2017
DOI: 10.1007/s11116-017-9760-8
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Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

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Cited by 82 publications
(28 citation statements)
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“…Thus, this paper involves this group of variables in the analyses. Land use and residential self-selections are also a large group of variables the correlations of which with urban travel behaviour and decision-making have been investigated, and in many contexts evidence of correlations have been found (Van Wee, Holwerda & van Baren 2002;Zhang 2004;Pinjari et al 2007;Frank et al 2008;Aziz et al 2017;Ding et al 2017). Moreover, people's attitudes, perceptions, behavioural norms, and beliefs have recently gained the attention of some of the scholars of the region.…”
Section: Mena Regionmentioning
confidence: 99%
“…Thus, this paper involves this group of variables in the analyses. Land use and residential self-selections are also a large group of variables the correlations of which with urban travel behaviour and decision-making have been investigated, and in many contexts evidence of correlations have been found (Van Wee, Holwerda & van Baren 2002;Zhang 2004;Pinjari et al 2007;Frank et al 2008;Aziz et al 2017;Ding et al 2017). Moreover, people's attitudes, perceptions, behavioural norms, and beliefs have recently gained the attention of some of the scholars of the region.…”
Section: Mena Regionmentioning
confidence: 99%
“…Many researchers have put efforts into establishing methods to explicitly address bicycle safety by reflecting urban conditions, and have found that many factors influence safety, including the traffic volume, lane width, population density, highway classification, presence of vertical grades, one-way streets, and truck routes [21]. These urban conditions were taken into account to predict the severity of an injury that would result from a motor vehicle crash that can occur at a specific location [46][47][48][49]. The same methods and findings can be applicable to e-PMV safety.…”
Section: Pmvs and Road Safetymentioning
confidence: 99%
“…Based on consumer choice theory, travelers are assumed to rationally choose a transport mode to travel from their origins to their destinations by evaluating the characteristics of various available competing alternatives, and weighing their options in an attempt to maximize personal utility [4,37,38]. Individuals' transport mode choices and travel behaviors are affected by a complex set of factors, such as availability, travel costs, personal attitudes, personal demographics, habits, perceptions of safety and convenience, cultures, and built environments [39][40][41][42][43][44]. Ridesharing provides a more flexible, more convenient, and often faster option than public transit [14], and a lower cost than private cars (ridesharing riders could share some costs with drivers, and riders do not need to pay for ownership) [3].…”
Section: Literature Reviewmentioning
confidence: 99%