Adjusting the service? Understanding the factors affecting bus ridership over time at the route level in Montréal, Canada

Abstract

Like many cities across North America, Montréal has experienced shrinking bus ridership over recent years. Most literature has focused on the broader causes for ridership decline at the metropolitan or city level; few have considered ridership at the route level, particularly while accounting for various operational attributes and accessibility-to-jobs issues. Because service adjustments take place-and are felt by riders-at the route level, it is essential to explore busridership phenomena at this same scale. Our study explores the determinants of bus ridership at the route level between 2012 and 2017 using two longitudinal random-coefficients models in Montréal. Our findings suggest that increasing the number of daily bus trips along a route and improving the average route speed are key factors in securing bus ridership gains. The service area's regional accessibility to jobs by public transit around the route has a positive impact on bus ridership at the route level, showing the importance of land use and network structure.Additionally, our models show that reducing service frequency along a parallel route will lead to an increase in ridership along the main route. This study can be of use to transit planners and policymakers who require a more granular understanding of the factors that affect ridership at the route level.

On bus ridership and frequency

“… Tang and Thakuriah (2012) and Brakewood et al (2015) use fixed-effects models at the route level to evaluate the impact of real-time passenger information on ridership. More recently Diab et al (2020) modeled the impact of service attributes on ridership between 2012 and 2017 in Montreal, QC. They find a positive correlation with vehicle speed, number of stops, job accessibility, and several measures of service quantity, including frequency, a dummy variable for routes with headways less than 10 min, and a dummy variable for the express network.…”

Disaggregate Probabilistic Models to Predict Trip Generation Propensities and Mode Choice Behaviour

“…Overall, trip-generation propensities of both modes show a decline but is not statistically significant for the automobile trip-making propensity. This finding is in line with what has been reported for other regions (Diab, Deweese, et al, 2020;Diab, Kasraian, et al, 2020;Miller et al, 2018). There is a decreasing trend in transit usage among the younger populations as it is found that they are more reluctant to generate trips if they can fulfil their activities without physically leaving their place of residence (Alemi et al, 2019;Circella et al, 2016;Enam & Konduri, 2018;Olsson et al, 2020).…”

Making accessibility work in practice

“…While some research relates accessibility to various outcomes, such research needs to be developed further to provide stronger evidence on the impacts of improving accessibility. In our previous research with colleagues, we have shown that improving accessibility by public transport in a region will lead to increase in public transport use at various scales (stop, route, census tract and system levels) (Cui, Boisjoly, Miranda-Moreno, & El-Geneidy, 2020;Diab, DeWeese, Chaloux, & El-Geneidy, 2020;Owen & Levinson, 2015;Wu, Levinson, & Owen, 2021b).…”