Modular gateway-ness connectivity and structural core organization in maritime network science

Mengqiao Xu,Haoxiang Xia,Qian Pan,Carlo Vittorio Cannistraci,Alessandro Muscoloni

doi:10.1038/s41467-020-16619-5

Abstract

Around 80% of global trade by volume is transported by sea, and thus the maritime transportation system is fundamental to the world economy. To better exploit new international shipping routes, we need to understand the current ones and their complex systems association with international trade. We investigate the structure of the global liner shipping network (GLSN), finding it is an economic small-world network with a trade-off between high transportation efficiency and low wiring cost. To enhance understanding of this trade-off, we examine the modular segregation of the GLSN; we study provincial-, connector-hub ports and propose the definition of gateway-hub ports, using three respective structural measures. The gateway-hub structural-core organization seems a salient property of the GLSN, which proves importantly associated to network integration and function in realizing the cargo transportation of international trade. This finding offers new insights into the GLSN’s structural organization complexity and its relevance to international trade.

Highlights

Around 80% of global trade by volume is transported by sea, and the maritime transportation system is fundamental to the world economy
Scientific advancements in these directions could provide novel methodological approaches for quantifying the structural dynamics of the global liner shipping network (GLSN) and their relevance to international trade. These facts motivate us to address a central research question of the present study: what specific topological properties and organization principles characterize the GLSN structure, and how are they associated with the GLSN’s functional outcomes? Among topological properties, the structural-core organization is crucial, as it refers to the emergence of certain hub ports that play an important role in the structural integration of the entire network. This corresponds to a specific question in liner shipping industry: which ports are the most important hubs in the GLSN structure, in the sense that they form a core that facilitates the efficiency of cargo transportation in the network? Such question is practically relevant because one of the most important issues in liner shipping service network design is to strategically pre-choose hub ports[16,17,18]
We explore the association between a new network structural measure and the GLSN’s two functional outcomes of practical importance: individual ports’ economic performance, which is at the node level; countries’ international trade statuses (i.e., the international trade value (ITV) of countries and the bilateral trade value (BTV) between countries), which is at the system level

Summary

Introduction

Around 80% of global trade by volume is transported by sea, and the maritime transportation system is fundamental to the world economy. Scientific advancements in these directions could provide novel methodological approaches for quantifying the structural dynamics (the connectivity changes that occur along time due to modifications in liner shipping service routes) of the GLSN and their relevance to international trade These facts motivate us to address a central research question of the present study: what specific topological properties and organization principles characterize the GLSN structure, and how are they associated with the GLSN’s functional outcomes? Such question is practically relevant because one of the most important issues in liner shipping service network design is to strategically pre-choose hub ports[16,17,18] We pursue this particular research interest through investigating the modular community structure of the GLSN, since modular community structure is one of the most prominent properties of complex networks[19] and can influence their function and structural core organization. The gateway-ness adds a valuable new tool in complex modular network analysis

Methods

Results

Conclusion