Abstract: The study examines U.S. port disruptions under tropical cyclones (TCs) by assessing key factors associated with port operational impact, recovery duration, and freight network-level impact, where generalizable empirical insights across TCs remain limited. We construct the CyPort dataset to capture these impacts for 145 U.S. principal ports across 90 tropical cyclones (2015–2023), integrating TC exposure, port characteristics, and freight network centrality. We employ the Random Parameter Negative Binomial-Lindley model to obtain more reliable resilience insights, accounting for data imbalance and unobserved heterogeneity across port–TC interactions. Results show that port-level and freight network-level impacts are governed by distinct drivers. Factors associated with reduced disruption are identified, including hinterland characteristics at the port level (e.g., railway connection and workforce factors) and betweenness centrality at the network level. Heterogeneous effects show wind, surge, rainfall, and railway connection affect ports differently, highlighting context-dependent resilience. Our insights support port preparedness, coordination, and long-term infrastructure investment.

Dr. Zihao “Scott” Li is a Postdoctoral Researcher at Texas A&M University. He received his Ph.D. in Transportation Engineering from Texas A&M University in 2024 and his M.S. in Engineering Physics from Tsinghua University, China, in 2020. His research focuses on transportation resilience, AI in transportation, mixed traffic modeling and control, and active traffic safety analysis. His work has been published or is forthcoming in leading venues, including Transportation Research Part B, C, and D, IEEE Transactions on Intelligent Transportation Systems, and the AAAI Conference on Artificial Intelligence. He has also received multiple fellowships, including the ITS Texas Scholarship and the Texas A&M University Dissertation Fellowship.