2022
DOI: 10.1016/j.ocecoaman.2022.106295
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Impact of local port disruption on global container trade: An example of stressing testing Chinese ports using a D-vine copula-based quantile regression

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Cited by 10 publications
(4 citation statements)
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“…To the best of the authors knowledge, this finding has not been reported in existing literature on maritime network vulnerability analysis. The damage of disruptions of those identified critical ports and countries to different countries is found to be highly heterogeneous (Figures 7 and 11). This finding confirms prior research that highlighted the regional differences in the vulnerability to disruptive events of critical components in global maritime transportation networks (Rousset & Ducruet, 2020; Wu, Wang, et al., 2019; Xiao & Bai, 2022), by providing two new insights into the vulnerability of GLSN at individual country level. First, the disruption of critical ports of Singapore, Shanghai and Busan can exert a global impact in that most other countries in the world will suffer a non‐negligible efficiency decrease, whereas the impact of other critical ports like Jebel Ali, Valencia, Rotterdam and New York–New Jersey is relatively localized in that their disruptions mainly affect countries geographically adjacent to them.…”
Section: Discussionsupporting
confidence: 89%
“…To the best of the authors knowledge, this finding has not been reported in existing literature on maritime network vulnerability analysis. The damage of disruptions of those identified critical ports and countries to different countries is found to be highly heterogeneous (Figures 7 and 11). This finding confirms prior research that highlighted the regional differences in the vulnerability to disruptive events of critical components in global maritime transportation networks (Rousset & Ducruet, 2020; Wu, Wang, et al., 2019; Xiao & Bai, 2022), by providing two new insights into the vulnerability of GLSN at individual country level. First, the disruption of critical ports of Singapore, Shanghai and Busan can exert a global impact in that most other countries in the world will suffer a non‐negligible efficiency decrease, whereas the impact of other critical ports like Jebel Ali, Valencia, Rotterdam and New York–New Jersey is relatively localized in that their disruptions mainly affect countries geographically adjacent to them.…”
Section: Discussionsupporting
confidence: 89%
“…Intermediate centrality refers to the ratio of the shortest paths passing through a certain point in the network and connecting these two points to the total number of shortest paths between these two points, reflecting the communication efficiency between port nodes and other port nodes, i.e., the role of the "middleman". The formula for calculating the centrality of the intermediary is shown in Equation (3), where δ(s, t|i ) is the number of shortest paths of ports s and t through port i and δ(s, t) is the sum of the shortest paths of ports s and t.…”
Section: Intermediate Centrality Analysismentioning
confidence: 99%
“…According to the data of the China Marine Disaster Bulletin 2022, the direct economic losses caused by typhoons and storm surges along the coast of China in the past decade reached RMB 6.8 billion. In addition to the economic losses, China's containerised port throughput accounts for about 30% of the global port throughput [3] and plays a pivotal role in the global containerised trade system. Therefore, when a typhoon affects the ports, it could directly lead to port closure, affect port operations and cargo transportation efficiency, and ultimately deteriorate the supply chain in which the port is located, reducing the efficiency of international trade.…”
Section: Introductionmentioning
confidence: 99%
“…While theoretical developments are still being made, vine copulas on a different number of variables have found application in virtually all fields of science and engineering. Recent example applications can be found in finance, business and economics 4 – 10 , coastal management 11 , earth sciences 12 14 and engineering 15 – 23 , where the number of variables in their respective vine copula models ranges from 3 to 10 variables. In a recent study by the authors, vine copulas on 6 variables (23,040 models) are fit to two sets of variables including waves, currents and hydrodynamic forces acting on a submerged floating tunnel for its evaluation under different design configurations.…”
Section: Background and Summarymentioning
confidence: 99%