The goal of the first part of this thesis is to obtain a high-level theoretical understanding of how an alliance can be managed such that its resources are used in an optimal manner. We propose a pricing mechanism to manage the interactions of carriers, through the allocation of alliance resources and profits, in a manner that encourages individual carriers to make decisions that are optimal for the alliance. Our methodology is based on modeling carrier behavior as linear programs, which are incorporated into a mechanism that manages carrier interactions by appropriately setting resource prices. After introducing two distinct behavioral models, the performance of the mechanism using each model is analyzed for its ability to ensure alliance optimal behavior is attained. We find that the behavioral model selected can significantly impact the characteristics of allocations obtained using the mechanism.
In the second part of the thesis, we seek to establish practical insights regarding how the characteristics of potential partners impact the benefit that can be gained by collaborating with these partners. Computational experiments are conducted to evaluate the impact of network size, fleet capacity, demand distribution, and network compatibility on the benefit associated with collaborating. A comprehensive study for simulated two and three-carrier alliances establishes general insights regarding the compatibility of carriers with varying network sizes and fleet capacities. The impact of increasing hub-to-hub connectivity between partnering carriers is then investigated, followed by a study of the effect of market overlap on alliance success. Finally, a real-world cargo alliance is analyzed.
In the third and final part of this thesis, we develop new approaches for determining and inducing fair profit allocations in alliances, providing alternatives to traditional approaches which equate minimum acceptance requirements and satisfaction. The mechanism established in the first part of the thesis is adapted to more precisely control the profit allocations obtained, in particular so that an allocation as close to some predetermined fair" allocation is obtained. Several measures of fairness are proposed and implemented, and their performance analyzed for each of the behavioral models discussed in the first part of the thesis.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/16290 |
| Date | 05 July 2007 |
| Creators | Houghtalen, Lori Marie |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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