Optimizing the Conditional Value-at-Risk in Revenue Management
Review of Managerial Science 8 (2014), pp. 495-521
36 Pages Posted: 6 Apr 2013 Last revised: 21 Sep 2014
Date Written: July 10, 2013
Many service industries use revenue management to balance demand and capacity. The assumption of risk-neutrality lies at the heart of the classical approaches, which aim at maximizing expected revenue. In this paper, we give a comprehensive overview of the existing approaches, most of which were only recently developed, and discuss the need to take risk-averse decision makers into account. We then present a heuristic that maximizes Conditional Value-at-Risk (CVaR). Although CVaR has become increasingly popular in finance and actuarial science due to its beneficial properties, this risk measure has not yet been considered in the context of revenue management. We are able to efficiently solve the optimization problem inherent in CVaR by taking advantage of specific structural properties that allow us to reformulate this optimization problem as a continuous knapsack problem. In order to demonstrate the applicability and robustness of our approach, we conduct a simulation study that shows that the new approach can significantly improve the risk profile in various scenarios.
Keywords: Revenue Management, Capacity Control, Dynamic Decisions, Dynamic Programming, Risk-Aversion, Conditional Value-at-Risk
JEL Classification: M11, M19, C61, C63
Suggested Citation: Suggested Citation