Network Structure Analysis of a Sub-Hub-Oriented Port

Song, Shi Cheng; Park, Sung hoon; Yeo, Gi Tae

doi:10.1016/j.ajsl.2019.06.004

Cited by 11 publications

(5 citation statements)

References 48 publications

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“…For example, major cities or industrial centers may have high authority centrality in a transportation network due to the high volume of goods and passengers that originate or terminate in these locations. The application of this measure in transportation networks is deemed worthy of further investigation in light of climate-related events and disasters, regardless of the applications in the literature, indicatively on spatially analyzing bus networks [72]; the international air transportation network at the country-level [73]; and port networks [74]. However, because the definition of the constants α and β in a transportation network for each node would be a particularly complex process, and as the main field of application of this algorithm is the Internet (to decide the importance of a web page based on the structure of connections), both hub centrality and authority centrality can be individually calculated with measures mentioned above, namely, those of degree and eigenvector centrality.…”

Section: Hub and Authority (Kleinberg) Centralitymentioning

confidence: 99%

Transportation Networks in the Face of Climate Change Adaptation: A Review of Centrality Measures

Stamos

2023

Future Transportation

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This paper presents a comprehensive review of centrality measures and their usefulness in transportation networks in the face of climate change adaptation. The focus is on understanding the importance of transportation nodes in the event of extreme weather events and climate-related disasters that may render them inoperable. The paper argues that if critical nodes can be identified, they can be better protected, while resources can be allocated to ensure their functioning in the event of such events. The paper assesses 17 centrality measures, including degree, closeness, betweenness, eigenvector, and Katz, and evaluates their usefulness and usability in transportation networks. The review highlights the need to reformulate these measures to take into account traffic- and transport-related parameters and variables. Without this reformulation, centrality measures only reveal node importance in a topological or structural way and fail to capture the true significance of the nodes in a transportation network. The reformulation enables the centrality measures to be properly applied in a transportation network and to expose the significance of their elements. This work has important implications for transportation planners and policy-makers in ensuring the resilience of critical transportation infrastructure in the face of climate-related disasters.

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Section: Hub and Authority (Kleinberg) Centralitymentioning

confidence: 99%

Transportation Networks in the Face of Climate Change Adaptation: A Review of Centrality Measures

Stamos

2023

Future Transportation

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“…The studies of maritime network centrality can also be classified into two types: Unweighted shipping network. Earlier, due to the limitation of data sources, most of the studies have taken the shipping network as a binary case to study its topological structure such as the small world and scale-free nature of the network ( Ducruet et al., 2010 ; Laxe et al., 2012 ; Kang and Woo, 2017 ; Song et al., 2019 ; Wu et al., 2019 ; Wan et al., 2021 ). Weighted shipping network.…”

Section: Literature Reviewmentioning

confidence: 99%

An effective distance-based centrality approach for exploring the centrality of maritime shipping network

Zeng-jie¹,

Liu²,

Wu³

et al. 2022

Heliyon

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“…In fact, many scholars have adopted social network analysis to study the status of nodes in a network. For example, Song et al [46] used a social network analysis to study the structure of a linear transportation network centered on a sub-hub port of Gwangyang in South Korea and found that Busan is the most important port in the transport network in terms of the number of connections. However, when considering the hub centrality, the influence of the Shanghai and Hong Kong ports is more significant.…”

Section: Traffic Relations and Statusmentioning

confidence: 99%

Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis

Mou

Ren

Zheng

et al. 2021

IJGI

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Maritime traffic can reflect the diverse and complex relations between countries and regions, such as economic trade and geopolitics. Based on the AIS (Automatic Identification System) trajectory data of ships, this study constructs the Maritime Silk Road traffic network. In this study, we used a complex network theory along with social network analysis and network flow analysis to analyze the spatial distribution characteristics of maritime traffic flow of the Maritime Silk Road; further, we empirically demonstrate the traffic inequality in the route. On this basis, we explore the role of the country in the maritime traffic system and the resulting traffic relations. There are three main results of this study. (1) The inequality in the maritime traffic of the Maritime Silk Road has led to obvious regional differences. Europe, west Asia, northeast Asia, and southeast Asia are the dominant regions of the Maritime Silk Road. (2) Different countries play different maritime traffic roles. Italy, Singapore, and China are the core countries in the maritime traffic network of the Maritime Silk Road; Greece, Turkey, Cyprus, Lebanon, and Israel have built a structure of maritime traffic flow in the eastern Mediterranean Sea, and Saudi Arabia serves as a bridge for maritime trade between Asia and Europe. (3) The maritime traffic relations show the characteristics of regionalization; countries in west Asia and the European Mediterranean region are clearly polarized, and competition–synergy relations have become the main form of maritime traffic relations among the countries in the dominant regions. Our results can provide a scientific reference for the coordinated development of regional shipping, improvement of maritime competition, cooperation strategies for countries, and adjustments in the organizational structure of ports along the Maritime Silk Road.

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Network Structure Analysis of a Sub-Hub-Oriented Port

Cited by 11 publications

References 48 publications

Transportation Networks in the Face of Climate Change Adaptation: A Review of Centrality Measures

Transportation Networks in the Face of Climate Change Adaptation: A Review of Centrality Measures

An effective distance-based centrality approach for exploring the centrality of maritime shipping network

Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis

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