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Open AccessArticle

A Network Modelling Approach to Flight Delay Propagation: Some Empirical Evidence from China

1, 1,2,*, 3 and 1,2,4
1
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China
2
Department of Geography, Ghent University, Krijgslaan 281/S8, B9000 Gent, Belgium
3
Department of the Built Environment, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands
4
Department of Geography, University of Tartu, Vanemuise 46, 51014 Tartu, Estonia
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(16), 4408; https://doi.org/10.3390/su11164408
Received: 24 June 2019 / Revised: 29 July 2019 / Accepted: 31 July 2019 / Published: 15 August 2019
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Abstract

This paper examines flight delay propagation in air transport networks. Delays add to additional costs, inefficiencies, and unsustainable development. An integrated flight-based susceptible-infected-susceptible (FSIS) model was developed to analyse the flight delay process from a network-based perspective. The probability of flight delay propagation was determined using a translog model. The model was applied to an airline network consisting of thirty-three routes involving three airlines. The results show that the propagation probability is network-related and varies across different routes. The variation is related to the flight frequencies at airports, route distances, scheduled buffer times, and the propagated delay time. Whereas buffer time has a greater impact on smaller airports, flight movement has a greater impact on larger airports. Having a better understanding of how delays happen can help the development of strategies to avoid them. This will lead to less costs, higher efficiencies, and more sustainable airport and airline development. View Full-Text
Keywords: air transport network; flight delay propagation; susceptible-infected-susceptible (SIS) model; delay propagation probability; China air transport network; flight delay propagation; susceptible-infected-susceptible (SIS) model; delay propagation probability; China
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Wu, W.; Zhang, H.; Feng, T.; Witlox, F. A Network Modelling Approach to Flight Delay Propagation: Some Empirical Evidence from China. Sustainability 2019, 11, 4408.

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