What drives intention to shift from car to the Québec tramway? A machine learning analysis

The Québec Tramway represents a significant electric rail investment designed to enhance urban mobility and decrease dependence on private automobiles in Québec City. Understanding the factors that encourage people to shift to sustainable modes is essential for effective policy design and transit operations. This study investigates residents’ stated intentions to transition from private car use to the tramway and identifies the primary factors associated with this intention. Survey data were collected from 1,400 residents of Québec City and Lévis between December 2025 and January 2026, covering sociodemographic characteristics, vehicle ownership, travel patterns, opinions regarding the tramway, and attitudinal, social, and psychological variables. The outcome variable measured stated intention to shift using three ordered categories: No, Probably, and Yes. Multiple modeling approaches were assessed, including several machine learning algorithms, with XGBoost demonstrating the highest predictive performance. Interpretation of the models using SHAP values and partial dependence plots indicates that shift intention is driven primarily by attitudes toward the tramway and perceived public transport experience, while sociodemographic factors play a secondary but meaningful role. Several key predictors exhibit threshold effects, suggesting that substantial improvements in reliability, comfort, and network connectivity are needed to move individuals from uncertainty to a definite intention to shift. These results provide actionable insights for tramway implementation and complementary policies to promote mode shift in Québec City.