Doyme, K;
Dray, L;
Schafer, A;
O'Sullivan, A;
(2019)
Simulating Airline Behavior: An Application for the Australian Domestic Market.
Transportation Research Record
10.1177/0361198119826533.
(In press).
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Abstract
In this paper we demonstrate the ability of a model, which simulates competition between air lines in a domestic aviation market, to accurately reproduce real world behaviour. The Australian market was chosen as a test case as it is a geographically isolated region with significant demand and complexity, including one of the busiest routes in the world, where connecting international passengers do not significantly skew the market. The model is based on an n-player noncooperative game, where each airline represents a player within the game. The primary assumption is that each airline attempts to maximise profits by adjusting the decision variables of airfares, flight frequency and choice of aircraft on routes within its network. The approach works iteratively, allowing each airline to respond to the decisions made by other airlines during each successive optimisation. The model is said to reach convergence when there is no significant change in any airline’s profit from one iteration to the next. Once this occurs, the predictions of each airline’s decision variables can be compared to real data. The model gives highly detailed predictions of airline specific airfares, flight frequencies on segments, passenger flows and airline market share, which strongly correlate with observed values.
Type: | Article |
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Title: | Simulating Airline Behavior: An Application for the Australian Domestic Market |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1177/0361198119826533 |
Publisher version: | https://doi.org/10.1177/0361198119826533 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | modelling aviation market, airline competition, airline behaviour, market optimization |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
URI: | https://discovery.ucl.ac.uk/id/eprint/10061807 |
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