Effects of Airbnb hosts’ quality and quantity attributes on reservation performance: The case of Hong Kong

Abstract

This study examined the effects of hosts’ quality attributes on the reservation performance of their listings. It also determined whether the number of listings a host manages impacts the quality of the experience, which in turn affects reservations. We used the InsideAirbnb database to collect publicly available information about hosts and listings on Airbnb.com in Hong Kong in 2018. Our sample included 2,284 hosts in Hong Kong. We used a regression model to examine the effects of quality and quantity attributes on the reservation performance of these Airbnb listings. We found that the hosts’ quality attributes, excluding the membership and local host attributes, positively influenced the number of reservations a host received. The results have implications for business development on sharing economy platforms and for hosts who wish to improve their trade.