What drives electric vehicle adoption? Affordability, range, and charging access in a U.S. stated-choice experiment

Despite increasing policy attention, U.S. electric vehicle (EV) uptake remains uneven. This study examines how relative affordability, vehicle range, and charging access shape EV choice in a U.S. stated-choice experiment containing 5,898 task-level observations from 983 respondents. Rather than treating the data as purely observational, we leverage experimentally varied scenario attributes and estimate counterfactual response curves using grouped cross-fitted random forest and XGBoost models embedded in a G-computation framework. Probability forecasts are calibrated before counterfactual standardization and evaluated with both discrimination and calibration diagnostics. Results reveal clear threshold and diminishing-return effects. Affordability has the greatest influence when EV prices are near a consumer’s budget, with smaller gains beyond that point. Vehicle range significantly increases EV choice up to about 300 miles, after which additional range has a limited impact. Charging access, particularly from home and at the town level, is strongly predictive of EV choice, with walking distance and the absence of nearby fast charging both reducing stated EV choice. These findings suggest that the largest changes in stated EV-choice probability occur when consumers cross affordability thresholds, vehicles reach sufficient rather than maximal range, and convenient home-adjacent and town-level charging becomes available. The study’s primary contribution is empirical and substantive. It uses experimentally grounded, probability-calibrated response curves to quantify the shape, relative magnitude, and threshold-like behavior of stated EV-choice responses to policy-relevant attributes on a common probability scale.