Improvements in intra-European inter-city flight connectivity: 1996–2004

Fan, Terence Ping Ching

doi:10.1016/j.jtrangeo.2005.08.006

Cited by 25 publications

(15 citation statements)

References 12 publications

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“…While analyses of network structures and performance (Burghouwt, Hakfoort, 2001;Bowen, 2002;Reynolds-Feighan, 2007;Paleari et al, 2010;Wang et al, 2011;Lin, 2012) as well as market developments following airline deregulation (Borenstein, 1992;Dempsey, 2002;Goetz, Sutton, 1997;Chan, 2000), the emergence of new airline business models (Dobruszkes, 2006(Dobruszkes, , 2009(Dobruszkes, , 2013Fan, 2006;Francis et al, 2006;Hooper et al, 2011;Budd et al, 2014;) and economic crises (Rimmer, 2000;Alderighi, Cento, 2004;Wittman, 2014) have been conducted, a consistent framework for global supply-side market analyses from the connectivity perspective has not been applied, to date. As shown by Suau-Sanchez and Burghouwt (2012), the development of such an approach is particularly important given the increasing significance of indirect connections, which require network analyses to simultaneously model network geography and temporal schedule coordination.…”

Section: Resultsmentioning

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).…”

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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: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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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“…Burghouwt and Hakfoort (2001) found that the total seat capacity of European airport network has grown by 59% between 1990 and 1998, while the growth of intercontinental traffic and intra-European traffic has surpassed 70%. Fan (2006), examining intra-European flights between 1996 and 2004 found that the number of cities served increased by 40% (from 94 to 135), while the number of city-pairs surged by 91% (from 224 to 428). Air travel in Europe continues to grow at a rapid rate, as Eurocontrol forecasts there will be 14.4 million yearly flights in Europe by 2035, which would be 50% more than in 2012 at a growth rate of 1.8% per year (EUROCONTROL, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…However, to date relatively little attention has been paid to the factors driving the changes in European air transport networks. Exceptions are the studies by Burghouwt and Hakfoort (2001) and Fan (2006). In Burghouwt and Hakfoort (2001), the authors investigate how the capacity of the European airport network changed over the period 1990-1998 at the airport and the route level.…”

Section: Introductionmentioning

confidence: 99%

“…Although their distinction between airport and route level change overcomes the drawbacks of previous empirical studies in that the nature of change is better revealed, the study remains descriptive, thus largely ignoring the interdependence between airport (nodal) and route (dyadic) attributes. Fan (2006) provides more evidence on the evolution of inter-city air transport connectivity in Europe, showing for instance that network growth is mostly attributable to the rising importance of low-cost carriers. His analysis, however, does not explore other factors that may be driving the evolution of air transport networks in Europe.…”

Section: Introductionmentioning

confidence: 99%

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Dynamics in the European Air Transport Network, 2003–9: An Explanatory Framework Drawing on Stochastic Actor-Based Modeling

Zhang¹,

Derudder²,

Witlox³

2015

Netw Spat Econ

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In this paper, we outline and test an explanatory framework drawing on stochastic actor-based modeling to understand changes in the outline of European air transport networks between 2003 and 2009. Stochastic actor-based models show their capabilities to estimate and test the effect of exogenous and endogenous drivers on network changes in this application to the air transport network. Our results reveal that endogenous structural effects, such as transitivity triads, indirect relations and betweenness effects impact the development of the European air transport network in the period under investigation. In addition, exogenous nodal and dyadic covariates also play a role, with above all the enlargement of the European Common Aviation Area having benefitted its new members to open more air routes between them. The emergence of major low-cost airline-focused airports also significantly contributed to these changes. We conclude by outlining some avenues for further research.

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De novo venture strategy: arch incumbency at inaugural entry

Fan

2009

Strategic Management Journal

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By definition, de novo industry ventures do not share many market‐contact points with incumbents—itself an important source of competitive ‘stability’ through mutual forbearance. As such, these ventures are often subject to aggressive retaliation at the outset, which could threaten their very survival. In this study, the notion of an arch incumbent is developed, hypothesizing that, in general, a large market overlap with an incumbent lowers the survival odds of a de novo entrant. However, a large market overlap with the arch incumbent combined with an aggressive inaugural market entry or a different market positioning reduces the probability of retaliation by the arch incumbent (and subsequently other incumbents as well), and hence increases the probability of survival for a de novo entrant. The empirical experience of de novo ventures in the intra‐European passenger airline industry supports these hypotheses. Copyright © 2009 John Wiley & Sons, Ltd.

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Improvements in intra-European inter-city flight connectivity: 1996–2004

Cited by 25 publications

References 12 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

Dynamics in the European Air Transport Network, 2003–9: An Explanatory Framework Drawing on Stochastic Actor-Based Modeling

De novo venture strategy: arch incumbency at inaugural entry

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