Dissertation
Optimal and Approximate Revenue Management Controls in the Hotel Industry
Doctor of Philosophy (PhD), Washington State University
01/2018
Handle:
https://hdl.handle.net/2376/107558
Abstract
The extant literature on hotel revenue management predominantly focuses on larger franchised hotel properties, and little consideration has been given to the revenue management practices at smaller hotel properties. In this dissertation, by considering both smaller and larger hotel properties, we present optimal and approximate revenue management controls in the hotel industry.
Chapter Two first develops a simple adaptive price optimization algorithm that is suitable to smaller hotel properties. As opposed to conducting simulation study, we design an Excel VBA application that executes the algorithm in its entirety and implement the application in an actual resort over a 4-month test period. The actual implementation of the algorithm represents an important step toward our ability to evaluate its revenue impact. Implementation result shows that the adaptive pricing algorithm generates a strong positive revenue impact on the test property. Thus, our adaptive approach has potential to be an invaluable revenue management tool for smaller hotel properties with very limited resource.
In Chapter Three we develop a taxonomy of key factors that either directly or indirectly can influence the prices that a hotel charges at a point in time. We conduct an extensive review and sophisticated summary of hotel revenue management factors related primarily to data analysis and modeling perspectives. The classification system provides valuable insights for future research and implications for application.
In Chapter Four we develop a hotel revenue management optimization method in an environment where each market segment price is optimized via demand elasticity curve ahead of a planning horizon. The key aspect of this method is to simultaneously optimize overbooking limits and inventory allocation levels in the post-price-optimization phase, as opposed to the traditional sequential overbooking first-allocation second approach. We test our proposed method against the traditional sequential approach using a simulated hotel revenue management system that has all the functionalities of a real-world system. The simulation results show that our method outperforms the sequential method by an average of 20% on nightly net revenue. The achieved speed is adequately fast enough to re-run the algorithm many times during a day.
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Details
- Title
- Optimal and Approximate Revenue Management Controls in the Hotel Industry
- Creators
- Aishajiang Aizezikali
- Contributors
- Timothy K Baker (Advisor)Robert J Harrington (Committee Member)Charles L Munson (Committee Member)Stergios B Fotopoulos (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Carson College of Business
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 154
- Identifiers
- 99900581821501842
- Language
- English
- Resource Type
- Dissertation