居住自选择视角下城市建成环境对通勤模式选择的影响——以兰州市主城区为例
收稿日期: 2023-02-21
修回日期: 2023-04-24
网络出版日期: 2024-03-14
基金资助
国家自然科学基金项目(41961029)
Impact of urban built environment on commuting mode choices from the residential self-selection perspective
Received date: 2023-02-21
Revised date: 2023-04-24
Online published: 2024-03-14
交通方式选择研究对于城市高效、可持续和安全的交通规划至关重要。以兰州市主城区为例，基于分布式认知理论，采用调查问卷数据、路网数据、POI数据，通过结构方程模型探讨居住自选择效应影响下非随机异质性的建成环境对通勤模式选择的影响。结果表明：（1） 居民根据自身社会经济属性及态度偏好选择不同建成环境特征的住宅小区，继而形成特定的通勤模式，说明居住自选择存在偏好异质性，居住自选择效应存在。（2） 在规避居住自选择效应后，建成环境依然对通勤模式选择具有显著影响。具体来讲，人口密度、路网密度及停车位数量直接影响通勤模式选择，路网密度、公交站点可达性、地铁站点可达性及停车位数量通过中介变量通勤距离与小汽车拥有间接影响通勤模式选择。（3） 高人口密度、密路网与高可达性的建成环境通过提高道路网络的连通性、步行与公共交通的连接性进一步推动积极通勤模式与公共交通通勤模式选择，引导居民向积极通勤模式为主导的出行结构转变。
郭燕 , 张志斌 , 陈龙 , 马晓敏 , 赵学伟 . 居住自选择视角下城市建成环境对通勤模式选择的影响——以兰州市主城区为例[J]. 干旱区地理, 2024 , 47(2) : 307 -318 . DOI: 10.12118/j.issn.1000－6060.2023.074
Research on travel mode choice is essential for efficient, sustainable, and safe urban traffic planning. This study selected the main urban area of Lanzhou City, Gansu Province, China as the study area, and based on the distributed cognitive theory, questionnaire data, road network data, and Point of Interest (POI) data. The structural equation model was used to explore the impact of nonrandom heterogeneity of the built environment on selecting the commuting mode under the influence of the residential self-selection effect. The study found that: (1) Residents chose residential quarters with different built-environment characteristics according to their socioeconomic attributes and attitude preferences. Subsequently, they formed a specific commuting pattern, indicating preference heterogeneity in residential self-selection and the existence of the residential self-selection effect. (2) The built environment continued to have a considerable impact on the choice of commuting mode even after avoiding the self-selection effect of residence. Specifically, population density, road network density, and the number of parking spaces directly affected the choice of commuting mode. Road network density, bus station accessibility, subway station accessibility, and the number of parking spaces indirectly influenced the choice of commuting mode through mediating variables, such as commuting distance and car ownership. (3) High-population density, dense road network, and high-accessibility of the built environment increased the active and public transportation commuting modes. This was achieved by improving the connectivity of road networks, connection between walking and public transit, and pedestrian-friendly environment and by guiding residents to a shift in the travel structure, led by active commuting patterns.
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