Progress and Prospects of Urban Job-Housing Separation under the Context of Migration Transformation in China

In the context of China's urbanization and migration transformation, the phenomenon and trends of job-housing separation have shown new dynamics, necessitating a systematic review of research on this topic in Chinese cities. This study uses CiteSpace to conduct a quantitative analysis of literature on job-housing separation in China from 2000 to 2022. The review is structured according to stages of urban development, with a focus on summarizing and evaluating current research hotspots, themes, and methodologies. The findings indicate that the job-residence separation at different stages of population mobility has different characteristics. Firstly, the research area of job-housing separation has expanded from first-tier cities to second- and third-tier cities, reflecting the new phenomenon of population flow and transition in China's urbanization process. Second, the research perspective has gradually shifted from the macro level to the micro level, paying more attention to the job-housing separation. At the same time, the study actively adopts advanced technologies such as machine learning to process large-scale migration data, and combines multidisciplinary theories such as geography, urbanism, and transportation to conduct in-depth analyses.. Based on this comprehensive review, several key points are identified: (1) In the context of migration transformation, research needs to focus more on the new characteristics of job-housing separation and its spatial correlations from a lifecycle perspective. This involves investigating the social foundations of job-housing separation across multiple scales, including the urban-rural divide, intercity dynamics, and intracity variations. (2) Current research has not adequately explored the evolution of job-housing separation. It is necessary to incorporate life cycle theory to unify each stage of job-housing separation into a dynamic research framework. (3) The use of machine learning techniques should be encouraged to process large-scale migration data. Interdisciplinary approaches, combining geography, urban studies, and transportation, are essential to explore the mechanisms of job-housing separation more comprehensively. This will enable better analysis and prediction of trends, supporting urban planning and the optimization of transportation infrastructure. (4) Integrating migration theories with lifecycle theory can further illuminate the interrelationships between job-housing separation and migration behavior. Research should focus on the impacts of migration on job-housing separation and explore how to address these issues in the context of migration, providing better planning recommendations for urban development. In conclusion, multidimensional and interdisciplinary research is essential to fully understand the dynamics of job-housing separation within the broader context of China's urbanization and migration transformation. By incorporating theories and methodologies from various disciplines, a deeper understanding of the mechanisms and influencing factors can lead to more effective policymaking and sustainable urban development.