This study investigates the revenue performance of choice-based revenue management (RM) systems in various business environments. Previous research conducted using simulated data suggests that incremental revenue gains of up to 15% are to be expected when choice-based RM techniques are employed. In addition, despite the novelty of these techniques, the implementation of choice-based RM systems is considered to be feasible at large global corporations. The revenue potential and the ease of execution associated with the choice-based methods are examined in the context of a large hotel chain. Customer-centric data which includes transaction and time of booking availability information is collected for five hotel properties located in the continental US. The customer preference for hotel products and their attributes is determined using discrete choice and other ad hoc models of demand. Optimization techniques that account for the customer purchasing behavior are employed to compute the capacity control policies the hotel operator should follow to maximize its revenues. Results indicate that collecting customer-centric data from today s RM systems is a time-consuming task. In the environment in which the study hotels operate, the choice-based RM systems report incremental revenue gains that are dependent on how the purchasing behavior models are formulated. In capacity constrained regimes that are the focus of RM, revenue gains of up to 2% are typically noted. In controlled environments in which the customer purchasing behavior can be better asserted, the incremental revenue gains range between 1% and 14%. These findings suggest that the execution of the choice-based RM, while feasible, needs to be preceded by the implementation of efficient and, most likely, expensive data collection procedures. The incremental revenue gains, consistent with those reported in the literature, indicate that RM users can substantially benefit from the use of the choice-based RM.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/24739 |
| Date | 20 May 2008 |
| Creators | Bodea, Tudor Dan |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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