Type of Publication: Article in Journal

Optimizing the Conditional Value-at-Risk in Revenue Management

Author(s):

Gönsch, J.; Hassler, M.

Title of Journal:

Review of Managerial Science

Publication Date:

2014

Number of Issue:

8

pages:

495-521

Keywords:

Revenue management; Capacity control; Dynamic decisions; Dynamic programming; Risk-aversion; Conditional value-at-risk

Fulltext:

Optimizing the Conditional Value-at-Risk in Revenue Management (709 KB)

Link to complete version:

https://doi.org/10.1007/s11846-013-0114-4

Citation:

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Abstract

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.