In practice, human-decision makers often feel uncomfortable with the risk-neutral revenue management systems' output. Reasons include a low number of repetitions of similar events, a critical impact of the achieved revenue for economic survival, or simply business constraints imposed by...

Many industries use revenue management to balance uncertain, stochastic demand and inflexible capacity. Popular examples include airlines, hotels, car rentals, retailing, and manufacturing. The classical revenue management approaches considered in theory and practice are based on two...

In many revenue management applications risk-averse decision-making is crucial. In dynamic settings, however, it is challenging to find the right balance between maximizing expected rewards and avoiding poor performances. In this paper, we consider time-consistent mean-semivariance (MSV)...