Abstract
We quantify the criticality of the world’s 1300 most important ports for global supply chains by predicting the allocation of trade flows on the global maritime transport network, which we link to a global supply-chain database to evaluate the importance of ports for the economy. We find that 50% of global trade in value terms is maritime, with low-income countries and small islands being 1.5 and 2.0 times more reliant on their ports compared to the global average. The five largest ports globally handle goods that embody >1.4% of global output, while 40 ports add >10% of domestic output of the economies they serve, predominantly small islands. We identify critical cross-border infrastructure dependencies for some landlocked and island countries that rely on specific ports outside their jurisdiction. Our results pave the way for developing new strategies to enhance the resilience and sustainability of port infrastructure and maritime trade.
| Original language | English |
|---|---|
| Article number | 4351 |
| Pages (from-to) | 1-13 |
| Number of pages | 13 |
| Journal | Nature Communications |
| Volume | 13 |
| DOIs | |
| Publication status | Published - 27 Jul 2022 |
Bibliographical note
Funding Information:The authors would like to thank the United Nations Statistical Division and the UN Global Working Group on Big Data for Official Statistics, in particular Markie Muryawan and Ronald Jansen, for providing the mode of transport data and the AIS data. Moreover, we like to thank Lóri Tavasszy and Luis Martinez for discussions and data provision that helped improve the methodology. J.V. acknowledges funding from the Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/R513295/1. E.E.K. was further supported by the Netherlands Organization for Scientific Research NWO (Grant No VI.Veni.194.033).
Funding Information:
The authors would like to thank the United Nations Statistical Division and the UN Global Working Group on Big Data for Official Statistics, in particular Markie Muryawan and Ronald Jansen, for providing the mode of transport data and the AIS data. Moreover, we like to thank Lóri Tavasszy and Luis Martinez for discussions and data provision that helped improve the methodology. J.V. acknowledges funding from the Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/R513295/1. E.E.K. was further supported by the Netherlands Organization for Scientific Research NWO (Grant No VI.Veni.194.033).
Publisher Copyright:
© 2022, The Author(s).
