Baiying Sun, Zhengfeng Huang, Kehong Guan, Pengjun Zheng
This six-year longitudinal analysis highlights the dynamic vulnerability and adaptive capacity of urban mobility networks under prolonged public health emergencies. To build crisis-resilient cities, policymakers must implement data-driven, dynamic supply-demand regulatory mechanisms to prevent resource misallocation, safeguard the livelihoods of gig workers, and ensure equitable access to essential mobility services across all urban sectors.
INTRODUCTION: Shared urban mobility systems are critical infrastructure for ensuring essential travel and maintaining socioeconomic stability during public health crises. However, the long-term system resilience and spatial-temporal equity of these networks under severe macro-shocks (e.g., the COVID-19 pandemic) and subsequent recovery phases remain underexplored.
METHODS: Utilizing a comprehensive longitudinal dataset (2019-2024) from Ningbo, China, this study constructs a multi-dimensional evaluation framework encompassing market supply, operational performance, economic viability, and service equity. We applied a projection pursuit-weighted TOPSIS model to quantify the overall resilience trajectory. Furthermore, to uncover structural disparities in service access, tensor decomposition and the Theil index were employed to measure the spatial-temporal distribution of passenger waiting times.
RESULTS: The empirical findings reveal that the socio-ecological resilience of the ride-hailing system exhibited severe vulnerability during the initial COVID-19 outbreak (Q1 2020), with closeness values dropping to 0.290. While overall resilience peaked during the post-pandemic recovery (Q4 2023), the system experienced a structural "involution," characterized by continuous supply expansion that outpaced demand, leading to degraded per-vehicle operational efficiency. Moreover, the study identified significant spatial-temporal inequalities in mobility access during pandemic restrictions (2020-2021), which were progressively mitigated following strict regulatory interventions and market normalization.
CONCLUSION: This six-year longitudinal analysis highlights the dynamic vulnerability and adaptive capacity of urban mobility networks under prolonged public health emergencies. To build crisis-resilient cities, policymakers must implement data-driven, dynamic supply-demand regulatory mechanisms to prevent resource misallocation, safeguard the livelihoods of gig workers, and ensure equitable access to essential mobility services across all urban sectors.