Understanding Airbnb spatial distribution in a southern European city: The case of Barcelona. (February 2020)

• Record Type: Journal Article
• Authors: Lagonigro, Raymond; Martori, Joan Carles; Apparicio, Philippe
• Is Part Of: Applied geography. Volume 115(2020)
• Publication Date: 2020-02
• Subjects: Airbnb -- Spatial analysis -- Geographic weighted regression -- Tourism impact -- Neighborhood transformation; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2019.102136
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: The recent proliferation of private tourist accommodations on what has been known as sharing economy has induced new models on urban tourism and on the use of traditional housing. Urban tourism pressure has caused many transformation processes with important impacts in neighborhoods with high tourist interest. In our work, we analyze the spatial distribution of Airbnb accommodations in the city of Barcelona and we explore the factors associated with the situation of Airbnb rentals in relation to the socioeconomic characteristics of the population and tourism indicators. In order to model spatial non-stationarity, a Geographically Weighted Regression (GWR) model has been used. The GWR model proposed in our study provides local insight to gain understanding of how socioeconomic factors explain the variation of the ratio of Airbnb short-term rentals in the different neighborhoods of the city and reveals dissimilar correlations in several areas. The main factors explaining the variation on the ratio of Airbnb rentals over the total number of households are family income, education level, and dwelling size, with opposed spatial patterns of positive and negative significant coefficients at a local scale. Highlights: Spatial models for Airbnb accommodations and population socioeconomic characteristics. Framework to assess urban planning policies related to private renting. Family income, education level, and dwelling size are the main factors explaining the variation on the proportion of Airbnb rentals, with uneven relationships in different neighborhoods of the city.