Long-term network structure evolution investigation for sustainability improvement: an empirical analysis on global top full-service carriers

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dc.contributor.authorYang, wendong
dc.contributor.authorJiang, Yun
dc.contributor.authorChi, Yulin
dc.contributor.authorXu, Zhengjia
dc.contributor.authorWei, Wenbin
dc.date.accessioned2024-03-15T15:26:11Z
dc.date.available2024-03-15T15:26:11Z
dc.date.issued2024-01-31
dc.description.abstractThe continuous and strategic planning of full-service carriers plays a prominent role in transferring and adapting them into resilient full-service carrier network structures. The exploration of full-service carrier network structures using the latest long-term empirical data facilitates enhancing cognitive capabilities in aspects of identifying network development tendencies, readjusting network structures, and supporting determinations of strategic business routes. Aiming at providing sustainable transport network solutions with historical long-term network structure analysis, this paper researches the global top 10 full-service carriers’ air transport networks from 2007 to 2022, applied using social network analysis (SNA). The static metrics from local to path-based perspectives are adopted to explore the global network evolution trend, along with competitiveness characteristics over critical airports. The cascading failure model is applied as a key indicator to analyze the dynamic robustness capability for the network. The similarity changing feature among the selected networks over the past years from 2007 to 2022 is measured using the autocorrelation function (ACF). The results indicate that, from 2011 to 2019, the majority of full-service carrier networks belong to the network types of closed, structural symmetry and two-way transitivity. The critical airports in North America present superiority in terms of network efficiency over those in Europe, Asia, and Oceania. The 10 full-service carriers’ air transport networks all show the trend of being more destruction-resistant. During the COVID-19 pandemic period, the merger with other airlines and the signing of a joint venture agreement led to higher temporal variability in the network structure.en_UK
dc.identifier.citationYang W, Jiang Y, Chi Y, et al., (2024) Long-term network structure evolution investigation for sustainability improvement: an empirical analysis on global top full-service carriers. Aerospace, Volume 11, Issue 2, January 2024, Article number 128en_UK
dc.identifier.issn2226-4310
dc.identifier.urihttps://doi.org/10.3390/aerospace11020128
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/21011
dc.language.isoen_UKen_UK
dc.publisherMDPIen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectair transportationen_UK
dc.subjectnetwork structureen_UK
dc.subjectSNA analysisen_UK
dc.subjectfull-service carriersen_UK
dc.titleLong-term network structure evolution investigation for sustainability improvement: an empirical analysis on global top full-service carriersen_UK
dc.typeArticleen_UK
dcterms.dateAccepted2024-01-29

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