Abstract
Maritime transport accounts for over 80% of the world trade volume and is the backbone of the global economy. Global supply chains create a complex network of trade flows. The structure of this network impacts not only the socioeconomic development of the concerned regions but also their ecosystems. The movements of ships are a considerable source of CO2emissions and contribute to climate change. In the wake of the announced development of Arctic shipping, the need to understand the behavior of the maritime trade network and to predict future trade flows becomes pressing. We use a unique database of daily movements of the world fleet over the period 1977–2008 and apply machine learning techniques on network data to develop models for predicting the opening of new shipping lines and for forecasting trade volume on links. We find that the evolution of this system is governed by a simple rule from network science, relying on the number of common neighbors between pairs of ports. This finding is consistent over all three decades of temporal data. We further confirm it with a natural experiment, involving traffic redirection from the port of Kobe after the 1995 earthquake. Our forecasting method enables researchers and industry to easily model effects of potential future scenarios at the level of ports, regions, and the world. Our results also indicate that maritime trade flows follow a form of random walk on the underlying network structure of sea connections, highlighting its pivotal role in the development of maritime trade.
Funder
EC | FP7 | FP7 Ideas: European Research Council
Publisher
Proceedings of the National Academy of Sciences
Reference55 articles.
1. J. Hoffman , S. Sirimanne , Eds., Executive Summary (United Nations Conference on Trade and Development, 2017).
2. J. P. Rodrigue , C. Comtois , B. Slack , The Geography of Transport Systems (Routledge, 2016).
3. B. Ki-Moon , Maritime transport is ‘backbone of global trade and the global economy’, says Secretary-General in message for International Day. https://www.un.org/press/en/2016/sgsm18129.doc.htm. Accessed 1 March 2019.
4. The complex network of global cargo ship movements
5. Resolving natural ranges and marine invasions in a globally distributed octocoral (genus Carijoa)
Cited by
34 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献