Jet Fuel Hedging and Modern Financial Theory in the U.S. Airline Industry

To counter the problem of the volatility of jet fuel prices within the United States, many financial managers of U.S. airlines use hedging as a financial tool to mitigate the risk of exposure to market price volatility. However, their efforts often lead to financial distress for their airlines. The purpose of this qualitative grounded theory study was to explore U.S. airline managers\u27 use of financial hedging to reduce the risk of exposure from the volatility of jet fuel prices. The conceptual framework was Simkowitz\u27s theory of modern finance, which concerns debt policy, dividend policy, and investment policy as they relate to financial decision making by upper management. The research questions addressed when, why, and how U.S. airline financial managers would consider the use of hedging as a financial tool to mitigate the risk in the purchase of jet fuel at times of lower jet fuel prices. Interviews with a purposive sample of 20 U.S. airline financial managers provided data for analysis and theory development of jet fuel hedging utilization in the U.S. airline industry. Data analysis using the constant comparative method enabled the development of a theory of jet fuel hedging utilization. Participants reported using over-the-counter derivatives purchasing strategies as a form of hedging to protect their airlines against spikes in jet fuel prices on the open market. Using study findings, managers may be able to reduce jet fuel operating costs in the U.S. airline industry. Implications for positive social change include potentially higher profits and more jobs as well as lower consumer prices

Network Revenue Management under Competition within Strategic Airline Alliances

Airlines often cooperate with partners within strategic alliances to offer their customers itineraries beyond their own networks. However, despite the cooperation, the alliance members often remain competitors on other routes and compete for customers. This thesis takes into account the competition between two alliance partners and models it in a linear program. An algorithm is developed to compute optimal capacity allocations in pure Nash equilibria based on the model. For cases, in which a Nash equilibrium does not exist or cannot be found within a pre-defined time, a heuristic approach is described to compute an approximate Nash equilibrium. Computational studies show the applicability of the approaches in real-sized airline networks. Finally, suggestions for future research are made