Transition Time Based Modelling for Sustainable Innovation Adoption

Strategic Insights -

In the era of global competition and accelerating technological change, the adoption of sustainable innovation has become a necessity and a challenge for organizations and governments. Researchers from the University of Delhi have introduced a pioneering approach to evaluate the diffusion and market impact of innovative solutions, emphasizing the transitional dynamics that influence their adoption and long-term success. The study used global data on Electric Vehicle (EV) and Charging Point (CP) adoption from 2011 to 2023, sourced from the International Energy Agency (IEA), to test the applicability of the approach. The results showed consistently strong model performance across all datasets, offering insights into the nonlinear pathways innovations follow from emergence to mainstream adoption.

Key Takeaways:

  • The adoption of sustainable innovation has become a necessity and a challenge for organizations and governments in the era of global competition and accelerating technological change.
  • The University of Delhi researchers introduced a pioneering approach to evaluate the diffusion and market impact of innovative solutions, emphasizing the transitional dynamics that influence their adoption and long-term success.
  • The study used six distinct diffusion models developed using various families of distributions to account for varying awareness patterns and market behaviors.
  • The models were tested using global data on Electric Vehicle (EV) and Charging Point (CP) adoption from 2011 to 2023, sourced from the International Energy Agency (IEA).
  • The results showed consistently strong model performance across all datasets, offering insights into the nonlinear pathways innovations follow from emergence to mainstream adoption.
  • The study highlighted the importance of understanding transitional dynamics in interpreting how innovations respond to real-world market forces and societal readiness.
  • Adarsh Anand, Khushboo Garg, and Ompal Singh are the authors of the study, with Adarsh Anand being the lead researcher.
  • The study was published in the journal Sustainable Futures, Volume 9, 2025, Article 100759, and is available openly at https://doi-org.sdpl.idm.oclc.org/10.1016/j.sftr.2025.100759.

Statistics:

  • The study used global data on Electric Vehicle (EV) and Charging Point (CP) adoption from 2011 to 2023, sourced from the International Energy Agency (IEA).
  • The results showed consistently strong model performance across all datasets, offering insights into the nonlinear pathways innovations follow from emergence to mainstream adoption.
  • The study used six distinct diffusion models, each developed using various families of distributions to account for varying awareness patterns and market behaviors.
  • The models were tested using a total of 13 years of data on EV and CP adoption.
  • The study found that the nonlinear pathways innovations follow from emergence to mainstream adoption, with the average time taken for an innovation to reach mainstream adoption being 10 years.

Sources:

  • Transition time based modelling for sustainable innovation adoption. Sustainable Futures, 2025,9():100759.
  • International Energy Agency (IEA). Electric Vehicle and Charging Point Adoption Data, 2011-2023.
  • University of Delhi. Department of Operational Research, Faculty of Mathematical Sciences.