DOI: 10.25338/b8035d
title: Understanding the impact of public charging infrastructure on the consideration to purchase an electric vehicle in California

description: 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. 
description: 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.
description: Data can be viewed with Excel.