The evolution of the European aviation network, 1990–1998

Burghouwt, Guillaume; Hakfoort, Jacco

doi:10.1016/s0969-6997(01)00024-2

Cited by 115 publications

(66 citation statements)

References 7 publications

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“…10 (b)), thereby outperforming the global aggregate nonstop network effects over the same period (30.5 %). Although this growth might partly be explained by economic recovery after the Gulf crisis, market deregulation should be considered a catalyst since new (albeit small) airlines entered the market (Berechman, de Wit, 1996) and above-average growth in intra-European traffic was observed (Burghouwt, Hakfoort, 2001). …”

Section: Europementioning

confidence: 99%

“…This is because as compared to legacy carriers, LCCs serve more remote (secondary) airports (Francis et al, 2006), which have 13.2 % lower average destination weights than European airports served by the 15 largest European legacy carriers. 27 In turn, the LCC growth resulted in additional connectivity at airports, which received little or no service by the legacy carriers (Burghouwt, Hakfoort, 2001;Fan, 2006;Suau-Sanchez, Burghouwt, 2011).…”

mentioning

confidence: 99%

“…While North American airlines had already operated established hub-and-spoke networks back in 1990, European legacy carriers significantly optimized their networks during the 1990s by further consolidating their (long-haul) operations at their hubs (Burghouwt, Hakfoort, 2001;Burghouwt et al, 2003) and improving temporal coordination of their schedules (Burghouwt, de Wit, 2005).…”

mentioning

confidence: 99%

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How air transport connects the world – A new metric of air connectivity and its evolution between 1990 and 2012

Allroggen

Wittman

Malina

2015

Transportation Research Part E: Logistics and Transportation Re

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SUMMARY ObjectiveScheduled air transport services connect airports throughout the world and thereby enable interaction on a global scale. By doing so, they spur globalization (Hummels, 2007) as well as social and economic development (Lakshmanan, 2011). In order to facilitate integration of regions into global value chains, planners, scholars and policymakers therefore need to understand as to how scheduled air transport services link a region to other markets. For this purpose, connectivity metrics have been developed, which measure the degree of connections between airports (Burghouwt, Redondi, 2013). In particular, the 'connection quality-weighting' approach (Veldhuis, 1997;Burghouwt, de Wit, 2005) has been used to compute the aggregate quality of all available connections at an airport with regard to their properties in quickly bridging distances. However, such a metric has neither been calibrated on the basis of observed passenger behavior nor been computed for the world's airports across a multi-decade time series. This paper sets out to develop the first such metric and to discuss global airline network development between 1990 and 2012 from a connectivity perspective. How Air Transport Connects the World 4 MethodologyThe Global Connectivity Index (GCI) for each airport is computed by summing the connectionquality of each available flight connection weighted by the interaction potential, to which the connection provides access. This requires three levels of analysis. First, on the link-identification level, we identify from OAG flight schedules all scheduled nonstop and onestop connections, which are available to passengers at each airport. Second, on the link-quality level, we compute each connection's frequency and relative connectivity value as compared to (hypothetical) nonstop flights. The relative connectivity value is derived from flight duration and layover time and calibrated through observed routing data for US passengers. Third, on the destination-quality level, we model the interaction potential, to which each worldwide airport provides access. For this purpose, we use gridded wealth-adjusted population data and a distance-decay function. Transaction-specific idiosyncrasies such as tastes or fares, which vary among potential passengers and impact on each passenger's itinerary choice, are not considered since they cannot be aggregated to the route level, yet. Results By computing yearly GCITo date, no analysis exists which evaluates 'quality-weighted' connectivity and/or centrality at the world's airports with the help of an empirically calibrated model. Such a model is developed in this paper. We compute these metrics to analyze worldwide connectivity and centrality trends The remainder of this paper proceeds as follows: In Section 2, the building blocks of 'connection quality-weighted' connectivity and centrality are outlined. Section 3 develops the connectivity and the centrality metrics. Global and world-region trends in connectivity and centrality between 1990 and 2012 are analyzed in Sect...

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Section: Europementioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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How air transport connects the world – A new metric of air connectivity and its evolution between 1990 and 2012

Allroggen

Wittman

Malina

2015

Transportation Research Part E: Logistics and Transportation Re

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“…For this reason, a large number of studies have focused on the long-term dynamics of airport networks, with the aim of investigating the transition from point-to-point to hub-and-spoke structures observed first in Europe and the US, and more recently in emerging economies. For example, in the European air network between 1990 and 1998, it has been observed (Burghouwt and Hakfoort, 2001) that medium-sized airports have attracted most of the intra-European traffic, creating specialised internal hubs, while intercontinental traffic has also been concentrated, but on different hubs, usually large airports.…”

Section: Complexity Science 21 Complex Network In Atmmentioning

confidence: 99%

Applying complexity science to air traffic management

Cook

Blom

Lillo

et al. 2015

Journal of Air Transport Management

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Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.

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“…The advantages of such a radial hub-and-spoke configuration, as compared to a point-to-point configuration (Figure 1), are obvious: for the same number of destinations, there are fewer routes to serve, which in turn yields the possibility of higher flight frequencies and bigger aircrafts (Burghouwt and Hakfoort 2001).…”

Section: Context: the Numerical Study Of Human Infrastructure Networkmentioning

confidence: 99%

Measuring hierarchical differentiation: connectivity and dominance in the European urban network

Nuffel

Saey

Derudder

et al. 2010

Transportation Planning and Technology

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To refer to or to cite this work, please use the citation to the published version:Van Nuffel, N., Saey, P., Derudder, B., Devriendt, L., Witlox, F. (2010 AbstractThis paper presents an examination of the empirical merits of a set of spatial interaction indices for measuring hierarchical differentiation (i.e. dominance and connectivity) in a spatial network. To allow for the comparison of the degree of hierarchical differentiation in networks with different number of nodes/links, we propose to normalize the ratio between the real measures and the corresponding values for a rank size distribution in order to obtain readily interpretable measures of hierarchical differentiation. When applied to data on 2 air passenger flows within Europe, the normalized indices, interpreted together, appear to give a good idea of the tendency towards hierarchical differentiation.The potential usefulness of this analytical framework is discussed in the context of studies on (transnational) inter-city relations and empirical assessments of changes in the spatial configuration of airline networks.

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The evolution of the European aviation network, 1990–1998

Cited by 115 publications

References 7 publications

How air transport connects the world – A new metric of air connectivity and its evolution between 1990 and 2012

How air transport connects the world – A new metric of air connectivity and its evolution between 1990 and 2012

Applying complexity science to air traffic management

Measuring hierarchical differentiation: connectivity and dominance in the European urban network

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