Invest in the ride: A 14 year longitudinal analysis of the determinants of public transport ridership in 25 North American cities

Boisjoly, Geneviève; Grisé, Emily; Maguire, Meadhbh; Veillette, Marie-Pier; Deboosere, Robbin; Berrebi, Emma; El-Geneidy, Ahmed

doi:10.1016/j.tra.2018.07.005

Cited by 81 publications

(71 citation statements)

References 26 publications

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“…In a longitudinal study of Utah Transit Authority ridership over 10 years, Lyons et al (2017) find that the change in proportion of white residents at a regional-level correlates negatively with the change in ridership. Boisjoly et al (2018) (2019) also find a positive relationship between the change in proportion of carless households and the change in ridership between 2012 and 2016 for clusters of large metropolitan areas but not for 4 smaller ones. These results help understand how the evolution of transit constituencies and their needs affect ridership on an aggregate level, but they lack the granularity to capture the impact of migration patterns happening locally.…”

Section: Urban Migrationmentioning

confidence: 94%

“…increased in recent years (Kain and Liu, 1999;Taylor et al, 2009;Chen et al, 2011;Boisjoly et al, 2018). Following post-recession service cuts, transit agencies in the United States have increased bus service (vehicle revenue miles) by 5.…”

mentioning

confidence: 99%

“…Finally, studies on the impact of ridehailing services on transit ridership have reached different conclusions (Boisjoly et al, 2018;Graehler Jr et al, 2019;Hall et al, 2018). To date, virtually all the research investigating ridership trends over time have used the metropolitan area or transit agency as the spatial unit of analysis.…”

mentioning

confidence: 99%

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Who’s ditching the bus?

Berrebi

Watkins

2020

Transportation Research Part A: Policy and Practice

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This paper uses stop-level passenger count data in four cities to understand the nation-wide bus ridership decline between 2012 and 2018. The local characteristics associated with ridership change are evaluated in Portland, Miami, Minneapolis/St-Paul, and Atlanta. Poisson models explain ridership as a cross-section and the change thereof as a panel. While controlling for the change in frequency, jobs, and population, the correlation with local socio-demographic characteristics are investigated using data from the American Community Survey. The effect of changing neighborhood demographics on bus ridership are modeled using Longitudinal Employer-Household Dynamics data. At a point in time, neighborhoods with high proportions of non-white, carless, and most significantly, high-school-educated residents are the most likely to have high ridership. Over time, white neighborhoods are losing the most ridership across all four cities. In Miami and Atlanta,places with high concentrations of residents with college education and without access to a car also lose ridership at a faster rate. In Minneapolis/St-Paul, the proportion of college-educated residents is linked to ridership gain. The sign and significance of these results remain consistent even when controlling for intra-urban migration. Although bus ridership is declining across neighborhood characteristics, these results suggest that the underlying cause of bus ridership decline must be primarily affecting the travel behavior of white bus riders.

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Section: Urban Migrationmentioning

confidence: 94%

mentioning

confidence: 99%

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Who’s ditching the bus?

Berrebi

Watkins

2020

Transportation Research Part A: Policy and Practice

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“…Although they found that the presence of Uber can increase or decrease transit ridership depending on the size and location of a transit agency, they concluded that the net effect of Uber on transit ridership was apparently positive. In another study, by using a longitudinal multilevel mixed-effect regression approach, Boisjoly et al [21] investigated the determining factors of public transit ridership over the period of 2002 to 2015 for 25 transit agencies in North America. According to the authors, characteristics of the metropolitan area (size and population), average fares, and car ownership were the major factors influencing ridership, and ridehailing had an overall positive (but statistically insignificant) impact on the outcome.…”

Section: Literature Reviewmentioning

confidence: 99%

Does Adoption of Ridehailing Result in More Frequent Sustainable Mobility Choices? An Investigation Based on the National Household Travel Survey (NHTS) 2017 Data

Das

2020

Smart Cities

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Among many changes potentially induced by the adoption of ridehailing, one key area of interest in transportation and urban planning research is how these services affect sustainable mobility choices, such as usage of public transit, walking, and biking modes and lower ownership of household vehicles. In this study, by using subsamples of the National Household Travel Survey (NHTS) 2017 data, propensity score matching technique is applied to generate matched samples of ridehailing adopters and non-adopters from ten different core-based statistical areas in the U.S. Results from multivariable count data regression models built on the matched samples indicate that, on average, the count of public transit trips is greater for adopters compared against identical non-adopters in all ten areas. Regarding average counts of walking and biking trips, adopters tend to make more trips in most of the places, although a few exceptions are also found. However, the relationship between ridehailing adoption and count of household vehicles appears to be more complicated as adopters, on average, seem to have a lower or higher number of vehicles than identical non-adopters, depending on the area. One major limitation of this study is that, in the statistical analyses, effects of attitudinal and detailed geographic variables are not directly controlled for, which complicates causal interpretations of findings.

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“…Media impacts on ridership specifically can be both positive and negative. For instance, Liu et al [30] found that positive social media campaigns can greatly increase ridership, while Boisjoly et al [31] found that transit messaging in the media and unreliable transportation scheduling websites could both lead to reduced ridership in some cases. Media influence, as a two-part framework with information selectivity, can also be used to explain mob mentality in online media platforms [32].…”

Section: Previous Workmentioning

confidence: 99%

The Association of Media and Environmental Variables with Transit Ridership

et al. 2020

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Transportation systems are central to all cities, and city planners and policy makers take special interest in assuring these systems are efficient, functional, sustainable, and, increasingly, that they have a positive impact on human health. In addition, vehicular emissions are increasingly costly to cities due to congestion and its impact on public health. This study aims to show the associations between the media and environmental variables and associated transit ridership. By tracking media influence, we illustrated how media coverage and attention to an issue over time may impact public opinion and ridership outcomes, especially at the local level where the issues are most salient. The relationship between air quality and transit ridership shown can be generally explained through a combination of infrastructure and human behavior. The media key terms examined in this analysis show that ridership is associated with favorable weather conditions and air quality, suggesting that ridership volume may be influenced by an overall sense of comfort and safety. Based on this analysis, we illustrated the role of media attention in both increased and decreased transit ridership and how such effects are compounded by air quality conditions (e.g., green, yellow, orange, and red air quality days).

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Invest in the ride: A 14 year longitudinal analysis of the determinants of public transport ridership in 25 North American cities

Cited by 81 publications

References 26 publications

Who’s ditching the bus?

Who’s ditching the bus?

Does Adoption of Ridehailing Result in More Frequent Sustainable Mobility Choices? An Investigation Based on the National Household Travel Survey (NHTS) 2017 Data

The Association of Media and Environmental Variables with Transit Ridership

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Invest in the ride: A 14 year longitudinal analysis of the determinants of public transport ridership in 25 North American cities

Cited by 81 publications

References 26 publications

Who’s ditching the bus?

Who’s ditching the bus?

Does Adoption of Ridehailing Result in More Frequent Sustainable Mobility Choices? An Investigation Based on the National Household Travel Survey (NHTS) 2017 Data

The Association of Media and Environmental Variables with Transit Ridership

Contact Info

Product

Resources

About

Invest in the ride: A 14 year longitudinal analysis of the determinants of public transport ridership in 25 North American cities