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How does the built environment at residential and work locations affect car ownership? An application of cross-classified multilevel model

机译:住宅和工作地点的建筑环境如何影响汽车拥有量?交叉分类多层次模型的应用

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摘要

Although many studies investigate the connection between the residential built environment and car ownership, the literature offers limited evidence on the effect of work locations. Using data from the Washington metropolitan area, this study develops a cross-classified multilevel model to examine the influences of the built environment at both residential and workplace locations on car ownership, while controlling for spatial dependency arising from spatial aggregation. We found that built environment characteristics at work locations, particularly bus stop density and employment density, influence household car ownership. They explain one third of the total variation of car ownership across work locations. The residential environment appears to impose a stronger influence than the workplace environment. Density, diversity, design, transit access around residences and distance from home to the city center affect car ownership.
机译:尽管许多研究调查了住宅建筑环境与汽车拥有权之间的联系,但文献仅提供了有限的证据说明工作地点的影响。这项研究使用华盛顿都会区的数据,建立了一个交叉分类的多层次模型,以研究住宅和工作场所的建筑环境对汽车拥有量的影响,同时控制由空间聚集引起的空间依赖性。我们发现工作地点的建筑环境特征(尤其是公交车站的密度和就业密度)会影响家用车的拥有量。他们解释了不同工作地点的汽车拥有量总变化的三分之一。居住环境似乎比工作场所环境具有更强的影响力。密度,多样性,设计,住宅周围的交通通道以及从住宅到市中心的距离都会影响汽车的拥有量。

著录项

  • 来源
    《Journal of Transport Geography》 |2019年第2期|37-45|共9页
  • 作者

    Ding Chuan; Cao Xinyu;

  • 作者单位

    Beihang Univ, Sch Transportat Sci & Engn, Beijing Key Lab Cooperat Vehicle Infrastruct Syst, Beijing 100191, Peoples R China|Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Beijing 100191, Peoples R China;

    Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Beijing 100191, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Auto ownership; Land use; Travel behavior; Spatial dependency; Random effect model;

    机译:汽车所有权;土地使用;出行行为;空间依赖性;随机效应模型;
  • 入库时间 2022-08-18 04:17:23

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