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On Node Criticality in Air Transportation Networks

Xiaoqian Sun (), Sebastian Wandelt () and Xianbin Cao
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Xiaoqian Sun: Beihang University
Sebastian Wandelt: Beihang University
Xianbin Cao: Beihang University

Networks and Spatial Economics, 2017, vol. 17, issue 3, 737-761

Abstract: Abstract In this study, we analyze the criticality of nodes in air transportation using techniques from three different domains, and thus, three essentially different perspectives of criticality. First, we examine the unweighted structure of air transportation networks, using recent methods from control theory (maximum matching and minimum dominating set). Second, complex network metrics (betweenness and closeness) are used with passenger traffic as weights. Third, ticket data-level analysis (origin-destination betweenness and outbound traffic with transit threshold) is performed. Remarkably, all techniques identify a different set of critical nodes; while, in general, giving preference to the selection of high-degree nodes. Our evaluation on the international air transportation country network suggests that some countries, e.g., United States, France, and Germany, are critical from all three perspectives. Other countries, e.g., United Arab Emirates and Panama, have a very specific influence, by controlling the passenger traffic of their neighborhood countries. Furthermore, we assess the criticality of the country network using Multi-Criteria Decision Analysis (MCDA) techniques. United States, Great Britain, Germany, and United Arab Emirates are identified as non-dominated countries; Sensitivity analysis shows that United Arab Emirates is most sensitive to the preference information on the outbound traffic. Our work gears towards a better understanding of node criticality in air transportation networks. This study also stipulates future research possibilities on criticality in general transportation networks.

Keywords: Network criticality; Air transportation systems; Complex network (search for similar items in EconPapers)
Date: 2017
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