Work

Factors associated with future transit use intentions: Evidence from large, mid-sized, and small Canadian metropolitan areas

Year: 2026

Type: article

Abstract: Public transit agencies face challenges in sustaining and rebuilding ridership amid lasting impacts from the COVID-19 pandemic, making it crucial to understand who plans to use transit and why. We examine factors associated with intention to use public transit in the next year across Canada (4-point Likert scale) and assess how they vary by metropolitan area size. Using data from the Canadian Mobility Survey (N = 16,955) covering 12 census metropolitan areas, we estimate four weighted binary logistic regression models (i.e., a pooled national model and three metropolitan-area-size-specific models). Our results show that intention is strongly associated with recent transit use and self-identified transit-user status, with non-users exhibiting low intention. Baseline intention is also lower in mid-sized and small metropolitan areas than in large ones, consistent with urban scale capturing broader differences in transit context. Beyond this, higher satisfaction, perceptions that service is improving, seeing transit as suitable for reaching desired destinations, and support for increased operating funding are consistently associated with higher intention, as do living near rapid transit and deeming a 20–35-minute door-to-door transit trip as reasonable, especially in larger metropolitan areas. Car use functions as a strong barrier, particularly in mid-sized and small metropolitan areas, where driving shares are highest. Overall, similar factors are associated with intention across urban scales, but their strength varies, with mid-sized and small metropolitan areas facing greater structural and behavioral barriers. These findings are of interest to policymakers and transit planners interested in increasing and retaining ridership.

Source: Transport Policy

DOI: 10.1016/j.tranpol.2026.104175

Authors: Thiago Carvalho, Ahmed El-Geneidy

Institution: McGill University

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Good health and well-being

Open Access status: hybrid

Estimated APC paid: $2,890