Date
Wednesday, November 15, 2023
Time
8:30 AM - 10:00 AM
Name
Predictors of Electric Vehicle Adoption Intent in Rideshare Drivers Relative to Commuters
Session ID BECC
A7 - Lightning: Transportation
Track
Transportation
Jamie Rye
Description

Research examining electric vehicle (EV) adoption intent is growing, but neglects rideshare drivers (e.g., Uber & Lyft), who drive up to 13% of all miles driven in metropolitan areas. This study uses Noppers’ framework on sustainable innovation adoption to compare rideshare drivers to commuters on symbolic and instrumental attribute (e.g., costs, maintenance) perceptions, and their influences on EV adoption intent. It is possible that rideshare drivers have stronger symbolic attribute ratings than commuters because more people see their vehicles for extended periods of time, so what the vehicle signals about drivers may be more salient to drivers; alternatively, because rideshare drivers use their vehicles for work, drivers may perceive vehicles in primarily instrumental terms. We test these competing hypotheses using a survey of n=136 rideshare drivers and n=378 commuters. Relative to commuters, rideshare drivers rated symbolic attributes higher and EV maintenance costs more favorably, but fewer had access to a charging spot. A regression model found that symbolic attributes positively predicted EV adoption intent for both groups, though more weakly among rideshare drivers.

Supporting Document 1