Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?

Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?

<p>Using 27 million flight bookings for 2 years from a major international airline company, we built a Next Likely Destination model to ascertain customers’ next flight booking. The resulting model achieves an 89% predictive accuracy using historical data. A unique aspect of the model is the i...

Full description

Saved in:
Bibliographic Details
Main Author: Saravanan Thirumuruganathan (11038038) (author)
Other Authors: Soon-gyo Jung (7434773) (author), Dianne Ramirez Robillos (14151015) (author), Joni Salminen (7434770) (author), Bernard J. Jansen (7434779) (author)
Published: 2021
Subjects:
Commerce, management, tourism and services
Air transportation and freight services
Information and computing sciences
Artificial intelligence
Data management and data science
Human-centred computing
Machine learning
Prediction
Recommendation
Airlines
Travel
User evaluation
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items