DAILY FLOWS, URBAN POLYCENTRICITY, AND TRANSIT COMMUTING PATTERNS: A STUDY OF SHANGHAI, CHINA

ABSTRACT

Employment center locations, the jobs-housing relationship, and commuting patterns are inextricably connected in a megacity that heavily relies on the urban transit system to shuttle commuters. Using a transit smartcard dataset, a machine learning method is employed as a preliminary filter to sift through commuter flows and isolate key data, then kernel density and topological analysis methods are implemented to delve into the primary research questions, providing a detailed look at how these patterns unfold. The results show that transit commuting behavior in Shanghai is a dispersal activity based on multi-level employment centers characterized as hierarchical, boundary-clear, and functionally oriented. Further analysis illustrates that the intensity of commuting linkages correlates with the employment center level, shaping a hybrid pattern that couples a core-periphery pattern with a spoke-hub pattern. The commuting network connections present corridor, neighborhood, capture, and replacement features, highlighting the importance of employment centers in shaping commuting patterns. From a daily flow perspective, these findings echo the central place theory and verify that the employment center distribution in Shanghai is also multi-layered and well-nested, forming the basis for commuting links. Policy implications are provided for polycentric megacities with progressively sophisticated urban transit systems.

Keywords::

• urban transit
• commuting pattern
• employment center
• polycentricity
• jobs-housing relationship

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.