Built environment correlates of walking for transportation: Differences between commuting and non-commuting trips

IF 1.6 4区 工程技术 Q4 TRANSPORTATION
Jixiang Liu, Jiangping Zhou, Longzhu Xiao
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引用次数: 9

Abstract

As a sustainable mode of travel, walking for transportation has multiple environmental, social, and health-related benefits. In existing studies, however, such walking has rarely been differentiated between commuting and non-commuting trips. Using multilevel zero-inflated negative binomial regression and multilevel Tobit regression models, this study empirically examines the frequency and duration of commuting and non-commuting walking and their correlates in Xiamen, China. It finds that (1) non-commuting walking, on average, has a higher frequency and longer duration than commuting walking; (2) most socio-demographic variables are significant predictors, and age, occupation, and family size have opposite-direction effects on commuting and non-commuting walking; and (3) different sets of built environment variables are correlated with commuting and non-commuting walking, and the built environment collectively influences the latter more significantly than the former. The findings provide useful references for customized interventions concerning promoting commuting and non-commuting walking.
建筑环境与步行交通的相关性:通勤和非通勤出行之间的差异
作为一种可持续的出行方式,步行交通具有多种环境、社会和健康益处。然而,在现有的研究中,这种步行很少区分通勤和非通勤旅行。本研究采用多水平零膨胀负二项回归和多水平托比特回归模型,实证检验了厦门市通勤和非通勤步行的频率和持续时间及其相关性。研究发现:(1)非通勤步行平均比通勤步行频率更高,持续时间更长;(2) 大多数社会人口学变量是显著的预测因素,年龄、职业和家庭规模对通勤和非通勤步行具有相反的方向影响;(3)不同的建筑环境变量集与通勤和非通勤步行相关,建筑环境对后者的总体影响大于前者。研究结果为促进通勤和非通勤步行的定制干预措施提供了有用的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.40
自引率
5.30%
发文量
34
审稿时长
30 weeks
期刊介绍: The Journal of Transport and Land Usepublishes original interdisciplinary papers on the interaction of transport and land use. Domains include: engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems. Papers reporting innovative methodologies, original data, and new empirical findings are especially encouraged.
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