Jobs-Housing Balance and Self-Containment Using Cellphone Big Data
Jobs-Housing Balance and Self-Containment Using Cellphone Big Data: Case Studies in Shenzhen and Shanghai
English | 2025 | ISBN: 9819781841 | 104 Pages | PDF (True) | 6 MB
English | 2025 | ISBN: 9819781841 | 104 Pages | PDF (True) | 6 MB
This book addresses the analysis of self-containment of employment (SCE), which measures journey-to-work trips among the percentage of workers who work locally. High SCE encourages the use of non-motorized transport and reduces transport-related energy consumption. In this book, mobile phone location data is employed to assess journey-to-work trips and explore spatial variations in SCE at multiple geographic scales. It finds that SCE is significantly higher in the suburbs than that in the central urban areas and tends to decrease as the spatial analysis unit shifts from the macro to the micro scale. The relationship between Jobs–housing balance is found to be more important in self-containment of employment for secondary-sector workers compared with that for tertiary-sector workers. Secondary-sector workers tend to reside near their workplaces because of relatively balanced jobs and housing, whereas tertiary-sector workers tend to reside farther away from their workplaces to save housing cost.