Following the Airlines Deregulation Act of 1978, air carriers have been allowed to select their network configuration, flight schedule, fares, service quality etc. Air carriers are operating with the main goal to maximize their profit resulting in a highly competitive business environment. Thus, there are increasing calls for developing analytical tools that capture the competition among airlines at the system level. This research work introduces a modeling framework for modeling airlines competition at the network level. The model replicates airlines' decisions on developing their network and corresponding flight schedule configuration, and estimates the overall profitability associated with this configuration. A game-theoretic modeling framework is developed. The framework adopts the concept of network equilibrium as the basis for capturing the competition among the air carriers. Each air carrier is assumed to modify its network structure and flight schedule with the goal to maximize its profit until a state of equilibrium is achieved. At equilibrium, it is assumed that no air carrier can improve its profit by unilaterally changing its network structure and/or flight schedule (i.e. entering or exiting from a market or changing number of flights in a market). The problem is formulated as a non-linear mathematical program. Two decomposition-based solution algorithms are developed for this problem. The first algorithm solves a special version of the problem where the constraints on the infrastructure capacity are relaxed. The second algorithm is designed to solve the general problem in which the infrastructure capacity constraints are considered.;A set of experiments are designed to illustrate the different capabilities of the developed modeling framework in capturing the competition pattern under different operation scenarios. These scenarios include air travel demand variation, air carriers' fleet expansion and downsizing, the relaxation of market and airport access restrictions, change in operation cost, infrastructure capacity limitations, congestion pricing, and merging between two air carriers. Two test-bed networks are used to run these experiments. The first network is a hypothetical small network that is used to present the results of the model at a high level of details (i.e. market-based schedule for the competing air carriers). The second network is a representation of the U.S. domestic network. This network is also used to validate the developed model by comparing the model results with the air carriers' published schedule.;The results of these experiments generally show that air carriers with lower cost structures and more resources dominate the competition in most markets. In addition, three main case studies are considered for the U.S. domestic network. The first case study aims at investigating the effect of applying congestion pricing strategies at congested airports. The results prove the importance of considering the network-wide effect of any local pricing strategies. The second case study examines the effect of repealing the Wright Amendment Act in Dallas Love field airport. The results show that canceling this act could significantly affect legacy air carriers with major operation in the DFW region. Finally, a case study that replicates the merging between Delta Airlines and Northwest Airlines is considered. The model shows that a significant increase in the profit can be achieved. It also identifies other air carriers that could be impacted by this merger.
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