the present work objective is the analysis of the united states air cargo transport during a decade, from the year 2004 to 2014. the network theory is used and indicators such as closeness and betweenness are calculated. the present work compares the networks and the respective metrics of the two main airlines of the industry and the other 18 biggest companies what enables the evaluation of the impact of economic recessions, such as the one from 2008, on these networks and the detection of assymetries between companies of different sizes. it is possible to note that, among other aspects, the air cargo transport graph is heavily influenced by the two main private companies of the sector, fedex and ups, what can be pointed out by, e.g., the number of nodes of 178 and 106 in 2014 respectively for these networks compared to 81 from the other 18 biggest companies.

the present work objective is the analysis of the united states air cargo transport during a decade, from the year 2004 to 2014. the network theory is used and indicators such as closeness and betweenness are calculated. the present work compares the networks and the respective metrics of the two main airlines of the industry and the other 18 biggest companies what enables the evaluation of the impact of economic recessions, such as the one from 2008, on these networks and the detection of assymetries between companies of different sizes. it is possible to note that, among other aspects, the air cargo transport graph is heavily influenced by the two main private companies of the sector, fedex and ups, what can be pointed out by, e.g., the number of nodes of 178 and 106 in 2014 respectively for these networks compared to 81 from the other 18 biggest companies.

;Joao Pedro Pinheiro Malere;Vladimir Minas;Giovanna Miceli Ronzani Borille
nature machine intelligence 2016 Vol. 24 pp. 1-9
191
malere2016transportesthe

Abstract

The present work objective is the analysis of the United States air cargo transport during a decade, from the year 2004 to 2014. The network theory is used and indicators such as closeness and betweenness are calculated. The present work compares the networks and the respective metrics of the two main airlines of the industry and the other 18 biggest companies what enables the evaluation of the impact of economic recessions, such as the one from 2008, on these networks and the detection of assymetries between companies of different sizes. It is possible to note that, among other aspects, the air cargo transport graph is heavily influenced by the two main private companies of the sector, FedEx and UPS, what can be pointed out by, e.g., the number of nodes of 178 and 106 in 2014 respectively for these networks compared to 81 from the other 18 biggest companies.

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