The Impact of Spatial and Locational Characteristics on Airbnb Prices in London

Abstract

This research delves into the intricate relationship between spatial and locational attributes and Airbnb pricing in London. Utilizing data encompassing Airbnb listings in London collected over one year concluding on December 10, 2022, and employing advanced geospatial statistical techniques, including a geographically weighted regression (GWR) model equipped with ten select explanatory variables, this study reveals multifaceted spatial patterns underlying Airbnb pricing. The study underscores the paramount significance of dissecting the multifaceted determinants of Airbnb pricing, encompassing property characteristics, location-specific variables, host-related attributes, and customer feedback. Through empirical analyses, this research illuminates pronounced spatial heterogeneity within Airbnb pricing, with notable variations discerned across different room types. Interpretation of model coefficients reveals the multifaceted influence of factors, such as proximity to subway stations, volume of customer reviews, and specific scores, on pricing dynamics. Additionally, the GWR model exposes significant spatial variations in the impact of location and neighborhood-related variables on pricing, with particularly marked effects in the realms of entire homes and private rooms. This study aims to illustrate the intricate interplay between spatial and locational characteristics and Airbnb pricing dynamics, offering invaluable insights for researchers and industry practitioners.