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Artificial Intelligence and Machine Learning in the Travel Industry

Edited by Ben Vinod ()

in Springer Books from Springer

Date: 2023
ISBN: 978-3-031-25456-7
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Chapters in this book:

Special issue on artificial intelligence/machine learning in travel
B. Vinod
Price elasticity estimation for deep learning-based choice models:an application to air itinerary choices
Rodrigo Acuna-Agost, Eoin Thomas and Alix Lhéritier
An integrated reinforced learning and network competition analysis for calibrating airline itinerary choice models with constrained demand
Ahmed Abdelghany, Khaled Abdelghany and Ching-Wen Huang
Decoupling the individual effects of multiple marketing channels with state space models
Melvin Woodley
Competitive revenue management models with loyal and fully flexible customers
Ravi Kumar, Wei Wang, Ahmed Simrin, Sivarama Krishnan Arunachalam, Bhaskara Rao Guntreddy and Darius Walczak
Demand estimation from sales transaction data: practical extensions
Norbert Remenyi and Xiaodong Luo
How recommender systems can transform airline offer construction and retailing
Amine Dadoun, Michael Defoin-Plate, Thomas Fiig, Corinne Landra and Raphaël Troncy
A note on the advantage of context in Thompson sampling
Michael Byrd and Ross Darrow
Shelf placement optimization for air products
Tomasz Szymanski and Ross Darrow
Applying reinforcement learning to estimating apartment reference rents
Jian Wang, Murtaza Das and Stephen Tappert
Machine learning approach to market behavior estimation with applications in revenue management
Nitin Gautam, Shriguru Nayak and Sergey Shebalov
Multi-layered market forecast framework for hotel revenue management by continuously learning market dynamics
Rimo Das, Harshinder Chadha and Somnath Banerjee
Artificial Intelligence in travel
B. Vinod
The key to leveraging AI at scale
Deborah Leff and Kenneth T. K. Lim
The future of AI is the market
Ross M. Darrow

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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprbok:978-3-031-25456-7

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DOI: 10.1007/978-3-031-25456-7

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