Examining factors that keep residents with high transit preference away from transit-rich zones and associated behavior outcomes

Wolday, Fitwi; Cao, Xinyu; Næss, Petter

doi:10.1016/j.jtrangeo.2017.12.009

Cited by 43 publications

(20 citation statements)

References 35 publications

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“…[42]. From previous studies we know that affluent persons may choose to live in areas with longer commutes, but other positive characteristics when commuting is seen as a second tier argument in their choice of residence [43]. The present study may also indicate that comfortable PT modes, such as train and high-speed craft, may contribute to reduce the importance of commuting relative to other factors in residential choice.…”

Section: Discussionmentioning

confidence: 49%

Subsidising urban and sub-urban transport – distributional impacts

Fearnley

Aarhaug

2019

Eur. Transp. Res. Rev.

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Background and methods: This paper studies distributional effects of public transport (PT) subsidies focusing on the Greater Oslo region. We identify how different PT markets enjoy different levels of subsidies. We describe how subsidies are distributed along PT modes and their respective patronage. This is done by document studies and travel surveys, supplemented by expert inquiries. Results: We find that high-income groups, served by regional trains and high-speed crafts, receive large per passenger and per passenger-kilometre subsidy, while lower-income areas, typically served by local and regional buses, metros and local trains, receive lower subsidies per passenger. Peak traffic receives higher subsidies than offpeak traffic. The overall distributional profile is, however, found to be moderately progressive, in particular because of the socioeconomic profile of the average PT passenger relative to the population as a whole.

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Section: Discussionmentioning

confidence: 49%

Subsidising urban and sub-urban transport – distributional impacts

Fearnley

Aarhaug

2019

Eur. Transp. Res. Rev.

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“…Ettema and Nieuwenhuis (2017), on their part, found RSS and built environment to be marginally confounding as strong travel preferences translate only weakly into residential selection. Also, studies that looked into the relative priority of various factors in residential loca-tion choice found travel preference to be second-tier as a selection criteria in residential location choice (Cao, 2008;Filion, Bunting, & Warriner, 1999;Wolday, Cao, & Naess, 2018).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Built environment and car driving distance in a small city context

Wolday

2018

JTLU

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This article focuses on the effect of built-environment factors on travel behavior in the context of small cities. Urban size and spatial context are central to travel behavior analysis because of the spatiotemporal nature of transportation. Different urban structural attributes exert travel behavioral influences at different spatial scales (local vs. regional) and urban sizes. Due to this inherent geographic dimension in travel studies, findings from larger urban areas may not be transferable to small cities. Despite this, however, small cities remain scantily represented in the literature. Using multivariate analysis on survey data from three small cities in Norway, this paper finds that the built-environment effects on travel behavior are highly influenced by regional characteristics and the city’s center structure (poly-centered vs. single centered). Residential proximity to the city center leads to reduced car driving distance through its distance-minimizing effect to concentrations of facilities for local travel. At the regional scale, proximity to the city center influences car driving distance via the higher likelihood among centrally located commuters of choosing transit as their commute mode.

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“…Stevens (2017a) identifies ten studies that attempt to control for the problem. However, the results from a number of studies (Cao, Mokhtarian, & Handy, 2009;Wolday, Cao, & Naess, 2018) suggest that not controlling for residential selection results in little bias if controls include a rich set of demographic and socioeconomic variables. 7 In addition to these national surveys, some studies rely upon surveys that have been done at the subnational level.…”

Section: Literature Reviewmentioning

confidence: 99%

Vehicle miles traveled and the built environment: New evidence from panel data

Ihlanfeldt

2020

JTLU

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There has been considerable interest in the impact that the built environment has on vehicle miles traveled (VMT). While this issue has been extensively researched, due to the heavy reliance on cross-sectional data, there remains uncertainty regarding how effective local land-use planning and regulation might be in reducing VMT. Based on a 13-year panel of Florida counties, models are estimated that relate VMT to new measures of the spatial distribution of alternative land uses within counties and county urban expansion. Identification of causal effects is established by including year and county fixed effects, along with an extensive set of control variables, and instrumenting those land uses that may be endogenous. Incremental annual changes in the spatial concentration of alternative land uses are found to affect VMT. The policy implication is that appropriate land-use policy can reduce VMT and should be considered part of the strategy for dealing with the problem of global warming.

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Examining factors that keep residents with high transit preference away from transit-rich zones and associated behavior outcomes

Cited by 43 publications

References 35 publications

Subsidising urban and sub-urban transport – distributional impacts

Subsidising urban and sub-urban transport – distributional impacts

Built environment and car driving distance in a small city context

Vehicle miles traveled and the built environment: New evidence from panel data

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