In this study, the seat inventory control problem is considered for airline networks from the
perspective of a risk-averse decision maker. In the revenue management literature, it is generally
assumed that the decision makers are risk-neutral. Therefore, the expected revenue is
maximized without taking the variability or any other risk factor into account. On the other
hand, risk-sensitive approach provides us with more information about the behavior of the
revenue. The risk measure we consider in this study is the probability that revenue is less
than a predetermined threshold level. In the risk-neutral cases, while the expected revenue
is maximized, the probability of revenue being less than such a predetermined level might
be high. We propose three mathematical models to incorporate the risk measure under consideration.
The optimal allocations obtained by these models are numerically evaluated in
simulation studies for example problems. Expected revenue, coefficient of variation, load factor
and probability of the poor performance are the performance measures in the simulation
studies. According to the results of these simulations, it shown that the proposed models can
decrease the variability of the revenue considerably. In other words, the probability of revenue
being less than the threshold level is decreased. Moreover, expected revenue can be increased
in some scenarios by using the proposed models. The approach considered in this thesis is especially proposed for small scale airlines because risk of obtaining revenue less than the
threshold level is more for this type of airlines as compared to large scale airlines.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12610711/index.pdf |
| Date | 01 July 2009 |
| Creators | Terciyanli, Erman |
| Contributors | Avsar, Zeynep Muge |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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