Abstract
This paper proposes a model for dynamic booking forecasting using a time-inhomogeneous Markov process. The transition probabilities are estimated based on a combination of an empirical and a parametric distribution. This model is applied for flight booking forecasting, where flight forecasts are updated on a daily basis over a time horizon of up to 300 days before the day of departure. The distribution of flight bookings over this time horizon, as well as the expected average flight bookings are determined. Historical data of two years of flights is used in our numerical analysis. The performance of our model is compared with two classical forecasting methods: the additive pickup method and the historical average. We show that our proposed model is up to 8% more accurate than the two classical methods mentioned above. Moreover, by determining the distribution of the flight bookings over a horizon of 300 days before departure, we provide additional information about the uncertainty around the flight
bookings.
bookings.
Original language | English |
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Title of host publication | Proceedings of the 21st Air Transport Research Society World Conference |
Number of pages | 7 |
Publication status | Published - 2017 |
Event | 21st Air Transport Research Society World Conference - University of Antwerp Stadscampus, Antwerp, Belgium Duration: 5 Jul 2017 → 8 Jul 2017 Conference number: 21 https://www.uantwerpen.be/en/conferences/atrs-2017-air-transport-conference/ |
Conference
Conference | 21st Air Transport Research Society World Conference |
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Abbreviated title | ATRS 2017 |
Country/Territory | Belgium |
City | Antwerp |
Period | 5/07/17 → 8/07/17 |
Other | This four-day event allowed presentation and discussion of on the one hand completed research in air transportation and on the other hand research in process. Also PhD researchers received the opportunity to present their work. Moreover, it wa a perfect opportunity for scientists and practitioners to deepen their knowledge in theoretical topics as well as practice and to discuss new research areas and business opportunities. |
Internet address |
Keywords
- Airline Booking Forecasting
- Markov Processes