Resilience of regional container port network: based on projection correlation and dynamic spatial Markov Chain

Ports are interconnected by shipping routes within the global logistics network. Shocks and risks stemming from financial crises, epidemics, ecology, and so on have prompted shifts in cross-border labor division towards regional cooperation, reflecting an ‘anti-globalization’ trend. Despite these dynamics, few studies have analyzed the spatial structure and dynamic evolution of resilience within regional container port network. Addressing this gap, this study considers spatial and dynamic attributes to identify influential factors of resilience and introduces the concept of spatial lag-multidimensional resistance (SL-MR) to strengthen the understanding and cognition of regional container port network resilience (RCPNR). By ports in Tianjin and Hebei, China, it constructs a dynamic spatial Markov chain (DSMC) based on the projection correlation (PC index) to dissect transition trajectories amid financial crises and other conflicts. The findings indicate: (1) The regional container port network often experiences a low-level path dependence like ‘poverty trap.’ (2) Hierarchical spatial lags significantly influence the transition probability of container port network resilience degradation, with regional port relationships being unidirectional rather than cooperative. (3) The impact of the 2008 financial crisis and the COVID-19 pandemic on regional port resilience varies, serving as key determinants in shaping diverse resilience types.