Does commuting distance matter? Commuting tolerance and residential change

By William A. V. Clark, Youqin Huang, S. D. Withers. 2002

346 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Transportation

View Paper: https://www.semanticscholar.org/paper/66b3fda20dbcf212552514e1d82683a4a4488fbd

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In Sociology and Political Science

In Transportation

Citations in the corpus

Electrical Motor Drivelines in Commercial All-Electric Vehicles: A Review (2012, neutral): “The range is over-dimensioned with respect to the standard commuting distances for 95% of the journeys, both in Europe and in USA [77] - [79].”
When Transport Geography Meets Social Psychology: Toward a Conceptual Model of Travel Behaviour (2010, background): “A number of studies (e.g. Levinson, 1997; Clark et al., 2003; Scheiner, 2006) point out that mode use, travel distances and activity behaviour all change after a residential relocation.”
Which Came First, the Telecommuting or the Residential Relocation? An Empirical Analysis of Causality (2006, background): “, within the same quarter—are not considered in this analysis on the assumption—supported by Clark et al. (2003)—that such moves could differ importantly from residential-only moves, but without enough of them—only 2 of the 76 simultaneous moves were made by telecommuters—to analyze separately.”
The impact of metropolitan structure on commute behavior in the Netherlands: a multilevel approach (2004, neutral): “There may be several workers in a household (Clark, Huang, and Withers 2002; Giulano and Small 1993), or a lag in housing development near suburban employment concentrations (Cervero and Wu 1997), or zoning measures creating greenbelts around urban nodes Jun and Bae 2000).”
Volatility of car ownership, commutingmode and time in the UK (2007, methodology): “A recent study by Clark et al (2003) looks the at relationship between changes in residential and workplace location and commuting distance and travel time using data from the Puget Sound Transportation Panel over the years 1989 to 1997.”
A New Generalized Heterogeneous Data Model (GHDM) to Jointly Model Mixed Types of Dependent Variables (2015, background): “…been well established in the literature that commute distance is one of the most important determinants of residential location (see, for example, Clark et al., 2003, Rashidi et al., 2012).3 Auto ownership is a count outcome, while commute travel mode choice is represented as a second nominal…”