Researchers at UC Davis have been systematically collecting survey data from California consumers who have purchased plug-in vehicles (PEVs) over the period 2011 through 2017, in multiple waves at specific points in time. The data are rich in information required for understanding the consumer choice process, including household demographics, household fleet, PEV transaction details (including replacement vehicle), driving and recharging behavior, and geographic location, as well as responses to scaling questions related to knowledge and attitudes affecting their PEV purchase. In their current form, these data have been valuable for yielding many types of important research findings related to PEV penetration in California. However (again, in current form), these data are limited to only certain types of standard analyses.
This project proposes to integrate these data sets with a variety of other data sets that, when combined, can support more advanced analyses using state-of-the-art methods from discrete choice modeling. These include models that can address choice of PEV versus competing options in the market, as well as dynamic effects associated with ongoing penetration over time (expanding infrastructure, changes in awareness levels, and neighborhood effects) including the impact over time of California’s greenhouse gas policies and programs.