Publication Detail
Ridehailing Drivers’ Perceptions and Adoption of Electric Vehicles: Insights From a Stratified Random Sample Survey
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UCD-ITS-RP-26-08 Journal Article |
Suggested Citation:
Giller, James, Xiatian Iogansen, Giovanni Circella, Mischa Young, Yongsung Lee, Patrick Loa (2026)
Ridehailing Drivers’ Perceptions and Adoption of Electric Vehicles: Insights From a Stratified Random Sample Survey
. Case Studies on Transport PolicyThe Clean Miles Standard regulation in California regulates ridehailing fleet electrification; however, ridehailing drivers face unique challenges in adopting electric vehicles (EVs). Based on a survey of ridehailing drivers in California, this paper provides unique insights into ridehailing drivers’ behaviors and perspectives towards vehicle electrification. Data were collected between October 2023 and June 2024 via an online questionnaire. A stratified random sampling procedure was used to recruit drivers statewide, resulting in a final sample of 1,357 ridehailing drivers. The data were used to investigate the characteristics associated with the current use of an EV for ridehailing work, and differences in drivers’ perspectives based on their working hours and household income, which are underexplored topics in the literature. Key findings include that perceiving public fast chargers as being available seems to have a greater impact on the probability of using an EV for ridehailing work than other types of public charger, and the perceived availability of home chargers is at best weakly associated with EV use. Full-time drivers are more likely to currently use an EV than other drivers, controlling for other factors; however, they are concerned about the driving range of EVs and their ability to learn how to use an EV for their ridehailing work. Drivers from low-income households have lower familiarity with or utilization of EV incentives and are less likely to perceive home chargers as being available. These insights can help shape policies to accelerate vehicle electrification and contribute to equitable outcomes in California and beyond.
Key words:
ridehailing, electric vehicles, survey data, charging infrastructure, California, logistic regression