Identify social and job disparities in the relationship between job-housing balance and urban commuting using Baidu trajectory big data

The job-housing relationship is a well-documented topic in urban and economic geography literature, but the disparities in job-housing relationships across workers' sociodemographic statuses have yet to be fully explored. This study utilizes a Baidu trajectory dataset and spatial analysis tools to examine job-housing relationships in Zhuhai, China, taking into account disparities in workers' socioeconomic status and job types. Origin–destination analysis indicates that job-housing relationships for commercial and public service sectors are balanced in the urban core, whereas, for the secondary sector, the relationship is more balanced in the suburban area compared to the central urban area. Network analysis further reveals the presence of self-contained communities for the secondary sector in peripheral areas. We find that high-income workers in the secondary sector experience longer commuting distances, in contrast to their counterparts in the commercial and public service sectors. These insights underscore the significance of considering workers' skills in urban and economic planning.