Spatially Varying Effect Mechanism of Intermodal Connection on Metro Ridership: Evidence from a Polycentric Megacity with Multilevel Ring Roads

Abstract

Understanding the spatially varying effect mechanism of intermodal connection on metro ridership helps policymakers develop differentiated interventions to promote metro usage, especially for megacities with multiple city sub-centers and ring roads. Using multiple datasets in Shanghai, this study combines Light Gradient Boosting Machine (LightGBM) with Shapley additive explanations (SHAP) to explore these effects with the consideration of the built environment and metro network topology. Results show that the collective impacts of intermodal connection are positive, not only within the main city but also alongside the main commuting corridors, while negative effects occur in the peripheral area. Specifically, bike sharing trips increase metro ridership within the inner ring of the city, while bus services lower metro usage at stations alongside the elevated ring roads. Parking facilities enable metro usage at city sub-centers, and the small pedestrian catchment area increases metro riders alongside the main commuting corridors. Empirical findings help policymakers understand the effect mechanism of intermodal connection for stations in different regions and prioritize customized planning strategies.

Keywords

• metro ridership
• spatial heterogeneity
• effect mechanism
• intermodal connection
• network topology
• machine learning