Analyzing and predicting the spatial penetration of Airbnb in U.S. cities

EPJ Data Science

Giovanni Quattrone¹  Daniele Quercia²  Licia Capra³  Mirco Musolesi³  Andrew Greatorex³ 

[1] Middlesex University;Nokia Bell Labs;University College London;

关键词: Quantitative analysis;    Spatial data mining;    Sharing economy;    Airbnb;   

DOI  :  10.1140/epjds/s13688-018-0156-6

来源: DOAJ

【 摘 要 】

Abstract In the hospitality industry, the room and apartment sharing platform of Airbnb has been accused of unfair competition. Detractors have pointed out the chronic lack of proper legislation. Unfortunately, there is little quantitative evidence about Airbnb’s spatial penetration upon which to base such a legislation. In this study, we analyze Airbnb’s spatial distribution in eight U.S. urban areas, in relation to both geographic, socio-demographic, and economic information. We find that, despite being very different in terms of population composition, size, and wealth, all eight cities exhibit the same pattern: that is, areas of high Airbnb presence are those occupied by the “talented and creative” classes, and those that are close to city centers. This result is consistent so much so that the accuracy of predicting Airbnb’s spatial penetration is as high as 0.725.

【 授权许可】

Unknown