Exploring spatio-temporal commuting patterns in a university environment

Delmelle, Eric; Delmelle, Elizabeth C.

doi:10.1016/j.tranpol.2011.12.007

Cited by 140 publications

(116 citation statements)

References 14 publications

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“…Additionally, the complex and distinctive travel behavior of university students who commute for three or more years to the same place, and are potential active commuters given their age and income situation, is well known (Delmelle & Delmelle, 2012;Limanond, Butsingkorn, & Chermkhunthod, 2011;Miralles-Guasch & Domene, 2010;Zhou, 2012). Students participate more in social or recreational activities than the general population, making more daily trips (Khattak, Wang, Son, & Agnello, 2011).…”

Section: Different Destination Different Commuting Pattern? Analyzinmentioning

confidence: 99%

“…The commuting pattern of students is also influenced by their socioeconomic status, namely the number of cars in their household (B=1.443, p=.000), the size of their household (B=-.532, p=.000), and their income -in comparison to a student with a monthly income of only €500/month, a student with an income of more than €4000/month is almost twice as likely to commute by car (B=1.970, p=.002). Younger students are less frequently car commuters than older students, probably due to their family composition, which is known to influence car usage (Delmelle & Delmelle, 2012). Unlike staff, students' car commuting is sensitive to commuting distance and to the built environment of the home and campus.…”

Section: Statistical Analysis Of the Influence Of Campus Location On mentioning

confidence: 99%

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Different destination, different commuting pattern? Analyzing the influence of the campus location on commuting

Vale

Pereira

Viana

2018

JTLU

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Abstract:There is a vast literature on the relationship between built environment and travel, emphasizing the importance of built environment as a determinant of travel. However, the majority of studies focuses on the characteristics of origins and neglects the influence that the destination might have on travel, despite the already demonstrated importance of destinations to explain travel. In this paper, we test the relationship between residential and workplace built environment and the commuting pattern of staff and students of the University of Lisbon, a multi-campus university. Data was obtained through a dedicated travel survey, containing 1474 georeferenced individuals. Chi-square analyses were developed to analyze differences between staff and students and between different campuses. A logistic regression model was developed to explain car commuting, controlling for socio-demographic data. Two different models were developed for students and staff.Our results show the built environment and associated multimodal accessibility of the campuses are important explanatory variables of commuting. Free parking at the campus is crucial for car commuting, especially for students. These results emphasize the importance of measuring destinations as explanatory variables and promoting good urban integration of the campus in the city, increasing its multimodal accessibility.

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Section: Different Destination Different Commuting Pattern? Analyzinmentioning

confidence: 99%

Section: Statistical Analysis Of the Influence Of Campus Location On mentioning

confidence: 99%

Different destination, different commuting pattern? Analyzing the influence of the campus location on commuting

Vale

Pereira

Viana

2018

JTLU

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“…Walking for AT was far more common than cycling and Cyclists were more likely to be male-both trends that are not unique to this study. 29,30,38 However, these findings do suggest that greater support (eg, infrastructural improvements) is needed to increase the overall rates of cycling for AT in Kingston, and that any interventions should be particularly mindful about how to increase cycling rates among women. Research has shown that high rates of female bicycle ridership are good indicators of a bicycle-friendly community.…”

Section: Implications For Active Transportation Interventionsmentioning

confidence: 94%

Active Transportation in Kingston, Ontario: An Analysis of Mode, Destination, Duration, and Season among Walkers and Cyclists

Collins¹,

Mayer²

2015

Journal of Physical Activity and Health

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Background: Individuals that engage in active transportation (AT) have healthier weights and fitness levels. Most AT research has focused on work-or school-based destinations. Meanwhile, little is known about the differences between individuals that engage in the most common forms of AT-walking and cycling-and how these AT patterns vary by destination, duration, and season. Methods: We recruited 1400 randomly sampled adults (350 per season) in Kingston, Ontario, Canada to complete a cross-sectional telephone survey. The survey captured the prevalence, destinations, and duration of AT, and we examined the observed differences by mode. Results: The majority (72%) of respondents were AT-users; walking constituted 93% of overall mode share. Cyclists were more likely to be male, younger, and employed than walkers. Walkers tended to access neighborhoodbased destinations, while cyclists were more likely to use AT to get to work. AT duration was comparable by mode, ranging from approximately 8 to 20 minutes. Overall rates of AT were lowest in the winter, but walking rates were reasonably high year-round. Conclusions: Beyond commuting to work and school, policy-makers and planners should consider the breadth of destinations accessed by different modes when aiming to increase physical activity through AT in their communities.

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“…Previous studies (e.g., Balsas, 2003;Shannon et al, 2006;Delmelle and Delmelle, 2012) suggest parking permit possession is a critical factor for university students' travel-mode choice decisions. Hence, parking space reduction intervention strategy seems to be the most effective to reduce car use as it is the case in Europe, yet there has been limited implementation of this strategy in the U.S. From a transportation-equity perspective, reducing parking space capacity is an ineffective strategy, unless adequate alternatives are provided.…”

Section: Introductionmentioning

confidence: 99%

Factors associated with students' parking-pass purchase decisions: Evidence from an American University

Sultana

2015

Transport Policy

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Exploring spatio-temporal commuting patterns in a university environment

Cited by 140 publications

References 14 publications

Different destination, different commuting pattern? Analyzing the influence of the campus location on commuting

Different destination, different commuting pattern? Analyzing the influence of the campus location on commuting

Active Transportation in Kingston, Ontario: An Analysis of Mode, Destination, Duration, and Season among Walkers and Cyclists

Factors associated with students' parking-pass purchase decisions: Evidence from an American University

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