Traditionally, revenue management models aim at a maximization of expected revenue, i.e. a risk-neutral decision-maker is assumed. During the last few years, however, the consideration of revenue risk has gained more and more attention. By failing to suggest mechanisms for reducing unfavorable revenue levels, traditional risk-neutral capacity control models fall short of meeting the needs of a risk-averse planner. This is why this book revises the well-known capacity control problem in revenue management from the perspective of a risk-averse decision-maker. Modelling an expected utility maximizing decision maker, the problem is formulated as a risk-sensitive Markov decision process. Special emphasis is put on the existence of structured optimal policies. Numerical examples illustrate the results.

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