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

Weiwei Wu,Haoyu Zhang,Tao Feng,Frank Witlox

doi:10.3390/su11164408

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.

Highlights

The global aviation industry has experienced unprecedented growth in terms of supply and demand
This paper examines flight delay propagation in air transport networks
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Summary

Introduction

The global aviation industry has experienced unprecedented growth in terms of supply and demand. The SIS model is utilised to understand the process of flight delay propagation in the context of an air transport network and explain the spreading characteristics between different routes in the entire network. In this regard, the paper sheds lights on the modelling and further understanding of flight delay propagations in the following three aspects: (i) Introducing and extending the SIS model to a flight SIS (FSIS) network model; (ii) estimating the delay propagation probabilities, and (iii) testing the model at the level of airports and airline networks by proposing delay control solutions.

Delay Propagation Model

Delay Propagation Probability

Elastic Analysis of Delay Propagation

Findings

Controlling Delay