Effects of Station-Area Built Environment on Metro Ridership: The Role of Spatial Synergy

Abstract

Evaluating transit-oriented development (TOD) efficiency in metro station areas remains challenging, as the traditional “Node–Place” model gives limited consideration to guiding factors and struggles to account for inter-regional flows under spatial heterogeneity. To address these limitations, this study develops an enhanced “Node–Place–Accessibility” model by introducing an accessibility dimension to better capture station-level connectivity and walkability. DepthmapX and a convex space approach were applied to quantify station-area accessibility, reflecting passengers’ perceived spatial distance during transfers. The model establishes a TOD measurement framework based on spatial coupling and functional connectivity, enabling the identification of factors influencing metro ridership across different spatial scales. Moran’s I was employed to describe spatial agglomeration and a local spatial clustering method integrating both passenger flow and built-environment (BE) characteristics was constructed to reveal differentiated spatial patterns. The Multiscale Geographically Weighted Regression (MGWR) model was further employed to quantify the spatially varying impacts of BE factors on ridership. Results indicate that the improved model provides stronger discriminative power in identifying “balanced stations,” and that BE conditions exert significant impact on metro ridership, particularly in areas with strong coordination among TOD components. Among the BE dimensions, design granularity exerts a more substantial impact on ridership than connectivity, density, and accessibility. This methodology provides large cities with a reliable tool for formulating targeted strategies that promote positive interactions between transportation and land use, thereby supporting sustainable urban development.