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Mode Choice, the Built Environment, and Consumer Behavior: Insights from Davis, CA.

机译:模式选择,构建环境和消费者行为:来自加利福尼亚州戴维斯的见解。

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摘要

Growing concerns about climate change and traffic congestion are motivating policymakers to find ways to encourage sustainable travel options. In the U.S., where 88% 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 thesis examines the relationship between the built environment, retail shopping mode choice, and consumer behavior. The objective of this study is twofold. First, to examine which factors influence mode choice to three different shopping destination types -- downtown, strip center, and big box - in Davis, CA. Second, to examine how shopping behavior in downtown Davis varies between bicyclists and motorists -- two groups that are in perpetual competition for parking spaces and other infrastructure accommodations. I use data from two cross-sectional online surveys conducted in 2009 and 2010 with a total of 2,043 respondents that asked questions about recent shopping trips. To address the first question, I estimate binary logit models for choosing to use an active travel mode to each of the three destination types. I find that distance to shopping destination and bicycling enjoyment are the primary determinants of choosing active travel modes, while socio-demographic characteristics play a smaller role. Perceptions of the convenience of using different modes to shop vary significantly across destination types and correspond to observed mode shares. However, the 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. To address the second question, I first compare shopping trip frequency and spending of shoppers who bicycled downtown to those who used a car to test for significant differences and then estimate binary logit models for bicycling downtown or not to identify factors significant in choosing to bicycle to shop. I find that customers who biked on their most recent trip downtown spent slightly higher amounts on average on their purchases each trip than their auto-driving counterparts, and that they made more frequent shopping trips, thus contributing larger amounts of money to downtown establishments than customers travelling by car. These findings help support the case for converting some auto infrastructure to bicycling infrastructure.
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%的购物旅行都是由汽车出行的,因此研究确定了影响购物方式选择的因素,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。本文研究了构建环境,零售购物模式选择和消费者行为之间的关系。这项研究的目的是双重的。首先,要检查哪些因素会影响加利福尼亚州戴维斯市三种不同购物目的地类型的选择-市区,购物中心和大型购物中心。其次,研究骑自行车的人和驾车者之间在戴维斯市区的购物行为是如何变化的。这两个群体一直在争夺停车位和其他基础设施住宿。我使用了2009年和2010年进行的两次横断面在线调查的数据,共有2,043名受访者对最近的购物旅行提出了疑问。为了解决第一个问题,我估计了用于选择对三种目的地类型中的每一种使用主动出行方式的二进制logit模型。我发现到购物目的地的距离和骑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。对于不同的目的地类型,使用不同模式购物的便利性的看法差异很大,并且与观察到的模式份额相对应。但是,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,但对目的地进行简单的基础架构更改不足以鼓励模式转换。为了解决第二个问题,我首先将购物之旅的频率和骑自行车到市中心的购物者与那些使用汽车来测试显着性差异的购物者的花费进行比较,然后估算二元logit模型用于骑自行车到市中心,或者不找出在选择骑自行车到城市的重要因素。店。我发现,最近一次骑车到市区的顾客每次购物的平均消费额要比自动驾驶车高出很多,而且他们购物的频率也更高,因此比顾客花更多的钱在市区乘汽车旅行。这些发现有助于支持将某些汽车基础设施转换为自行车基础设施的案例。

著录项

  • 作者

    Popovich, Natalie.;

  • 作者单位

    University of California, Davis.;

  • 授予单位 University of California, Davis.;
  • 学科 Transportation.;Demography.;Urban planning.;Climate change.
  • 学位 M.S.
  • 年度 2014
  • 页码 51 p.
  • 总页数 51
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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