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Practical decision rules for risk-averse revenue management using simulation-based optimization

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  • Sebastian Koch

    (University of Augsburg)

  • Jochen Gönsch

    (University of Duisburg-Essen)

  • Michael Hassler

    (University of Augsburg)

  • Robert Klein

    (University of Augsburg)

Abstract

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 management. However, solving capacity control problems is a challenging task for many risk measures and the approaches are often not compatible with existing software systems. In this paper, we propose a flexible framework for risk-averse capacity control under customer choice behavior. Existing risk-neutral decision rules are augmented by the integration of adjustable parameters. Our key idea is the application of simulation-based optimization (SBO) to calibrate these parameters. This allows to easily tailor the resulting capacity control mechanism to almost every risk measure and customer choice behavior. In an extensive simulation study, we analyze the impact of our approach on expected utility, conditional value-at-risk (CVaR), and expected value. The results show a superior performance in comparison to risk-neutral approaches from the literature.

Suggested Citation

  • Sebastian Koch & Jochen Gönsch & Michael Hassler & Robert Klein, 2016. "Practical decision rules for risk-averse revenue management using simulation-based optimization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 468-487, December.
  • Handle: RePEc:pal:jorapm:v:15:y:2016:i:6:d:10.1057_s41272-016-0065-x
    DOI: 10.1057/s41272-016-0065-x
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    Cited by:

    1. Schur, Rouven & Gönsch, Jochen & Hassler, Michael, 2019. "Time-consistent, risk-averse dynamic pricing," European Journal of Operational Research, Elsevier, vol. 277(2), pages 587-603.
    2. Gönsch, Jochen, 2017. "A survey on risk-averse and robust revenue management," European Journal of Operational Research, Elsevier, vol. 263(2), pages 337-348.
    3. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    4. Jochen Gönsch & Michael Hassler & Rouven Schur, 2018. "Optimizing conditional value-at-risk in dynamic pricing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 711-750, July.

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