Role of the built environment on mode choice decisions: additional evidence on the impact of density

By Cynthia Chen, Hongmian Gong, R. Paaswell. 2008

369 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Transportation

View Paper: https://www.semanticscholar.org/paper/e7bedfb6f2c9e3ab6bfda8ca849e98a2e640ad42

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In Sociology and Political Science

In Transportation

Citations in the corpus

Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review (2014, background): “…USA Travel Survey BMOPT VO and VU p p – p p p – p Schimek (1996) USA Travel Survey Two-equation system simultaneous equation model VO and VU p p – p p p – p Chen, Gong, and Paaswell (2008) USA Travel Survey Two-equation system simultaneous equation model VO and VU p p – p p p p p Bhat and…”
Factors influencing modal split of commuting journeys in medium-size European cities (2013, methodology): “We report the links found by Kim and Ulfarsson (2008) and Sabir (2011) on Table 1.”
Residential self-selection and travel behaviour: What are the effects of attitudes, reasons for location choice and the built environment? (2017, neutral): “Over the past decades many studies have investigated how the built environment (BE) in ﬂ uences travel behaviour (e.g. Cervero, 2002; Chen et al., 2008).”
How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities (2012, background): “In addition to self-selection problems, other issues that can possibly confound the relationship between built environment and travel behavior include spatial auto-correlation, inter-trip dependency, and geographic scales (Krizek 2003b; Bottai et al. 2006; Chen et al. 2008; Frank et al, 2008).”
Satisfaction with the commute: The role of travel mode choice, built environment and attitudes (2017, background): “…streets, and high transit and job accessibility at both home (Cervero and Kockelman, 1997; Ewing and Cervero, 2010; Handy et al., 2005) and job locations (Chatman, 2003; Chen et al., 2008; Ding et al., 2014; Zhang, 2004), are associated with less car use and more active travel and transit use.”
When Transport Geography Meets Social Psychology: Toward a Conceptual Model of Travel Behaviour (2010, background): “Several recent studies (e.g. Schwanen and Mokhtarian, 2005a, 2005b; Bhat and Guo, 2007; Cao et al., 2007a, 2007b; Pinjari et al., 2007; Chen et al., 2008; Mokhtarian and Cao, 2008) argue that attitudes and preferences toward travel, activities and residential neighbourhoods are the true determinants”
Do satisfying walking and cycling trips result in more future trips with active travel modes? An exploratory study (2019, background): “…of owning a car is influenced by longer-term decisions such as the residential location choice, it can be expected that the built environment also affects travel behaviour indirectly, through car ownership (Chen et al., 2008; Eluru, Bhat, Pendyala, & Konduri, 2010; Van Acker and Witlox, 2010).”
The promises of big data and small data for travel behavior (aka human mobility) analysis (2016, background): “, residential location choices) and trip making behaviors (Chen et al., 2008).”
Travel mode choice and travel satisfaction: bridging the gap between decision utility and experienced utility (2016, background): “These studies state that people residing in urban neighborhoods travel less by car than people living in suburban neighborhoods, due to differences in density, diversity and design (Cervero 1996; Cervero and Kockelman 1997; Chen et al. 2008).”
Examining the Impacts of Residential Self‐Selection on Travel Behaviour: A Focus on Empirical Findings (2009, methodology): “6 Chen et al. (2008) constructed two simultaneous equations, in which car ownership level and the propensity to use a car influence each other. In this specification, car use for commute trips (a binary variable) is observed but the underlying propensity to use a car is unobserved. Thus, this latent”
What Affects Transit Ridership? A Dynamic Analysis involving Multiple Factors, Lags and Asymmetric Behaviour (2011, background): “Micro-level studies attempt to explain individuals’ transit use as a function of hypothesised variables such as family income and car ownership (for example, Kitamura, 1989; Chen and McKnight, 2007; Chen et al., 2008).”