{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/27127"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/27127","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Essays in Revenue Management and Dynamic Pricing","abstract":"In this dissertation, I study two topics in the context of revenue management. The First topic involves building a mathematical model to analyze the competition between many retailers who can change the price of their respective products in real time. I develop a game-theoretic model for the dynamic price competition where each retailer's objective is to maximize its own expected total revenue. I use the Nash equilibrium to predict market equilibrium and provide managerial insights into how each retailer should take into account its competitors' behavior when setting the price. The second topic involves working with Amtrak, the national railroad passenger corporation, to develop a revenue management model. The revenue management department of Amtrak provides the sales data of Auto Train, a service of Amtrak that allows passengers to bring their vehicles on the train. I analyze the demand structure from sales data and build a mathematical model to describe the sales process for Auto Train. I further develop an algorithm to calculate the optimal pricing strategy that yields the maximum revenue. Because of the distinctive service provided by Auto Train, my findings make important contribution to the revenue management literature.","abstract_html":"In this dissertation, I study two topics in the context of revenue management. The First topic involves building a mathematical model to analyze the competition between many retailers who can change the price of their respective products in real time. I develop a game-theoretic model for the dynamic price competition where each retailer's objective is to maximize its own expected total revenue. I use the Nash equilibrium to predict market equilibrium and provide managerial insights into how each retailer should take into account its competitors' behavior when setting the price. The second topic involves working with Amtrak, the national railroad passenger corporation, to develop a revenue management model. The revenue management department of Amtrak provides the sales data of Auto Train, a service of Amtrak that allows passengers to bring their vehicles on the train. I analyze the demand structure from sales data and build a mathematical model to describe the sales process for Auto Train. I further develop an algorithm to calculate the optimal pricing strategy that yields the maximum revenue. Because of the distinctive service provided by Auto Train, my findings make important contribution to the revenue management literature.","abstract_has_math":false,"creators":["Yousef-Sibdari, Soheil"],"institution":"Virginia Tech","degree_name":"Ph. 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