Understanding the impact of public charging infrastructure on the consideration to purchase an electric vehicle in California

This research tests an implicit assumption on investment in plug-in electric vehicle (PEV) charging infrastructure: people who are not already interested in PEVs will see public PEV charging and become interested in PEVs. Data from a survey of car-owning households in California are combined with data on public PEV charging and PEV registrations to estimate a structural equation model of the extent to which participants have considered acquiring a battery electric vehicle (BEV) or plug-in hybrid electric vehicle (PHEV), and whether participants report seeing PEV charging. The model controls for socio-economic and demographic measures and participants' awareness, knowledge, and assessments of PEVs, and the known correlation between PEV registrations and public charging locations. Using logistic ordinal regression we also assess whether charger density near workplaces affects the results. All results contradict the assumption that people will see charging infrastructure and that more charging—rather than more people seeing charging—means more people will consider purchasing a BEV or PHEV. Rather, prior interest and positive assessments of PEVs, allow people to see PEV charging. In short, interest in PEVs is a prerequisite to people seeing PEV charging.Data can be viewed with Excel.Funding provided by: UC Davis Institute of Transportation Studies*Crossref Funder Registry ID: Award Number:We use data from car-owning households (all cars, not just PEVs) from a survey completed in 2021 by nearly 3,000 respondents across California. These data are supplemented by data on the contemporaneous (with the household survey) counts of charging locations and PEV registrations in survey participants' home zip codes. The analysis also controls for density of PEVs in the participants' home zip codes as there is geographic correlation between PEVs and PEV charging infrastructure. Further, the analysis includes whether participants see PEV charging. The survey instrument also measured consumer awareness, knowledge, assessments, and consideration of PEVs. The sample was recruited by a professional survey firm. Participants were recruited from panels of people maintained by such firms for the express purpose of participating in research. Participants are typically screened based on criteria relevant to each study to which they are invited. Firms providing this service typically reward participation based on how many studies a person completes and the time and effort required to do so. Because all recruiting was done by the vendor and because these firms typically maintain cooperative relationships with each other allowing them to recruit from each other's panels, the number of initial invitations to the pre-screening questionnaire for this study is unknown. Thus, a traditional response rate cannot be calculated. What is known is the number of people who screened into this study's questionnaire and how many completed it. The completion rate was in the low-70 percentages. Participants were screened into this study via a pre-questionnaire establishing eligibility, determined primarily by respondent age (for reasons of informed consent and for quota sampling), respondent sex, household vehicle ownership (for basic eligibility), household income, and residential zip code. Quotas for age, sex, and income were set to match regional distributions within California for car-owning households. The analysis here is for the state