Research questions

This project investigates the factors associated with the emergence and survival of Airbnb listings in Vienna. This analysis enables a spatial and temporal examination of the relationships between gentrification, Airbnb density, and residential segregation. Second, the project examines urban renewal projects as potential catalysts for the spatial expansion of Airbnb. Third, it explores how Airbnb listings contribute to the construction of neighbourhood images, how “off-the-beaten-track” tourist spaces evolve over time in Vienna, and the extent to which these host-generated neighbourhood narratives align with the representations promoted by the city’s tourism initiatives.

Methods/Research design

The project constructs a panel dataset combining Airbnb listing data, grid-level socio-spatial variables, and service densities. Spatiotemporal econometric models are applied to analyse these relationships. For the second objective, the dataset is extended with geocoded data on urban renewal projects. A DiD approach is used to estimate the causal effects of these projects on Airbnb density, prices, and ratings. For the third objective, host descriptions are analysed using quantitative text-analysis methods, including word-frequency and sentiment measures. LDA and DTM are used to identify dominant topics and trace their evolution over time.

Results/dissemination

This project contributes to existing knowledge on Vienna across the three key dimensions outlined above. The findings may also provide a better understanding of the temporal relationship between gentrification and the emergence of Airbnb listings. The outputs are intended to reach audiences beyond academia. Based on the findings, a set of policy recommendations will also be developed, with particular reference to Vienna’s current regulation of Airbnb and other short-term rentals. Exposure to Airbnb activity will be visualised through an open and interactive platform hosted on the ISR website. The platform will allow residents to access useful information about short-term rental dynamics in their immediate neighbourhoods and the associated socio-spatial changes.