Dynamic pricing and revenues of Airbnb listings: Estimating heterogeneous causal effects |
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| Affiliation: | 1. Department of Economics (Ca’ Foscari University of Venice), Italy;2. Department of Applied Economics (University of the Balearic Islands), Spain;1. Department of Psychology, Henan University, China;2. School of Hospitality and Tourism, Auckland University of Technology, New Zealand;3. Hospitality and Tourism Institute, Duy Tan University, Viet Nam;4. Faculty of Social Sciences and Humanities, Duy Tan University, Viet Nam;1. Howard Feiertag Department of Hospitality and Tourism Management, Pamplin College of Business, Virginia Polytechnic Institute and State University, 295 West Campus Drive, Blacksburg, VA, 24061, United States;2. Chaplin School of Hospitality & Tourism Management, Florida International University, 3000 Northeast 151st Street, North Miami, FL, 33181, United States;3. University of Nevada, Las Vegas William F. Harrah College of Hotel Administration, 4505 S. Maryland Parkway, Las Vegas, NV, 89119, United States;1. School of Tourism Management, Sun Yat-sen University, Guangzhou 510275, China;2. School of Business, Guizhou University of Finance and Economics, Guiyang 550025, China;3. School of Hotel, Restaurant and Tourism Management, College of Hospitality, Retail and Sport Management, University of South Carolina, Columbia, SC, 29208, USA;1. Department of Marketing, Events and Tourism, University of Greenwich, London SE10 9LS, United Kingdom;2. School of Hospitality and Tourism, Auckland University of Technology, WH Building, 49 Wellesley Street East, Auckland 1010, New Zealand;1. University of Edinburgh Business School, 29 Buccleuch Place, Edinburgh, Scotland, United Kingdom;2. School of Hospitality & Tourism Management, University of South Florida, FL, 34243, USA;3. Dedman College of Hospitality, Florida State University, Tallahassee, FL, USA;1. Villanova School of Business, Villanova University, 800 E. Lancaster Ave., Villanova, PA 19085, USA;2. Montpellier Business School, Avenue des Moulins 34080, Montpellier, France;3. Department of Economics, Lancaster University Management School, Lancaster LA1 4YX, United Kingdom;4. Hadelman Family Research Fellow, Isenberg School of Management, University of Massachusetts-Amherst, USA |
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| Abstract: | This paper investigates the extent to which the implementation of intertemporal price discrimination affects Airbnb listings’ revenue. We found that on average, a price surge (i.e., increasing the price as we approach the date of service consumption) has an adverse effect on revenue. However, the magnitude of such effect exhibits significant heterogeneity among listings. Through the application of generalized random forests, a causal machine learning technique, we identify exacerbating and moderating treatment modifiers and shed light on the listing dimensions that cause price surges to be particularly detrimental for hosts’ revenues. |
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| Keywords: | Airbnb Dynamic pricing Heterogeneous causal effects Generalized random forest |
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