The global container-shipping network’s survivability evolution based on big data statistics: A computational approach and its empirical evidence

Abstract

Abstract How to precisely estimate the survivability of the container maritime system is a crucial but unsolved problem. In this paper, we propose an improved container liner network model based on data from global container liner routes and ports of call for several years. Afterward, we applied kernel principal component analysis to reconstruct commonly-used network metrics. As a measure of survivability, we took the critical points of their variance during errors and attacks. We further analysed the evolution of container-shipping network survivability in recent years. Our research revealed that as the ports and density of routes increased over the past few years, the node strength distribution of the container-shipping network became more and more heterogeneous. The robustness increased while the vulnerability aggravated, and both indicators are slowing down. The paper examines how the container-shipping network has evolved in recent years using a model more consistent with container transportation scenarios. By analysing the characteristics and evolutionary trend of the container-shipping network, this paper provides insight into how to take advantage of the changing situation.