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Estimating flight-level price elasticities using online airline data: A first step toward integrating pricing,demand, and revenue optimization
Institution:1. Georgia Institute of Technology, School of Civil and Environmental Engineering, 790 Atlantic Drive, Atlanta, GA 30332-0355, United States;2. Georgia Institute of Technology, Ernest Scheller Jr. College of Business, 800 West Peachtree NW, Atlanta, GA 30308, United States;3. National Bureau of Economic Research, 1050 Massachusetts Ave., Cambridge, MA 02138, United States;1. State Key Lab of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;2. Tianjin Key Laboratory of Equipment Design and Manufacturing Technology, School of Mechanical Engineering, Tianjin University, Tianjin 300072, China
Abstract:We estimate flight-level price elasticities using a database of online prices and seat map displays. In contrast to market-level and route-level elasticities reported in the literature, flight-level elasticities can forecast responses in demand due to day-to-day price fluctuations. Knowing how elasticities vary by flight and booking characteristics and in response to competitors’ pricing actions allows airlines to design better promotions. It also allows policy makers the ability to evaluate the impacts of proposed tax increases or time-of-day congestion pricing policies. Our elasticity results show how airlines can design optimal promotions by considering not only which departure dates should be targeted, but also which days of the week customers should be allowed to purchase. Additionally, we show how elasticities can be used by carriers to strategically match a subset of their competitors’ sale fares. Methodologically, we use an approach that corrects for price endogeneity; failure to do so results in biased estimates and incorrect pricing recommendations. Using an instrumental variable approach to address this problem we find a set of valid instruments that can be used in future studies of air travel demand. We conclude by describing how our approach contributes to the literature, by offering an approach to estimate flight-level demand elasticities that the research community needs as an input to more advanced optimization models that integrate demand forecasting, price optimization, and revenue optimization models.
Keywords:Air travel demand  Price elasticity  Price endogeneity
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