Abstract:
Airbnb, an influential sharing economy platform, profoundly impacts temporary accommodation in the tourism industry. It has been developing rapidly in recent years until the COVID-19 pandemic struck the global tourism and the Airbnb markets heavily. In this dissertation, we investigate the determinants of Airbnb listing prices in Barcelona, London and NYC before (in 2019) and during the pandemic (in 2020). We explore the temporal and spatial patterns of the listings’ prices in both years and verify the significant drivers for Airbnb prices across these cities.
This study uses the annual average of Airbnb listings prices as a dependent variable and a set of property characteristics directly linked to each property, some socio-economic variables from the censuses and point of interest data corresponding to neighbourhoods of the studied properties independent variables. We employ expletory data analysis, correlations tests, and global hedonic price models geographically weighted regression models to analyse the patterns of price-related variables.
This research identifies a number of interesting relationships between price, properties’ characteristics and location factors. It also points out and explains differences between 2019 and 2020 data and spatial and temporal patterns occurring in the three studied cities centre.