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How recommender systems can transform airline offer construction and retailing

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’...

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Autores principales: Dadoun, Amine, Defoin-Platel, Michael, Fiig, Thomas, Landra, Corinne, Troncy, Raphaël
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Palgrave Macmillan UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980747/
http://dx.doi.org/10.1057/s41272-021-00313-2
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author Dadoun, Amine
Defoin-Platel, Michael
Fiig, Thomas
Landra, Corinne
Troncy, Raphaël
author_facet Dadoun, Amine
Defoin-Platel, Michael
Fiig, Thomas
Landra, Corinne
Troncy, Raphaël
author_sort Dadoun, Amine
collection PubMed
description 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.
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spelling pubmed-79807472021-03-23 How recommender systems can transform airline offer construction and retailing Dadoun, Amine Defoin-Platel, Michael Fiig, Thomas Landra, Corinne Troncy, Raphaël J Revenue Pricing Manag Practice Article 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. Palgrave Macmillan UK 2021-03-20 2021 /pmc/articles/PMC7980747/ http://dx.doi.org/10.1057/s41272-021-00313-2 Text en © The Author(s), under exclusive licence to Springer Nature Limited 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Practice Article
Dadoun, Amine
Defoin-Platel, Michael
Fiig, Thomas
Landra, Corinne
Troncy, Raphaël
How recommender systems can transform airline offer construction and retailing
title How recommender systems can transform airline offer construction and retailing
title_full How recommender systems can transform airline offer construction and retailing
title_fullStr How recommender systems can transform airline offer construction and retailing
title_full_unstemmed How recommender systems can transform airline offer construction and retailing
title_short How recommender systems can transform airline offer construction and retailing
title_sort how recommender systems can transform airline offer construction and retailing
topic Practice Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980747/
http://dx.doi.org/10.1057/s41272-021-00313-2
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