The Price of Short-Term Housing: A Study of Airbnb on 26 Regions in the United States

Abstract

This study investigates the influence of customer review content and other attributes on Airbnb listing prices, using data from listings across 26 U.S. regions. By integrating sentiment analysis and topic modeling with hedonic and quantile regression models, this paper examines the significant role of electronic word-of-mouth in the short-term rental market, by studying how review sentiments and topics affect pricing strategies. The findings reveal that negative reviews have twice the impact on listing prices as positive reviews; and fourfold for lower-priced listings. Moreover, the results of topic modeling show that both positive and negative reviews related to facilities and location have a larger impact on listing prices. Additionally, the study looks at how the distance of listings from the city center and the timing of reviews affect pricing adjustments. The influence of reviews diminishes for listings located farther from the city center, indicating that Airbnb listing prices near the city center are more sensitive to changes in price determinants. The study also uncovers the existence of a lag effect in how reviews impact prices, showing that Airbnb hosts may not adjust prices as quickly as hotel owners. Overall, the study enriches existing literature by taking into account the review content and type of customer reviews, offering a more comprehensive understanding of short-term rental pricing.