The Federal Aviation Administration uses Air Traffic Management Initiatives (TMIs) to mitigate the consequences of aviation system capacity shortfalls, for example by delaying aircraft on the ground at their origin airports. In order to make more efficient use of National Airspace (NAS) resources, reduce delay costs, and increase the flexibility of NAS users to meet their operational needs, tremendous efforts have been made to design TMIs in a manner to encourage cooperation between the FAA and airlines. Airlines are offered opportunities to make choices such as cancelling flights and increasing delays on some flights while decreasing delays on others. However, there has been little study of airlines’ resulting behavior. In this dissertation, we analyze choices made by airlines in response to TMIs and attempt to infer from these key features of airlines’ preference structures. Two econometric models are specified and estimated. The first model focuses on airlines’ flight cancellation decisions, and the second model examines airline requests to simultaneously re-assign arrival slots and cancel flights using Slot Credit Substitution (SCS) messages.

The cancellation model captures how airlines value delays of the subject flight itself and potential delay savings of other flights in making a flight cancellation decision. Aircraft size, along with segment frequency and load factor, are all significant factors in cancellation decisions; larger, fuller, and less frequent flights are less likely to be cancelled. Somewhat surprisingly, a higher average fare is found to increase cancellation probability. Hub-bound flights are found more likely to be cancelled than spoke-bound flights. The model also confirms airlines’ hedging behavior in response to TMIs by preferentially cancelling short-haul flights. In addition, a piece wise linear specification of the utility function confirms that the delay impact is non-linear. Individual airline model reveals some consistent behavior as well as some differences in how different factors enter into cancellation decisions.

The SCS model captures airlines’ tradeoff behavior in dealing with flight cancellations and delays. It confirms that cancelling flights decreases airlines’ utility while reducing delays increases the utility. Moreover, airlines are sensitive to the aircraft 2 size and average fare of flights in performing these actions. In this model, however, average fare has the expected sign. The model estimates that airlines are willing to cancel a flight if the cancellation can reduce around 100 minutes of delays on their other flights that are in the ground delay program.