Robustness of airline alliance route networks
•Robustness of the route network of three airline alliances is analyzed.•Robustness is assessed through giant component size vs number of isolated airports.•A new inverted adaptive strategy (IAS) has been introduced.•Robustness is also assessed through a normalized multi-scale vulnerability measure....
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Veröffentlicht in: | Communications in nonlinear science & numerical simulation 2015-05, Vol.22 (1-3), p.587-595 |
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Sprache: | eng |
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Zusammenfassung: | •Robustness of the route network of three airline alliances is analyzed.•Robustness is assessed through giant component size vs number of isolated airports.•A new inverted adaptive strategy (IAS) has been introduced.•Robustness is also assessed through a normalized multi-scale vulnerability measure.•Star Alliance has the most resilient network.
The aim of this study is to analyze the robustness of the three major airline alliances’ (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure – the inverted adaptive strategy – is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion – inverted efficiency – shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results. |
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ISSN: | 1007-5704 1878-7274 |
DOI: | 10.1016/j.cnsns.2014.07.019 |