A network modelling approach to flight delay propagation: some empirical evidence from China

Weiwei Wu, Haoyu Zhang (Corresponding author), Tao Feng, Frank Witlox

Research output: Contribution to journalArticleAcademicpeer-review

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.

LanguageEnglish
Article number4408
Number of pages16
JournalSustainability
Volume11
Issue number16
DOIs
StatePublished - 1 Aug 2019

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Airports
flight
airport
China
modeling
evidence
Costs
Time delay
transport network
costs
cost
Air
air
efficiency
time

Keywords

  • Air transport network
  • China
  • Delay propagation probability
  • Flight delay propagation
  • Susceptible-infected-susceptible (SIS) model

Cite this

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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.",
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A network modelling approach to flight delay propagation : some empirical evidence from China. / Wu, Weiwei; Zhang, Haoyu (Corresponding author); Feng, Tao; Witlox, Frank.

In: Sustainability, Vol. 11, No. 16, 4408, 01.08.2019.

Research output: Contribution to journalArticleAcademicpeer-review

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