Geography and social networks in transportation mode choice

Pike, Susan; Lubell, Mark

doi:10.1016/j.jtrangeo.2016.10.009

Cited by 29 publications

(15 citation statements)

References 33 publications

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“…Based on an ego-centric approach, we can collect alters' behaviours by asking egos to report it (e.g. Pike, 2014;Pike & Lubell, 2016). However, it may cause measurement errors due to memory bias or lack of enough knowledge.…”

Section: Discussion and Research Directionsmentioning

confidence: 99%

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Social networks, social influence and activity-travel behaviour: a review of models and empirical evidence

2017

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The study of social networks in activity-travel research has recently gained momentum because social activities and social influence were relatively poorly explained in activity-based models of travel demand. Over the last decade, many scholars have shown interest in identifying personal social networks that constitute an important source of explanation of activity-travel behaviour. This paper seeks to review two research streams: social networks and activity-travel behaviour, and social influence and travel decisions. We classify models, summarise empirical findings and discuss important issues that require further research. ARTICLE HISTORY

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Section: Discussion and Research Directionsmentioning

confidence: 99%

“…Pike (2014Pike ( , 2015 found that university students who have relatively many social contacts who bike tend to be more likely to use bicycle for commuting. Pike and Lubell (2016) found that this positive social influence tends to decrease by increasing commute distance.…”

Section: Travel Mode Choicementioning

confidence: 95%

Social networks, social influence and activity-travel behaviour: a review of models and empirical evidence

2017

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“…• Model 2: we veri#ied the hypotheses "social in#luence on the travel mode choice is not dependent on the social in#luence within the ego's home". We created a travel mode choice model for egos-alters from different households, which only considered the social contacts that do not live in the same household as the respondent's (Pike and Lubell, 2016). "Excluding household members minimizes the overlap of and similarities in the choice environments of each ego and their social contact" (Pike and Lubell, 2016).…”

Section: Model and Hypothesesmentioning

confidence: 99%

“…The third perspective allows the study of the transportation mode choice or other related travel choices, as, for example, choosing the place of residence (Li, 2018), departure time (Xiao and Lo, 2016), and shopping location (Han et al, 2011). We use the social in#luence perspective in this study, which was mainly based on the research carried out by Susan Pike (Pike, 2014;Pike, 2015;Pike and Lubell, 2016;Pike and Lubell, 2018) and Maness et al (2015). Pike (2015) extensively studied social in#luence on transportation mode choices for university trips in Davis (USA).…”

Section: Introductionmentioning

confidence: 99%

Modeling travel mode choice under social influence for the brazilian context

2020

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Busca-se neste trabalho a definição de um modelo comportamental para verificar a existência da influência social na escolha do modo de viagem no contexto brasileiro. Para isso, realizou-se uma pesquisa no campus Darcy Ribeiro da Universidade de Brasília (UnB) com coleta e modelagem logit multinomial de dados sociais e de viagem. Verificou-se, como resultado, a existência da influência social por conformidade na escolha do modo de viagem para a universidade quando se consideram os modos sustentáveis (bicicleta e caminhada) e a carona: a probabilidade de um indivíduo utilizar modos sustentáveis em detrimento do automóvel é 76% maior quando a quantidade de contatos sociais usuários destes modos aumenta em 10%. Para a carona este aumento é de 27%. A consideração da influência social permite a percepção mais abrangente dos fatores relevantes no processo decisório individual, sendo referência para a formulação de políticas públicas de mobilidade, com destaque para aquelas que buscam promover alternativas sustentáveis e compartilhadas.

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“…Perceptions are difficult to quantify accurately, but there is a direct connection between how an area is perceived and residents' willingness to engage in walking and bicycling [12,38]. Individuals are more likely to perceive the area as bikeable if there are high numbers of cycle commuters in an area [17,46].…”

Section: Introductionmentioning

confidence: 99%

Geographical Assessment of Low-Carbon Transportation Modes: A Case Study from a Commuter University

et al. 2018

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This case study examines the geographic variation in students' low-carbon transportation (LCT) modes to a commuter university campus. Three major goals are accomplished from this research: (1) identifying commuting zones for the bicycling, walking, and transit mode choice for UNCG students; (2) understanding whether the real vs. perception of space can be predictive to mode choice; and (3) understanding the relative importance of demographic, psychological, and logistic factors on students' mode choice, using a suite of variables developed in multiple fields. Our analyses support the assertion that various physical, demographic, and psychological dimensions influence LCT mode choice. While the presence of sidewalks is conducive to walking, the distance, either perceived or actual, within 1.61 km from UNCG is the most important factor for walking mode share. The bicycling commute is not associated with either the distance or presence of bicycle lanes, while transit ridership most likely increases if students live >8 km from the UNCG campus with the nearest bus stop within 1 km from home. Given the limited bicycle lanes in Greensboro, students who commute to campus by bicycle are resilient to unfavorable bicycle conditions by sharing the road with cars and adjusting their travel routes. Our findings also concur with previous studies showing that bicycle commuters are disproportionately represented by self-identified whites while bus riders are disproportionately comprised of self-identified non-whites. Our analyses support Greensboro's current planning and policy emphasis on low-carbon travel behaviors via equitable and safe transit-oriented multi-modal infrastructures, and suggest that UNCG should utilize its influence to advocate and further facilitate these ongoing efforts.

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Geography and social networks in transportation mode choice

Cited by 29 publications

References 33 publications

Social networks, social influence and activity-travel behaviour: a review of models and empirical evidence

Social networks, social influence and activity-travel behaviour: a review of models and empirical evidence

Modeling travel mode choice under social influence for the brazilian context

Geographical Assessment of Low-Carbon Transportation Modes: A Case Study from a Commuter University

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