle management. It helps businesses plan market entry, set effective prices and align production with shifting demand. It equips firms to manage overlapping product generations and prepare for technology-driven shifts in the market. Originality/value This study introduces a novel framework for analysing technology adoption by integrating price dynamics and customer disengagement. It provides an empirical tool for understanding market behaviour during technological change.