Suggested Citation:
Ramadoss, Trisha, Jae Hyun Lee, Adam Davis, Scott Hardman, Gil Tal (2025)

Classifying Electric Vehicle Adopters and Forecasting Progress to Full Adoption

Electric light-duty vehicle sales are increasing, but adoption is not uniform. Forecasting who is adopting and when is crucial to planning infrastructure, creating incentives, and ensuring equity. We identify different clusters of adopters in California, examine adoption rates within them, and forecast adoption trajectories. Clusters are classified by revealed characteristics using results from a multi-year survey of 18,921 plug-in electric vehicle (PEV) adopters. Eight clusters are identified: four each among single-vehicle and multi-vehicle households. We classify the population into these segments and simulate future PEV adoption using Bass diffusion. We compare adoption trajectories—assuming current rates of adoption, a scenario of 100% new vehicle sales by 2035, and a scenario of “net zero” by 2045. Our analysis finds large clusters with low to-date PEV adoption, encompassing 47% of the population, and results reveal some clusters are not on track to meet California sales targets and/or climate goals.