地理学报 ›› 2011, Vol. 66 ›› Issue (2): 167-177.doi: 10.11821/xb201102003

• 城市研究 • 上一篇    下一篇

基于结构方程模型的广州城市社区居民出行行为

曹小曙1, 林强2   

  1. 1. 中山大学地理科学与规划学院,广州510275;
    2. 深圳市城市规划发展研究中心,深圳518040
  • 收稿日期:2010-01-13 修回日期:2010-06-20 出版日期:2011-02-20 发布日期:2011-03-31
  • 作者简介:曹小曙(1970-), 男, 甘肃人, 博士, 博导, 教授, 中国地理学会会员(S110005157M), 主要从事交通地理与土地 利用研究。E-mail: caoxsh@mail.sysu.edu.cn
  • 基金资助:

    国家自然科学基金项目(40571052)

A SEM-based Study on Urban Community Resident's Travel Behavior in Guangzhou

CAO Xiaoshu1, LIN Qiang2   

  1. 1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;
    2. Shenzhen Urban Planning and Research Center, Shenzhen 518040, Guangdong, China
  • Received:2010-01-13 Revised:2010-06-20 Online:2011-02-20 Published:2011-03-31
  • Supported by:

    National Natural Science Foundation of China, No.40571052

摘要: 基于行为主义的视角,从微观的社区层面研究城市居民的出行行为。选取广州市的3 个城 市社区作为案例,以218 个样本数据库为基础,根据研究的侧重点不同分别建立两个结构方程模 型,拟合各变量之间的路径关系。其中居民出行选择的结构方程模型重点分析居民属性、居住 区位与居民出行目的、出行时间、出行方式等出行偏好之间的关系。居民出行决策的结构方程 模型则模拟居民的出行决策过程。结果显示:居民之间由于自身属性不同在出行选择和出行偏 好上存在差异,居民出行行为中居民属性和居住区位是根本,出行目的是关键,居民出行行为可 以概括为“属性决定目的,目的影响行动”。此外,居民的出行行为有其复杂的作用机制和决策 路径,居民的出行决策过程可以解读为性别决策子系统、年龄决策子系统、收入决策子系统和居 住区位决策子系统等4 个决策子系统,各子系统中路径作用的不同使居民属性和居住区位对居 民出行决策产生多重多向的效应,在复合系统的影响下城市社区居民表现出差异化的出行 行为。

关键词: 城市社区, 出行行为, 结构方程模型, 广州市

Abstract: From the perspective of behaviorism, the travel behavior of the urban resident is explored at the community scale. An example of Guangzhou is discussed and 218 samples from three communities are provided. Two Structural Equation Models (SEM) are developed respectively to explore the path relationships between various variables. Moreover, the mechanism of interaction between attributes and travel behaviors of residents are presented. The results indicate the distinctions between different urban residents’travel behaviors which result from various residents' attributes and community locations. Generally speaking, the travel pattern, travel timetable and travel frequency are influenced by travel motivation, which is determined by the residents' attributes and community location. Among all of the variables, residents’attributes and community location are the fundamental variables, while the former is the key variable. What's more, residents’attributes and community location have a significant impact on travel decision-making of the residents through four sub-path systems. The Gender Sub-path presents that females conduct more non-work trips which raise travel frequency. The Age Sub-path suggests that the older residents prefer a low-cost travel mode with more non-work travel intentions, thus their travel frequency is increased. The Income Sub-path indicates that the work trip plays a significant role in daily travel of high-income residents who prefer the high-cost travel mode, and as a result, their travel frequency is decreased. The Community Location Sub-path indicates that the residents in suburban communities care more about travel expenses than the residents in the city center; hence, the reduction of non-work trips will decrease their travel frequency.

Key words: urban community, travel behavior, SEM (structural equation model), Guangzhou