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

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

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Uittreksel

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.

TaalEngels
Artikelnummer4408
Aantal pagina's16
TijdschriftSustainability
Volume11
Nummer van het tijdschrift16
DOI's
StatusGepubliceerd - 1 aug 2019

Vingerafdruk

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

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    Citeer dit

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    title = "A network modelling approach to flight delay propagation: some empirical evidence from China",
    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, Nr. 16, 4408, 01.08.2019.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    TY - JOUR

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    T2 - Sustainability

    AU - Wu,Weiwei

    AU - Zhang,Haoyu

    AU - Feng,Tao

    AU - Witlox,Frank

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    N2 - 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.

    AB - 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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    KW - Delay propagation probability

    KW - Flight delay propagation

    KW - Susceptible-infected-susceptible (SIS) model

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