Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoods
A now substantial body of literature finds that land use and urban form have a statistically significant, albeit relatively modest, effect on travel behavior. Some scholars have suggested that various built-environment characteristics influence travel more in concert than when considered in isolatio...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
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University of Minnesota
2016-08-01
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Series: | Journal of Transport and Land Use |
Subjects: | |
Online Access: | https://www.jtlu.org/index.php/jtlu/article/view/840 |
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author | Carole Turley Voulgaris Brian D. Taylor Evelyn Blumenberg Anne Brown Kelcie Ralph |
author_facet | Carole Turley Voulgaris Brian D. Taylor Evelyn Blumenberg Anne Brown Kelcie Ralph |
author_sort | Carole Turley Voulgaris |
collection | DOAJ |
description | A now substantial body of literature finds that land use and urban form have a statistically significant, albeit relatively modest, effect on travel behavior. Some scholars have suggested that various built-environment characteristics influence travel more in concert than when considered in isolation. Yet few previous studies have combined built-environment measures to create holistic descriptions of the overall character of neighborhoods, and fewer still have related these neighborhoods to residents’ travel decisions. To address this gap in the literature, we develop a typology of seven distinct neighborhood types by applying factor analysis and then cluster analysis to a set of 20 variables describing built-environment characteristics for most census tracts in the United States. We then include these neighborhood types in a set of multivariate regression models to estimate the effect of neighborhood type on the travel behavior of neighborhood residents, controlling for an array of personal and household characteristics. We find relatively little variation in the number of daily trips among neighborhood types, but there is substantial neighborhood variation in both person miles of travel and mode choice. Travel by residents of one particular neighborhood type is notably distinguished from all others by a very low number of miles traveled, little solo driving, and high transit use. However, this neighborhood type is found almost exclusively in just a few very large metropolitan areas, and its replicability is uncertain. |
first_indexed | 2024-12-17T19:07:38Z |
format | Article |
id | doaj.art-a7c642bd0d0a4edfa0829e83b1b56af7 |
institution | Directory Open Access Journal |
issn | 1938-7849 |
language | English |
last_indexed | 2024-12-17T19:07:38Z |
publishDate | 2016-08-01 |
publisher | University of Minnesota |
record_format | Article |
series | Journal of Transport and Land Use |
spelling | doaj.art-a7c642bd0d0a4edfa0829e83b1b56af72022-12-21T21:35:58ZengUniversity of MinnesotaJournal of Transport and Land Use1938-78492016-08-0110110.5198/jtlu.2016.840Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoodsCarole Turley Voulgaris0Brian D. Taylor1Evelyn Blumenberg2Anne Brown3Kelcie Ralph4University of California, Los AngelesUniversity of California, Los AngelesUniversity of California, Los AngelesUniversity of California, Los AngelesRutgers, The State University of New JerseyA now substantial body of literature finds that land use and urban form have a statistically significant, albeit relatively modest, effect on travel behavior. Some scholars have suggested that various built-environment characteristics influence travel more in concert than when considered in isolation. Yet few previous studies have combined built-environment measures to create holistic descriptions of the overall character of neighborhoods, and fewer still have related these neighborhoods to residents’ travel decisions. To address this gap in the literature, we develop a typology of seven distinct neighborhood types by applying factor analysis and then cluster analysis to a set of 20 variables describing built-environment characteristics for most census tracts in the United States. We then include these neighborhood types in a set of multivariate regression models to estimate the effect of neighborhood type on the travel behavior of neighborhood residents, controlling for an array of personal and household characteristics. We find relatively little variation in the number of daily trips among neighborhood types, but there is substantial neighborhood variation in both person miles of travel and mode choice. Travel by residents of one particular neighborhood type is notably distinguished from all others by a very low number of miles traveled, little solo driving, and high transit use. However, this neighborhood type is found almost exclusively in just a few very large metropolitan areas, and its replicability is uncertain.https://www.jtlu.org/index.php/jtlu/article/view/840Neighborhood classificationtravel behavior |
spellingShingle | Carole Turley Voulgaris Brian D. Taylor Evelyn Blumenberg Anne Brown Kelcie Ralph Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoods Journal of Transport and Land Use Neighborhood classification travel behavior |
title | Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoods |
title_full | Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoods |
title_fullStr | Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoods |
title_full_unstemmed | Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoods |
title_short | Synergistic neighborhood relationships with travel behavior: An analysis of travel in 30,000 US neighborhoods |
title_sort | synergistic neighborhood relationships with travel behavior an analysis of travel in 30 000 us neighborhoods |
topic | Neighborhood classification travel behavior |
url | https://www.jtlu.org/index.php/jtlu/article/view/840 |
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