The book provides a comprehensive overview of current practices and future directions in airline revenue management. It explains state-of-the-art revenue management approaches and outlines how these will be augmented and enhanced through modern data science and machine learning methods in the future. Several practical examples and applications will make the reader familiar with the relevance of the corresponding ideas and concepts for an airline commercial organization. The book is ideal for both students in the field of airline and tourism management as well as for practitioners and industry experts seeking to refresh their knowledge about current and future revenue management approaches, as well as to get an introductory understanding of data science and machine learning methods. Each chapter closes with a checkpoint, allowing the reader to deepen the understanding of the contents covered.

This textbook has been recommended and developed for university courses in Germany, Austriaand Switzerland.

About the Author

Curt Cramer is an Advanced Analytics and Data Science executive in the retail industry. He has gathered extensive applied analytics experience in 15 years of consulting and line management responsibilities across industries, including leisure travel. He holds a Ph. D. in Engineering/Computer Science from the University of Karlsruhe/KIT.

Andreas Thams is an Honorary Professor for Airline Management at University of Applied Sciences Worms. He held various commercial management positions in the airline, travel, and logistics industry, particularly in the field of revenue management. He has a Ph. D. in Econometrics from Freie Universit�t Berlin.

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