The impact of the COVID-19 on the industry has highlighted once again the need to create new ways of addressing consumers that would be less reliant on historic data, and more adjusted to recent observations of consumer behaviour, real time experiments and competitive context. This article addresses the implications of consumer behavioural economics in the design of offers and the way airlines will have to rethink the way they price in a New Distribution Capability (NDC) world, as defined by IATA. In a pandemic impacted era, this investment will show its fruits not only after, but also during the recovery phase, where travel behaviour is exceptionally different, capacity fluctuates and the competitive landscape is equally difficult to predict. We will discuss what challenges a pricing department is facing in this new world of offers, as well as how to overcome them in order to provide relevant and personalised offers to each consumer and price them according to the value that these offers bring. In the COVID-19 context as well as post-pandemic, airlines will need to not only respond quicker with capacity adjustments, but also to better understand human behaviour relative to a purchase decision and address each consumer with an optimised offer in real-time, as they request it. Some of the questions for which new artificial intelligence experimentation techniques and behavioural economics models will require significant development are: What drives a person to choose or not to choose a certain offer? How many choices should they see? What trip purpose segment do they belong to? What is their willingness to pay? What attributes of an offer are people considering and what value do they associate to these offers?

COVID-19 对行业的影响再次凸显了需要创造新的解决消费者问题的方式，这种方式将减少对历史数据的依赖，并更多地适应最近对消费者行为、实时实验和竞争环境的观察。本文讨论了消费者行为经济学在优惠设计中的影响，以及航空公司在 IATA 定义的新分销能力 (NDC) 世界中必须重新思考定价方式的方式。在大流行影响的时代，这项投资不仅会在恢复阶段之后，而且会在恢复阶段取得成果，在这个阶段，旅行行为异常不同，容量波动，竞争格局同样难以预测。我们将讨论定价部门在这个新的优惠世界中面临的挑战，以及如何克服它们以便为每个消费者提供相关和个性化的优惠，并根据这些优惠带来的价值对其进行定价。在 COVID-19 和大流行后，航空公司不仅需要通过容量调整更快地做出响应，而且还需要更好地了解与购买决策相关的人类行为，并实时向每个消费者提供优化的报价，按照他们的要求。新的人工智能实验技术和行为经济学模型需要重大发展的一些问题是：是什么驱使人们选择或不选择某个报价？他们应该看到多少个选择？他们属于哪个旅行目的段？他们的支付意愿如何？人们正在考虑要约的哪些属性以及他们与这些要约相关联的价值是什么？