Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach

Xinyu Cao, Patricia L. Mokhtarian, Susan L. Handy, 2007, in Transportation

doi:10.1007/s11116-007-9132-x
Location Northern California
Population Other (specify)
Sample size 547
Factor analysis type exploratory factor analysis, Oblique rotation
Stepwise regression no
Removal of insignificant variables yes
Reviewed by SH

Abstract

Suburban sprawl has been widely criticized for its contribution to auto dependence. Numerous studies have found that residents in suburban neighborhoods drive more and walk less than their counterparts in traditional environments. However, most studies confirm only an association between the built environment and travel behavior, and have yet to establish the predominant underlying causal link: whether neighborhood design independently influences travel behavior or whether preferences for travel options affect residential choice. That is, residential self-selection may be at work. A few studies have recently addressed the influence of self-selection. However, our understanding of the causality issue is still immature. To address this issue, this study took into account individuals’ self-selection by employing a quasi-longitudinal design and by controlling for residential preferences and travel attitudes. In particular, using data collected from 547 movers currently living in four traditional neighborhoods and four suburban neighborhoods in Northern California, we developed a structural equations model to investigate the relationships among changes in the built environment, changes in auto ownership, and changes in travel behavior. The results provide some encouragement that land-use policies designed to put residents closer to destinations and provide them with alternative transportation options will actually lead to less driving and more walking.

Factors

Models

Source variable Target variable Effect p-value Effect type
Changes in # of driving-age member Changes in outdoor spaciousness 0.112 <0.05 direct_effect
Current age Changes in outdoor spaciousness -0.128 <0.05 direct_effect
Accessibility Changes in outdoor spaciousness -0.14 <0.05 direct_effect
Outdoor spaciousness Changes in outdoor spaciousness 0.221 <0.05 direct_effect
Travel minimizing Changes in accessibility 0.138 <0.05 direct_effect
Safety of car Changes in accessibility -0.103 <0.05 direct_effect
Accessibility Changes in accessibility 0.13 <0.05 direct_effect
Changes in outdoor spaciousness Changes in automobiles 0.158 <0.05 direct_effect
Changes in income Changes in automobiles 0.13 <0.05 direct_effect
Changes in # of driving-age member Changes in automobiles 0.294 <0.05 direct_effect
Current age Changes in automobiles -0.123 <0.05 direct_effect
Current dist. to nearest fast food (km) Changes in automobiles 0.076 <0.1 direct_effect
Outdoor spaciousness Changes in automobiles -0.099 <0.05 direct_effect
Changes in accessibility Changes in driving -0.206 <0.05 direct_effect
Changes in automobiles Changes in driving 0.099 <0.05 direct_effect
Changes in income Changes in driving 0.087 <0.05 direct_effect
Current education Changes in driving -0.079 <0.1 direct_effect
Ln (1 + current # of kids < 18) Changes in driving 0.096 <0.05 direct_effect
Current age Changes in driving -0.104 <0.05 direct_effect
Socializing Changes in driving -0.087 <0.05 direct_effect
Current # of leisure businesses w/in 1600 m Changes in driving -0.08 <0.1 direct_effect
Car dependent Changes in driving 0.108 <0.05 direct_effect
Source variable Target variable Effect p-value Effect type
Changes in # of kids (<=5) Changes in attractiveness -0.086 <0.05 direct_effect
Current age Changes in attractiveness -0.125 <0.05 direct_effect
Attractiveness Changes in attractiveness 0.21 <0.05 direct_effect
Changes in # of driving-age members Changes in outdoor spaciousness 0.118 <0.05 direct_effect
Current age Changes in outdoor spaciousness -0.129 <0.05 direct_effect
Accessibility Changes in outdoor spaciousness -0.118 <0.05 direct_effect
Outdoor spaciousness Changes in outdoor spaciousness 0.212 <0.05 direct_effect
Accessibility Changes in accessibility 0.143 <0.05 direct_effect
Safety of car Changes in accessibility -0.098 <0.05 direct_effect
Travel minimizing Changes in accessibility 0.127 <0.05 direct_effect
Changes in outdoor spaciousness Changes in automobiles 0.157 <0.05 direct_effect
Changes in # of driving-age members Changes in automobiles 0.294 <0.05 direct_effect
Changes in income Changes in automobiles 0.13 <0.05 direct_effect
Current age Changes in automobiles -0.123 <0.05 direct_effect
Current dist. to nearest fast food Changes in automobiles 0.076 <0.05 direct_effect
Outdoor spaciousness Changes in automobiles -0.099 <0.05 direct_effect
Changes in accessibility Changes in driving -0.123 <0.05 direct_effect
Changes in automobiles Changes in driving 0.099 <0.05 direct_effect
Changes in income Changes in driving 0.008 <0.1 direct_effect
Ln (1 + current # of kids < 18) Changes in driving 0.114 <0.05 direct_effect
Current age Changes in driving -0.101 <0.05 direct_effect
Current education Changes in driving -0.081 <0.05 direct_effect
Socializing Changes in driving -0.094 <0.05 direct_effect
Car dependent Changes in driving 0.113 <0.05 direct_effect
Changes in attractiveness Changes in walking 0.213 <0.05 direct_effect
Changes in # of driving-age members Changes in walking 0.092 <0.05 direct_effect
Currently working Changes in walking -0.075 <0.05 direct_effect
Physical activity options Changes in walking 0.137 <0.05 direct_effect
Safety Changes in walking 0.128 <0.05 direct_effect
Socializing Changes in walking 0.164 <0.05 direct_effect
Current # of business types w/in 400 m Changes in walking 0.096 <0.05 direct_effect
Safety of car Changes in walking -0.127 <0.05 direct_effect
Pro-bike/walk Changes in walking 0.103 <0.05 direct_effect

The Attitudes and Travel Database is produced with support from the Center for Teaching Old Models New Tricks at Arizona State University, a University Transportation Center sponsored by the US Department of Transportation through Grant No. 69A3551747116.

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