2022
DOI: 10.1016/j.ajsl.2022.08.002
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Structural changes in the cruise network by ship size in Northeast Asia

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Cited by 8 publications
(6 citation statements)
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References 19 publications
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“…Network diameter refers to the maximum value of the shortest path between any two ports in the cruise shipping network. The larger the network diameter is, the more ports the itinerary has (Ito, Hanaoka, & Sugishita, 2022). The calculation formula is: …”
Section: Methodsmentioning
confidence: 99%
“…Network diameter refers to the maximum value of the shortest path between any two ports in the cruise shipping network. The larger the network diameter is, the more ports the itinerary has (Ito, Hanaoka, & Sugishita, 2022). The calculation formula is: …”
Section: Methodsmentioning
confidence: 99%
“…A maritime transport network can be described by tracking the activity of ships since they navigate between ports. The network explains the location and quantity of nodes (ports) that form the network and their edges or links (shipping routes) because of ship activities [32]. An investigation of network connectivity addresses associations amid nodes in a network that are connected by links between them.…”
Section: Studies On Cruise Shipping Networkmentioning
confidence: 99%
“…Kanrak et al [35] further analysed the change in the cruise shipping network by comparing the networks before and after the pandemic. Ito et al [32] investigated the structural changes in the cruise shipping network via ship size in Northeast Asia adopting network science approaches along with AIS data. Rodriguez et al [36] adopted 2018 itineraries covering 902 ports to understand structural changes in Northern Europe and the Caribbean cruise networks.…”
Section: Studies On Cruise Shipping Networkmentioning
confidence: 99%
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“…Research on the structural characteristics of innovation networks mainly focuses on the overall characteristics of the network, network positions, and network relationships. In the research on the overall characteristics of innovation networks, indicators such as network density, average clustering coefficient, network centralization, and modularity have been used in studies [14]. In research on the position of innovation networks, most scholars have used indicators such as closeness centrality, betweenness centrality, and constraint to explore the position of nodes in innovation networks [15].…”
Section: Introductionmentioning
confidence: 99%