A Survey on Risk-Averse and Robust Revenue Management

Abstract 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 assumptions. First, demand – as the only uncertain variable – follows a known distribution and, second, risk-neutrality justifies the maximization of expected revenue. Recently, two related streams of literature emerged that do not need these assumptions. Research on risk-averse revenue management acknowledges that, in practice, many decision makers are risk-averse. Research on robust revenue management focuses worst-case scenarios without a known demand distribution, which is especially relevant for new and extremely unstable businesses. This paper motivates the consideration of risk-averse and robust revenue management. We briefly introduce revenue managements’ two main methods – capacity control and dynamic pricing – in the classical, risk-neutral setting. Then, we provide an exhaustive review of the literature on risk-averse and robust capacity control and dynamic pricing. In doing so, the relevant decision criteria are briefly introduced. Finally, possible avenues for future research are outlined.