Transition time based modelling for sustainable innovation adoption

In an era of global competition and accelerating technological change, the adoption of sustainable innovation has become both a necessity and a challenge. As the world moves toward achieving the Sustainable Development Goals (SDGs), organizations and governments must grapple with the uncertainties and complexities of implementing large-scale innovation. Innovation rarely follows a linear path—it unfolds through dynamic phases of transition that influence how new solutions are received, integrated, and scaled. Understanding these transitions is essential to interpreting how innovations respond to real-world market forces and societal readiness. This paper introduces a pioneering approach to evaluate the diffusion and market impact of such innovations, emphasizing the transitional dynamics that influence their adoption and long-term success. To test the applicability of this approach, six distinct diffusion models are developed using various families of distributions to account for varying awareness patterns and market behaviours. Empirical validation is conducted using global data on Electric Vehicle (EV) and Charging Point (CP) adoption from 2011 to 2023, sourced from the International Energy Agency (IEA). Results show consistently strong model performance across all datasets, offering insights into the nonlinear pathways innovations follow from emergence to mainstream adoption.