The rising number of homes and apartments rented out through Airbnb and similar peer-to-peer accommodation platforms cause concerns about the impact of such activity on the tourism sector and property market. To date, spatial analysis on peer-to-peer rental activity has been usually limited in scope to individual large cities. In this study, we take into account the whole territory of Spain, with special attention given to cities and regions with high tourist activity. We use a dataset of about 250 thousand Airbnb listings in Spain obtained from the Airbnb webpage, aggregate the numbers of these offers in 8124 municipalities and 79 tourist areas/sites, measure their concentration, spatial autocorrelation, and develop regression models to find the determinants of Airbnb rentals’ distribution. We conclude that apart from largest cities, Airbnb is active in holiday destinations of Spain, where it often serves as an intermediary for the rental of second or investment homes and apartments. The location of Airbnb listings is mostly determined by the supply of empty or secondary dwellings, distribution of traditional tourism accommodation, coastal location, and the level of internationalization of tourism demand.

inStytut geOgrafii i przeStrzennegO zagOSpOdarOWania pOlSka akademia nauk www.igipz.pan.pl kOmiSja ObSzaróW WiejSkich pOlSkie tOWarzyStWO geOgraficzne www.ptgeo.org.pl

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World Tourism Organization (UNWTO) is the major source of internationally comparable data on tourism. However, UNWTO data has two drawbacks: it focuses on international trips and ignores differences between regions within individual countries. Alternative sources of big data are increasingly used to enhance tourism statistics. In this paper, we combine traditional information sources with gridded population dataset and Airbnb data to address the limitations of UNWTO statistics. We produce a map of world tourism destinations measured by the number of tourism visits and tourism expenditure in 2019, before the COVID-19 pandemic. We then identify hot spots of tourism and compare the level of spatial concentration of tourism to that of global population and economy. The results illustrate how supply and demand shape the global distribution of tourism, highlight the dominance of domestic travels in global tourism mobility and may help planning tourism policy in the face of current global challenges.

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