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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