Spatial Variations of Commuting Behavior and Their Impact Factors in Shanghai Metropolitan Area
Author(s): |
Kaiming Li
Liying Yue Huizhi Geng Kaishun Li |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Frontiers in Built Environment, February 2022, v. 8 |
DOI: | 10.3389/fbuil.2022.789024 |
Abstract: |
Exploring the spatial variations and the impact of spatial and social factors on commuting behavior is vital to promote cities’ sustainable development and improve residents’ daily lives. Based on 2015 1% Population Sample Survey data in Shanghai, this study constructs an improved accessibility index to evaluate the jobs–housing spatial relationship and compares spatial variations and factors of commuting duration and commuting distance at the sub-district level by using spatial autocorrelation analysis, spatial lag model, and spatial error model. In terms of spatial variations, the median commuting distance and commuting duration are 6.32 km and 28.37 min, respectively. Both of them have significant spatial autocorrelation, and the latter is higher. The high–high agglomeration areas of commuting distance scatter between the outer ring road and the outer suburbs. The high–high agglomeration areas of commuting duration are mainly distributed between the middle and the outer ring roads. In terms of affecting factors, the impacts of social factors on the commuting level are more significant than spatial factors. Ignoring the former will overestimate the effects of the latter. Commuting distance is more significantly correlated with spatial factors, and job accessibility is the most critical factor, while commuting duration is more significantly associated with social factors, and education level is the essential factor. There is significant intra-urban heterogeneity and spatial autocorrelation of commuting distance and duration in the metropolis. Social factors are more influential than spatial factors on commuting behavior. |
Copyright: | © Kaiming Li, Liying Yue, Huizhi Geng, Kaishun Li |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
Geographic Locations
1.84 MB
- About this
data sheet - Reference-ID
10665585 - Published on:
09/05/2022 - Last updated on:
01/06/2022