A comparative study of airport connectivity in China, Europe and US: Which network provides the best service to passengers?

Paleari, Stefano; Redondi, Renato; Malighetti, Paolo

doi:10.1016/j.tre.2009.08.003

Cited by 112 publications

(60 citation statements)

References 19 publications

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“…We do not follow analyses of shortest and quickest paths (e.g. Shaw, Ivy, 1994;Malighetti et al, 2008;Paleari et al, 2010;Zhang et al, 2010), but instead identify all connections, which a passenger might consider a feasible travel option. In so doing, we follow our objective to evaluate connectivity and centrality of the entire network as perceived by passengers.…”

Section: Figmentioning

confidence: 99%

“…Most analyses of air transport networks (e.g. Shaw, Ivy, 1994, Paleari et al, 2010 do not consider this quality dimension since they intend to evaluate traffic patterns and overall network performance without accounting for destination properties. In order to meet our objective of assessing the quality of each connection from a potential passenger's perspective and in line with the Economic Geography literature (Redding, Venables, 2004;Breinlich, 2006;Redding, 2010), we add a destination quality dimension to the connectivity model.…”

Section: Figmentioning

confidence: 99%

“…6 In an effort to avoid potential seasonality bias caused by computing connectivity scores for a small number of days (e.g. Malighetti et al, 2008;Paleari et al, 2010;Redondi et al, 2011), we run a yearly connectivity analysis. Therefore, frequency !…”

Section: Frequency Modelmentioning

confidence: 99%

“…In their review, Burghouwt and Redondi (2013) distinguish several metrics, including metrics based on shortest and quickest connection paths (e.g. Shaw, Ivy, 1994;Malighetti et al, 2008;Paleari et al, 2010;Zhang et al, 2010) as well as metrics computed by summing connection quality over all available connections (e.g. Veldhuis, 1997;Burghouwt, de Wit, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…Veldhuis, 1997, Paleari et al, 2010. As most passengers transfer at hubs where airlines coordinate incoming and outgoing traffic to offer indirect connectivity (Burghouwt, de Wit, 2005), bias of using a short MCT is smaller than using long MCT.…”

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: Figmentioning

confidence: 99%

Section: Figmentioning

confidence: 99%

Section: Frequency Modelmentioning

confidence: 99%

Section: Introductionmentioning

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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Origin–destination synthesis for aviation network data: examining hub operations in the domestic and international US markets

Park

O’Kelly

2016

J of Advced Transportation

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Hub-and-spoke networking is a key feature of current aviation markets in which hubs, as connecting points, function to consolidate and redistribute flows. This indicates that observation of traffic on a segment does not necessarily convey information about the origin to destination routing of passenger journeys because of the unavoidable detours in the system. This paper examines the heterogeneity of the flow composition in domestic and international US markets, which in turn allows us to observe the variation of operations across major hubs. A modified Route Flow Estimator for origin-destination synthesis (or origin-destination matrix estimation) is designed to decompose the segment traffic into itinerary-based passenger trips. Several public and commercial databases, which are easily accessible, are exploited (and reconciled) for the model in order to (i) generate possible trip itineraries using those segment markets, and (ii) link data-driven operational conditions with the underlying segment flows. The results are validated with US domestic trip observations and empirical knowledge related to the air transportation system. Then, the variability of the hub operations is examined based on sensitivity tests using the model parameters. From the resolution of itinerary-based estimates, we observe that major airports' hub operations are spatially uneven, particularly with respect to domestic and international connecting passengers.

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Logistics in China

Feng

Lee

2012

International Series in Operations Research &Amp; Management Science

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A comparative study of airport connectivity in China, Europe and US: Which network provides the best service to passengers?

Abstract: Gestionale è approvato dal Comitato di Redazione. I Working Papers della Collana costituiscono un servizio atto a fornire la tempestiva divulgazione dei risultati dell'attività di ricerca, siano essi in forma provvisoria o definitiva.

Cited by 112 publications

References 19 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

Origin–destination synthesis for aviation network data: examining hub operations in the domestic and international US markets

Logistics in China

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