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Downtown, strip centers, and big-box stores: Mode choice by shopping destination type in Davis, California

机译:市中心,购物中心和大型商店:加利福尼亚州戴维斯市的购物目的地类型选择模式

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Growing concerns about climate change and traffic congestion are motivating policymakers to find ways to encourage sustainable travel options. In the United States, where 88 percent of shopping trips are made by car, research identifying the factors that influence shopping mode choice can provide insight into ways to divert some of these trips to more sustainable alternatives. This paper aims to better explain the relationship between the built environment and shopping mode choice by examining how mode choice differs for the same individual across three different types of shopping destinations—downtown, strip center, and big box—in Davis, California. We conducted two cross-sectional online surveys in 2009 and 2010 with a total of 2043 respondents that asked questions about recent shopping. To understand the factors influencing mode choice at these three shopping destination types, we estimate binary logit models for choosing to use an active travel mode (bike or walk) to shop. Our results suggest that while distinct factors influence mode choice at the different destination types, simple infrastructure changes to the destination are not enough to encourage mode shift. Distance to shopping destinations and enjoying bicycling are the primary determinants of choosing active travel modes, while socio-demographic characteristics play a smaller role.
机译:对气候变化和交通拥堵的日益关注促使决策者寻找鼓励可持续旅行选择的方法。在美国,有88%的购物旅行是汽车旅行,通过研究确定影响购物模式选择的因素,可以深入了解将这些旅行中的一些转移到更具可持续性的选择中的方法。本文旨在通过研究加利福尼亚州戴维斯市三种不同类型的购物目的地(市区,购物中心和大商店)中同一个人的模式选择有何不同,来更好地解释建筑环境与购物模式选择之间的关系。我们在2009年和2010年进行了两次横断面在线调查,共有2043名受访者对近期购物提出了疑问。为了了解在这三种购物目的地类型上影响模式选择的因素,我们估算了用于选择使用主动出行模式(自行车或步行)购物的二进制logit模型。我们的结果表明,虽然不同的因素会影响不同目的地类型下的模式选择,但是简单地对目的地进行基础结构更改不足以鼓励模式转换。距离购物胜地的距离和骑自行车的乐趣是选择主动出行方式的主要决定因素,而社会人口统计特征所起的作用较小。

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