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.

Authors

  • Joao Pedro Pinheiro Malere Instituto Tecnológico de Aeronáutica
  • Vladimir Minas Instituto Tecnológico de Aeronáutica
  • Giovanna Miceli Ronzani Borille Instituto Tecnológico de Aeronáutica

DOI:

https://doi.org/10.14295/transportes.v24i4.1096

Keywords:

Cargo air transportation networks, social network analysis, complex networks.

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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References

Batti, D. A. B., & Faria, C. A. (2011). Transporte aéreo-uma alternativa ao transporte rodoviário de cargas. Journal of Transport Literature, 5(2), 92-105.

BOEING (2014). World Air Cargo forecast – 2014-15. <http://www.boeing.com/resources/boeingdotcom/commercial/about-our-market/cargo-market-detail-wacf/download-report/assets/pdfs/wacf.pdf>. Acessado em 20 de novembro de 2015.

Bowen, J. T. (2004). The geography of freighter aircraft operations in the Pacific Basin. Journal of Transport Geography, 12(1), 1-11. DOI: 10.1016/S0966-6923(03)00024-3.

Brownrigg R (2012) Package ‘maps’. Disponível em <http://cran.r-project.org/web/packages/maps/>. Acessado en 20 de março de 2016.

BTS 1 (2016). Number of U.S. Airports. <http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_01_03.html>. Acessado em 01 de julho de 2016.

BTS 2 (2016). Weight of shipments by transportation mode .<http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/data_and_statistics/by_subject/freight/freight_facts_2015/chapter2/table2_1>.Acessado em 01 de julho de 2016.

Cerqueira, C. H. Z., de Souza Costa, J. M., & de Araujo Carvalho, D. M. (2014). Aplicação de Análise de Redes Sociais em uma Cadeia de Suprimentos de uma Empresa do Setor Elétrico Brasileiro. Sistemas & Gestão, 9(4), 418-429. DOI: 10.7177/sg.2014.v9.n4.a1

Cook, G. N., & Goodwin, J. (2008). Airline Networks: A Comparison of Hub-and-Spoke and Point-to-Point SystemsAirline Networks: A Comparison of Hub-and-Spoke and Point-to-Point Systems. Journal of Aviation/Aerospace Education & Research, 17(2), 1.

Couto, G. S., Silva, A. P. C. D., Ruiz, L. B., & Benevenuto, F. (2015). Structural properties of the Brazilian air transportation network. Anais da Academia Brasileira de Ciências, 87(3), 1653-1674. DOI: 10.1590/0001-3765201520140155.

Csardi G, Nepusz T (2006): The igraph software package for complex network research, InterJournal, Complex Systems 1695.

De Nooy, W., Mrvar, A., & Batagelj, V. (2011). Exploratory social network analysis with Pajek (Vol. 27). Cambridge University Press. DOI: 10.1017/CBO9780511806452.

Donatelli, D. J. (2012). Evolution of US air cargo productivity (Master of Science Dissertation, Massachusetts Institute of Technology).

DOT (2012). Aviation industry Performance - A review of the aviation industry, 2008-2011. <https://www.oig.dot.gov/sites/default/files/Aviation%20Industry%20Performance%5E9-24-12.pdf>. Acessado em 28 de Agosto de 2016.

Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social networks, 1(3), 215-239. DOI: 10.1016/0378 8733(78)90021-7.

Grandjot, H. H., Roessler, I., & Roland, A. (2007). Air Cargo Guide: An introduction to the air cargo industry. Huss-Verlag.

Helmig, C. (2005). Welcome the Change. Flying Fresh–The perishable air cargo magazine, 1, 5.

Morning Star (2016). FedEx is one of two titans in private U.S. parcel shipping. We don't expect this to change <http://analysisreport.morningstar.com/stock/research/c-report?t=XNYS:FDX&region=usa&culture=en-US&productcode=MLE&cur=>. Acessado em 28 de Agosto de 2016.

Newman, M. E. (2003). The structure and function of complex networks. SIAM review, 45(2), 167-256. DOI:10.1137/S003614450342480.

Newman, M. E. (2004). Analysis of weighted networks. Physical Review E,70(5), 056131. DOI:10.1103/PhysRevE.70.056131

Onghena, E. (2013). From cost structure to strategy: the impact of the cost structure on the strategic behavior of integrators (PhD thesis Faculty of Applied Economic Sciences, University of Antwerp).

Page, L., Brin, S., Motwani, R., & Winograd, T. (1998). The PageRank citation ranking: bringing order to the Web. Tech. Rep., Stanford Digital Library Technologies Project. DOI: 10.1.1.31.1768

Reka A., Barabási A.L. (2002). Statistical mechanics of complex networks. Rev Mod Phys 74:47-97.

Scholz, A. B. (2012). Network structures of cargo airlines-an empirical and a modelling approach. KIT Scientific Publishing.

Scott, J. (1991). Networks of corporate power: A comparative assessment. Annual Review of Sociology, 181-203.

Scott, J., & Carrington, P. J. (2014). The SAGE handbook of social network analysis. SAGE publications. DOI: 10.4135/9781446294413.

Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (Vol. 8). Cambridge university press.

Published

2016-12-01

How to Cite

Pinheiro Malere, J. P., Minas, V., & Miceli Ronzani Borille, G. (2016). 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. TRANSPORTES, 24(4), 1–9. https://doi.org/10.14295/transportes.v24i4.1096

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