Abstract
The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current research mainly focuses on the coarse-grained, holistic cargo ship transportation network while ignoring the structural diversity of different sub-networks. In this paper, we evaluate the robustness of the global cargo ship transportation network based on the most recent Automatic Identification System (AIS) data available. First, we subdivide three typical cargo ship transportation networks (i.e., oil tanker, container ship and bulk carrier) from the original cargo ship transportation network. Then, we design statistical indices based on complex network theory and employ four attack strategies, including random attack and three intentional attacks (i.e., degree-based attack, betweenness- based attack and flux-based attack) to evaluate the robustness of the three typical cargo ship transportation networks. Finally, we compare the integrity of the remaining ports of the network when a small proportion of ports lose their function. The results show that 1) compared with the holistic cargo ship transportation network, the fine-grain-based cargo ship transportation networks can fully reflect the pattern and process of global cargo transportation; 2) different cargo ship networks behave heterogeneously in terms of their robustness, with the container network being the weakest and the bulk carrier network being the strongest; and 3) small-scale intentional attacks may have significant influence on the integrity of the container network but a minor impact on the bulk carrier and oil tanker transportation networks. These conclusions can help improve the decision support capabilities in maritime transportation planning and emergency response and facilitate the establishment of a more reliable maritime transportation system.
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Foundation: Key Project of the Chinese Academy of Sciences, No.ZDRW-ZS-2016-6-3; National Natural Science Foundation of China, No.41501490
Author: Peng Peng (1989–), PhD Candidate, specialized in maritime transportation GIS, complex network analysis.
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Peng, P., Cheng, S., Chen, J. et al. A fine-grained perspective on the robustness of global cargo ship transportation networks. J. Geogr. Sci. 28, 881–889 (2018). https://doi.org/10.1007/s11442-018-1511-z
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DOI: https://doi.org/10.1007/s11442-018-1511-z