How recommender systems can transform airline offer construction and retailing

Dadoun, Amine; Defoin-Platel, Michael; Fiig, Thomas; Landra, Corinne; Troncy, Raphaël
Journal of Revenue and Pricing Management, March 2021

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.


DOI
Type:
Journal
Date:
2021-03-19
Department:
Data Science
Eurecom Ref:
6501
Copyright:
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in Journal of Revenue and Pricing Management, March 2021 and is available at : https://doi.org/10.1057/s41272-021-00313-2

PERMALINK : https://www.eurecom.fr/publication/6501