How recommender systems can transform airline offer construction and retailing

Amine Dadoun (), Michael Defoin-Plate (), Thomas Fiig (), Corinne Landra () and Raphaël Troncy ()
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Amine Dadoun: Eurecom, Sophia Antipolis
Michael Defoin-Plate: Amadeus, Sophia Antipolis
Thomas Fiig: Amadeus
Corinne Landra: Amadeus, Sophia Antipolis
Raphaël Troncy: Eurecom, Sophia Antipolis

A chapter in Artificial Intelligence and Machine Learning in the Travel Industry, 2023, pp 93-107 from Springer

Abstract: Abstract Recommender systems have already been introduced in several industries such as retailing and entertainment, with great success. However, their application in the airline industry remains in its infancy. We discuss why this has been the case and why this situation is about to change in light of IATA’s New Distribution Capability standard. We argue that recommender systems, as a component of the Offer Management System, hold the key to providing customer centricity with their ability to understand and respond to the needs of the customers through all touchpoints during the traveler journey. We present six recommender system use cases that cover the entire traveler journey and we discuss the particular mind-set and needs of the customer for each of these use cases. Recent advancements in Artificial Intelligence have enabled the development of a new generation of recommender systems to provide more accurate, contextualized and personalized offers to customers. This paper contains a systematic review of the different families of recommender system algorithms and discusses how the use cases can be implemented in practice by matching them with a recommender system algorithm.

Keywords: Recommender systems; Artificial intelligence; Dynamic offer construction; NDC (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-25456-7_7

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