TY - GEN
T1 - Examining the spatiotemporal changing pattern of freight maritime transport networks in Indonesia during COVID-19 outbreaks
AU - Destyanto, A.R.
AU - Huang, Yilin
AU - Verbraeck, A.
PY - 2022
Y1 - 2022
N2 - The COVID-19 pandemic in Indonesia has led to a significant change in human mobility. It is also considered the most serious threat to the inter-island trade network since the economic crisis in 1998. Leveraging two-year historical port call data (covering 6,000 records in total) of Indonesian domestic cargo vessels from the Automatic Identification System (AIS), this study examines the spatiotemporal changes of maritime freight transport network connectivity and cargo shipping capacity throughout the COVID-19 outbreaks period. We constructed two directed graphs, one in 2019 and another in the 2020 period, based on 1,283 Indonesian domestic cargo ship trajectories that connect 25 main Indonesian ports through 370 links. This study calculated and compared the four metrics of complex network analysis, including assortative coefficient, average degree, betweenness centrality, and clustering coefficient, to figure out the shipping network pattern changes. The result shows that the network connectivity and its shipping capacity changed in 2020, although the national port call trend is not significantly different from 2019. Based on our observation, we notice that the network is shifting from a "main hub-and-spoke connection," which dominantly involves western Indonesia hub-ports structure, towards a "multi hub-and-spoke connection," which increases the ports centrality position in eastern Indonesia. We also analyzed the change of cargo shipping capacity in each link to reflect how shipping liner companies respond to the pandemics. The insights generated in this study are hoping to contribute toward more rapid, effective, and comprehensive responses to this unprecedented disruption.
AB - The COVID-19 pandemic in Indonesia has led to a significant change in human mobility. It is also considered the most serious threat to the inter-island trade network since the economic crisis in 1998. Leveraging two-year historical port call data (covering 6,000 records in total) of Indonesian domestic cargo vessels from the Automatic Identification System (AIS), this study examines the spatiotemporal changes of maritime freight transport network connectivity and cargo shipping capacity throughout the COVID-19 outbreaks period. We constructed two directed graphs, one in 2019 and another in the 2020 period, based on 1,283 Indonesian domestic cargo ship trajectories that connect 25 main Indonesian ports through 370 links. This study calculated and compared the four metrics of complex network analysis, including assortative coefficient, average degree, betweenness centrality, and clustering coefficient, to figure out the shipping network pattern changes. The result shows that the network connectivity and its shipping capacity changed in 2020, although the national port call trend is not significantly different from 2019. Based on our observation, we notice that the network is shifting from a "main hub-and-spoke connection," which dominantly involves western Indonesia hub-ports structure, towards a "multi hub-and-spoke connection," which increases the ports centrality position in eastern Indonesia. We also analyzed the change of cargo shipping capacity in each link to reflect how shipping liner companies respond to the pandemics. The insights generated in this study are hoping to contribute toward more rapid, effective, and comprehensive responses to this unprecedented disruption.
KW - Network dynamics
KW - Network Performance Analysis
KW - Network performance
KW - Network properties
UR - http://www.scopus.com/inward/record.url?scp=85143897688&partnerID=8YFLogxK
U2 - 10.1145/3468013.3468662
DO - 10.1145/3468013.3468662
M3 - Conference contribution
T3 - ACM International Conference Proceeding Series
SP - 590
EP - 597
BT - Proceedings of the 4th Asia Pacific Conference on Research in Industrial and Systems Engineering
PB - Association for Computing Machinery (ACM)
ER -