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.

推荐系统已经在零售和娱乐等多个行业中引入，并取得了巨大的成功。但是，它们在航空业中的应用还处于起步阶段。我们将讨论这种情况的发生原因，以及根据IATA的新分销能力标准，这种情况将要改变的原因。我们认为，推荐系统作为报价管理系统的组成部分，对于提供以客户为中心的能力，使他们能够在旅行过程中通过所有接触点理解并响应客户的需求，具有关键性。我们提出了六个推荐器系统用例，涵盖了整个旅行者的旅程，并且我们讨论了每种用例的特定思维定式和客户需求。人工智能的最新进展使新一代推荐系统的开发成为可能，从而可以为客户提供更准确，上下文相关和个性化的服务。本文包含对推荐器系统算法的不同系列的系统综述，并讨论了如何通过与推荐器系统算法进行匹配来在实际中实现用例。