Recurrence in the evolution of air transport networks
Abstract Changes in air transport networks over time may be induced by competition among carriers, changes in regulations on airline industry, and socioeconomic events such as terrorist attacks and epidemic outbreaks. Such network changes may reflect corporate strategies of each carrier. In the pres...
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2021-03-01
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Online Access: | https://doi.org/10.1038/s41598-021-84337-z |
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doaj-a3d7a1a688f449c2a50eba23ce34b95a2021-03-11T12:22:35ZengNature Publishing GroupScientific Reports2045-23222021-03-0111111510.1038/s41598-021-84337-zRecurrence in the evolution of air transport networksKashin Sugishita0Naoki Masuda1Department of Mathematics, State University of New York at BuffaloDepartment of Mathematics, State University of New York at BuffaloAbstract Changes in air transport networks over time may be induced by competition among carriers, changes in regulations on airline industry, and socioeconomic events such as terrorist attacks and epidemic outbreaks. Such network changes may reflect corporate strategies of each carrier. In the present study, we propose a framework for analyzing evolution patterns in temporal networks in discrete time from the viewpoint of recurrence. Recurrence implies that the network structure returns to one relatively close to that in the past. We applied the proposed methods to four major carriers in the US from 1987 to 2019. We found that the carriers were different in terms of the autocorrelation, strength of periodicity, and changes in these quantities across decades. We also found that the network structure of the individual carriers abruptly changes from time to time. Such a network change reflects changes in their operation at their hub airports rather than famous socioeconomic events that look closely related to airline industry. The proposed methods are expected to be useful for revealing, for example, evolution of airline alliances and responses to natural disasters or infectious diseases, as well as characterizing evolution of social, biological, and other networks over time.https://doi.org/10.1038/s41598-021-84337-z |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kashin Sugishita Naoki Masuda |
spellingShingle |
Kashin Sugishita Naoki Masuda Recurrence in the evolution of air transport networks Scientific Reports |
author_facet |
Kashin Sugishita Naoki Masuda |
author_sort |
Kashin Sugishita |
title |
Recurrence in the evolution of air transport networks |
title_short |
Recurrence in the evolution of air transport networks |
title_full |
Recurrence in the evolution of air transport networks |
title_fullStr |
Recurrence in the evolution of air transport networks |
title_full_unstemmed |
Recurrence in the evolution of air transport networks |
title_sort |
recurrence in the evolution of air transport networks |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2021-03-01 |
description |
Abstract Changes in air transport networks over time may be induced by competition among carriers, changes in regulations on airline industry, and socioeconomic events such as terrorist attacks and epidemic outbreaks. Such network changes may reflect corporate strategies of each carrier. In the present study, we propose a framework for analyzing evolution patterns in temporal networks in discrete time from the viewpoint of recurrence. Recurrence implies that the network structure returns to one relatively close to that in the past. We applied the proposed methods to four major carriers in the US from 1987 to 2019. We found that the carriers were different in terms of the autocorrelation, strength of periodicity, and changes in these quantities across decades. We also found that the network structure of the individual carriers abruptly changes from time to time. Such a network change reflects changes in their operation at their hub airports rather than famous socioeconomic events that look closely related to airline industry. The proposed methods are expected to be useful for revealing, for example, evolution of airline alliances and responses to natural disasters or infectious diseases, as well as characterizing evolution of social, biological, and other networks over time. |
url |
https://doi.org/10.1038/s41598-021-84337-z |
work_keys_str_mv |
AT kashinsugishita recurrenceintheevolutionofairtransportnetworks AT naokimasuda recurrenceintheevolutionofairtransportnetworks |
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