Gelir yönetimi modellerinde ortalama-varyans yaklaşımı ile riskten korunma yöntemleri

Revenue management problems have become one of the mostly studied problems in the literature and has drawn considerable attention from any field of research and application. This is mainly due to the fact that the problem of allocating a fixed capacity can be encountered in many fields, some of which are hotel industry, healthcare operations and financial services. The randomness in demand creates uncertainty to the decision makers. Most of the related literature assumes that the decision maker is risk-neutral and aims to maximize the expected profit. However, in real life, most individuals may be risk-sensitive in a sense that they tend to avoid risk in exchange for a reduction in the return. Moreover, a common assumption in the related literature is independence of the demand variables; most studies do not account for the case where the demands are related. Nevertheless, it is known that in most cases, the demand variables tend to depend on each other. In this thesis, we present the results for both independent and dependent demand cases and follow a mean-variance approach to the revenue management problem to account for the risk-sensitivity of the decision maker. Furthermore, we incorporate hedging into the model by assuming that there is a correlation between the demand and the financial market, for which there is strong statistical evidence. The risk is hedged by investing in a portfolio of financial instruments. We determine the optimal portfolio and the optimal protection level simultaneously by solving the mean-variance objective function. While describing demand structure, we account for both the perfect and partial dependency cases with the financial market. Finally, we perform simulation studies to illustrate our findings. Numerical illustrations are presented to show the relationship between the risk aversion level and the optimal order quantity as well as to quantify the effect of the mean-variance approach and hedging on the variance of the revenue management cash flow. Keywords : Revenue management model, mean-variance approach, risk management