Temporal dynamics of public transportation ridership in Seoul before, during, and after COVID-19 from urban resilience perspective

Abstract

Abstract We delve into the temporal dynamics of public transportation (PT) ridership in Seoul, South Korea, navigating the periods before, during, and after the COVID-19 pandemic through a spatial difference-in-difference model (SDID). Rooted in urban resilience theory, the study employs micro-level public transportation card data spanning January 2019 to December 2023. Major findings indicate a substantial ridership decline during the severe COVID impact phase, followed by a period in the stable and post-COVID phases. Specifically, compared to the pre-COVID phase, PT ridership experienced a 32.1% decrease in Severe, followed by a reduced magnitude of 21.8% in Stable and 13.5% in post-COVID phase. Interestingly, the observed decrease implies a certain level of adaptability, preventing a complete collapse. Also, contrasting with findings in previous literature, our study reveals a less severe impact, with reductions ranging from 27.0 to 34.9%. Moreover, while the ridership in the post-COVID phase exhibits recovery, the ratio (Post/Pre) staying below 1.0 suggests that the system has not fully returned to its pre-pandemic state. This study contributes to the urban resilience discourse, illustrating how PT system adjusts to COVID, offering insights for transportation planning.

Keywords

• Public transportation
• Transportation planning
• COVID impact
• Spatial difference-in-difference
• Human mobility data