Purpose
The purpose of this paper is twofold: to explore the distribution and pricing characteristics of Airbnb listings in Malta as at May 2019; and to develop a pricing model to determine the factors which have a statistically significant impact on price per night of listings.
Design/methodology/approach
A descriptive analysis of location and pricing of listings was undertaken via heat mapping techniques. A cross-sectional ordinary least squares (OLS) regression was run to determine the statistically significant variables.
Findings
Listings tend to cluster around not only in traditional tourist towns but also in rural areas which opens up new opportunities for tourist lodging. The Southern Harbour region was found to be the most expensive with the Gozo and Comino region being the least expensive. The coefficients of the pricing regression model were in line with a priori expectations.
Research limitations/implications
The study is based on a cross-sectional data set and thus fails to account for seasonal changes in prices. Likewise, the use of an OLS regression without incorporating quantile regression methods or spatial autocorrelation econometric techniques is another limitation of this study.
Originality/value
The paper is one of the few related to sharing economy rental platforms, particularly in Malta. It is also the first study in Malta to develop a comprehensive pricing model to determine what affects a listing’s price per night and the extent to which certain factors do so.
