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Short-Term Rental Platform in the Urban Tourism Context: A Geographically Weighted Regression (GWR) and a Multiscale GWR (MGWR) Approaches

Shabrina, Z; Buyuklieva, B; Ng, MKM; (2020) Short-Term Rental Platform in the Urban Tourism Context: A Geographically Weighted Regression (GWR) and a Multiscale GWR (MGWR) Approaches. Geographical Analysis 10.1111/gean.12259. (In press). Green open access

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Abstract

This article contributes to advancing the knowledge on the phenomenon of the most popular short‐term rental platforms, Airbnb. By implementing a geographically weighted regression (GWR) and its multiscale form, MGWR, we examine the relationship between Airbnb locations and the core elements of urban tourism including hotels, food and beverages (F&B) venues, as well as access to public transport. This article’s contributions are twofold: methodological and empirical. First, the results show that incorporating localities improve overall model performance. It allows us to account for the nuance of each area of interest as the MGWR performs slightly better than the GWR in the case of spatially sparse data. Second, both models show that Airbnbs collocate with hotels supported by various amenities, but Airbnbs also go beyond traditional hotel zones. This analysis highlights and extends the latter where Airbnb concentrations are those for which there are strong associations with F&B establishments and access to public transports. This suggests that Airbnbs might benefit local businesses outside the reach of major tourist zones. However, there is further work to be done to understand whether the economic benefit to the local economy is worth the associated social costs raised by previous studies.

Type: Article
Title: Short-Term Rental Platform in the Urban Tourism Context: A Geographically Weighted Regression (GWR) and a Multiscale GWR (MGWR) Approaches
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/gean.12259
Publisher version: https://doi.org/10.1111/gean.12259
Language: English
Additional information: © 2020 The Authors. Geographical Analysis published by Wiley Periodicals LLC on behalf of The Ohio State University. © 2020 The Ohio State University. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
URI: https://discovery.ucl.ac.uk/id/eprint/10113405
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