Quality signals on Airbnb: A hedonic regression approach

This study aims at identifying guests' willingness to pay for characteristics of listings on Airbnb, putting a particular emphasis on trust-building information provided by the platform. In order to do so, a hedonic regression model is applied to an extensive dataset that was gathered in 2017 from Airbnb's website and encompasses listings from seven major German cities, namely Berlin, Munich, Hamburg, Cologne, Dresden, Stuttgart and Frankfurt am Main. Our results regarding tangible characteristics are mostly in line with expectations: Additional space and certain amenities increase the value of a listing. The same holds true for an accommodation's distance to the city center, although we find proof for a non-linear relationship. Results for trust-building factors on the other hand are mixed. While favorable review scores and membership duration have a positive effect on prices, we cannot establish such a relationship for 'superhost' and 'verified ID' badges. In contrast to other studies, which are, however, focused on the US, we cannot find price differences linked to hosts' gender or ethnicity. Using an extended data set that encompasses listings from 2007 to 2008, we furthermore construct hedonic price indices for all seven cities, which suggest supply shifts due to regulatory pressure.