Multiscale core-periphery structure in a global liner shipping network

Abstract

Maritime transport accounts for a majority of trades in volume, of which 70% in value is carried by container ships that transit regular routes on fixed schedules in the ocean. In the present paper, we analyse a data set of global liner shipping as a network of ports. In particular, we construct the network of the ports as the one-mode projection of a bipartite network composed of ports and ship routes. Like other transportation networks, global liner shipping networks may have core-periphery structure, where a core and a periphery are groups of densely and sparsely interconnected nodes, respectively. Core-periphery structure may have practical implications for understanding the robustness, efficiency and uneven development of international transportation systems. We develop an algorithm to detect core-periphery pairs in a network, which allows one to find core and peripheral nodes on different scales and uses a configuration model that accounts for the fact that the network is obtained by the one-mode projection of a bipartite network. We also found that most ports are core (as opposed to peripheral) ports and that ports in some countries in Europe, America and Asia belong to a global core-periphery pair across different scales, whereas ports in other countries do not.

Estimating international trade status of countries from global liner shipping networks

“…The dataset was provided by Alphaliner [ 33 ] at a given point of time (i.e. April 2015) and was also used in our previous work [ 17 , 34 ]. The Alphaliner database extensively covers the fleets of regular service routes worldwide, including all the service routes of the world's top 100 liner shipping companies in terms of liner shipping capacity (measured in Twenty-foot Equivalent Unit (TEU)).…”

“…Therefore, the normalization factor C /[ n ( n − 1)/2] implies that C is equally divided by all the possible n ( n − 1)/2 pairs of ports. In our previous work, we adopted C /( n − 1) as the edge weight to analyse a similarly constructed GLSN [ 17 ]. For each of the six edge-weighting schemes, we calculated the edge weight for a given pair of ports as the summation of the edge weight over all the service routes to which both ports belong.…”

“…The dataset was provided by Alphaliner [33] at a given point of time (i.e. April 2015) and was also used in our previous work [17,34]. The Alphaliner database extensively covers the fleets of regular service royalsocietypublishing.org/journal/rsos R. Soc.…”

Evaluation of Development Potential of Ports in the Yangtze River Delta Using FAHP-Entropy Model

“…According to the different modes of cargo transportation, the maritime network can be divided into container, bulk carrier, and tanker networks. The existing studies mainly focus on the spatial characteristics and evolution of the maritime container network, which mostly uses the shipping schedules provided by International, Barry Rogliano Salle (Alphaliner database), company's website, periodicals, and magazines [33,34]. The real-time data are difficult to obtain, so few people use the real-time positioning information of ships [35]-Lloyd's list, Lloyd's Register of Shipping, AIS data, etc.…”

An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)

“…Meanwhile, the nodes in a core are also reasonably well-connected to those in the periphery. The core-periphery structure may have practical implications for understanding the robustness, efficiency, and uneven development of the global natural resource trades [57].…”