Artificial intelligence and machine learning in the travel industry : simplifying complex decision making / Ben Vinod, editor.
Vinod, Ben, editor.
2023
G156.5.I5
Available Online

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Title
Artificial intelligence and machine learning in the travel industry : simplifying complex decision making / Ben Vinod, editor.
ISBN
9783031254567 (electronic bk.)
3031254562 (electronic bk.)
9783031254550
3031254554
DOI
https://doi.org/10.1007/978-3-031-25456-7
Published
Cham : Palgrave Macmillan, 2023.
Language
English
Description
1 online resource (vi, 182 pages)
Item Number
10.1007/978-3-031-25456-7 doi
Call Number
G156.5.I5
Dewey Decimal Classification
338.4791028563
Summary
Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel. The leading sectors adopting AI rapidly are Financial Services, Automotive and Assembly, High Tech and Telecommunications. Travel has been slow in adoption, but the opportunity for generating incremental value by leveraging AI to augment traditional analytics driven solutions is extremely high. The contributions in this book, originally published as a special issue for the Journal of Revenue and Pricing Management, showcase the breadth and scope of the technological advances that have the potential to transform the travel experience, as well as the individuals who are already putting them into practice. Ben Vinod is a co-founder of Charter and Go, a dynamic offer, order management, and dispatch solution for air charter operators. He served as vice president of pricing, yield management, and reservations inventory control at American Airlines Decision Technologies (1993-1999) and was senior vice president and chief scientist at Sabre (2008-2020), focused on innovation and thought leadership in pioneering advanced solutions across the travel value chain for travel suppliers and intermediaries. He has published over 50 articles in academic and trade journals, is a member of AGIFORS, and serves on the editorial board of the Journal of Revenue and Pricing Management. .
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed June 2, 2023).
Added Author
Vinod, Ben, editor.
Available in Other Form
Artificial intelligence and machine learning in the travel industry
Linked Resources
Online Access
Record Appears in
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All Resources
1. Special issue on artificial intelligence/machine learning in travel
2. Price elasticity estimation for deep learning-based choice models: an application to air itinerary choices
3. An integrated reinforced learning and network competition analysis for calibrating airline itinerary choice models with constrained demand
4. Decoupling the individual effects of multiple marketing channels with state space models
5. Competitive revenue management models with loyal and fully flexible customers
6. Demand estimation from sales transaction data: practical extensions
7. How recommender systems can transform airline offer construction and retailing
8. A note on the advantage of context in Thompson sampling
9. Shelf placement optimization for air products
10. Applying reinforcement learning to estimating apartment reference rents
11. Machine learning approach to market behavior estimation with applications in revenue management
12. Multi-layered market forecast framework for hotel revenue management by continuously learning market dynamics
13. Artificial Intelligence in travel
14. The key to leveraging AI at scale
15. The future of AI is the market.

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