Abstract In a context of debate over the future of the US Federal Aviation Administration's (FAA) funding model, this paper revisits the current system of airport classification used for the allocation of public funding for capacity developments. Previous papers have already addressed the limitations of the FAA's uni-dimensional method, and proposed new approaches that take into account the two dimensions of “hubbing” activity, i.e., traffic generation and connectivity. However, these studies are biased by the lack of detailed demand data on international connections. Using an MIDT dataset comprising a sample of domestic and international markets served by US airports during the first quarter of 2013, this paper aims at providing a full picture on the pitfalls of the existing FAA method, as well as addressing the impact of international connectivity in characterising the airports' hubbing profiles. Hierarchical clustering is used to provide alternative criteria for hub classification within the context of US National Plan of Integrated Airport Systems (NPIAS). This new typology of primary US airports can help to optimize AIP funding by allowing for further differentiation in the FAA allocation criteria.
Highlights We analyse the pitfalls of the FAA airport typology used to allocate AIP funds. Both domestic and international markets are included in our MIDT dataset. Results indicate that the “hubbing” profiles of large US airports vary widely. We propose a new typology that reflects each airport's role within the US network. This method can help to optimize AIP funding allocation.
Regulatory airport classification in the US: The role of international markets
Transport Policy ; 37 ; 157-166
2014-11-05
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Regulatory airport classification in the US: The role of international markets
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