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

Abstract

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.

A Study of Transport Behaviour of Academic Communities

“…Some of the studies use traffic counts, automatic counts or GPS-based applications [28]. Studies address entire communities [26,29], sometimes staff only, and mostly students who are the largest group within a university community [13]. In case of traffic counts, studies sporadically cover traffic as a whole with all modes included and are mostly confined to pedestrians and/or cyclists [13].…”

“…The results of the research known from the literature create a set of diverse transport behaviours displayed by different academic communities [29]. As well as having different transport patterns, universities also differ in terms of their communities [30].…”

“…The built environment of trip origin or destination, including pedestrian, cycling and public transport infrastructure, street networks and car parks [13,29,31,35], • A presence of Travel Demand Management (TDM) measures such as parking cost or restriction information campaigns against car usage and transit pass subsidy [15].…”

“…The literature includes studies on the academic communities of universities in the US [13,22,36], Canada [31], Europe [14,15,18,21,29,31,37,38] and Asia [12,39]. With different levels of socio-economic and spatial development and motorization, European, American, and Asian countries differ significantly, a feature that can be seen not only in the size of the university but also in the behaviour of the community [40].…”

Potencial de transferência de um índice de mobilidade sustentável para campus universitário

“…Campi universitários con iguram PGVs de caracterıśticas particulares e alta complexidade, motivo pelo qual devem ser tratados de forma diferenciada (Parra, 2006;Balsas, 2003;Meireles, 2014; Stein e Rodrigues da Silva, 2014 e 2017; Rodrigues et al, 2005;Chung et al, 2018). Por abrigarem instituições de ensino e, consequentemente, constituıŕem uma comunidade de futuros tomadores de decisão, espera-se que os campi exerçam o papel de laboratório de boas práticas em diversos aspectos, inclusive no que diz respeito à mobilidade sustentavel (Tolley, 1996;Meireles, 2014;Vale et al, 2018). Além disso, os campi, em geral, apresentam ambientes de uso misto do solo, multimodais e caminhaveis, sendo, portanto, locais propıćios para boas práticas de mobilidade (Cherry et al, 2018).…”