Airbnb in tourist cities: comparing spatial patterns of hotels and peer-to-peer accommodation (1606.07138v3)

Abstract: In recent years, what has become known as collaborative consumption has undergone rapid expansion through peer-to-peer (P2P) platforms. In the field of tourism, a particularly notable example is that of Airbnb. This article analyses the spatial patterns of Airbnb in Barcelona and compares them with hotels and sightseeing spots. New sources of data, such as Airbnb listings and geolocated photographs are used. Analysis of bivariate spatial autocorrelation reveals a close spatial relationship between Airbnb and hotels, with a marked centre-periphery pattern, although Airbnb predominates around the main hotel axis and hotels predominate in some peripheral areas of the city. Another interesting finding is that Airbnb capitalises more on the advantages of proximity to the main tourist attractions of the city than does the hotel sector. Finally, it was possible to detect those parts of the city that have seen the greatest increase in pressure from tourism related to Airbnb's recent expansion.

• The paper reveals that Airbnb exhibits a distinct center-periphery pattern in Barcelona, with listings concentrated in central areas compared to clustered hotels.
• The paper demonstrates that Airbnb's spatial autocorrelation is stronger than that of hotels, as shown by analyses using Moran’s I and LISA.
• The paper highlights that Airbnb listings are positioned closer to major tourist attractions, intensifying tourism pressure in traditional residential neighborhoods.

Spatial Patterns of Airbnb and Hotel Accommodations in Tourist Cities: A Comparative Analysis

The paper "Airbnb in tourist cities: comparing spatial patterns of hotels and peer-to-peer accommodation" provides a thorough investigation into the spatial distribution of Airbnb accommodations in comparison with traditional hotels, focusing on the city of Barcelona. The authors utilize new sources of geolocated Big Data to analyze spatial patterns, revealing the complexities introduced by Airbnb in urban tourism ecosystems.

Methodology and Data

The paper employs geolocated data from the Inside Airbnb initiative and hotel records from the Catalonia Tourism Registry. By leveraging Geographic Information Systems (GIS) and spatial statistics, the authors assess distribution patterns using tools like Moran’s I and Local Indicators of Spatial Association (LISA). These tools enable a fine-grained analysis of the spatial relationships between Airbnb accommodations, hotels, and tourist attractions.

Key Findings

1. Center-Periphery Distribution: The data indicates a marked center-periphery pattern for Airbnb listings, with high concentrations in Barcelona's central districts. Airbnb listings cover broader areas compared to the focused hotel clusters often situated along key tourist axes like Ramblas-Paseo de Gracia.
2. Spatial Autocorrelation: Airbnb accommodations exhibit stronger spatial autocorrelation than hotels, highlighting their regular distribution pattern. Moreover, the bivariate spatial analyses demonstrate a close spatial relationship between the locations of Airbnb and hotel accommodations.
3. Tourist Attraction Proximity: Airbnb listings are more strategically located near major tourist attractions than hotels, as identified through the analysis of geolocated photographs on the Panoramio platform.
4. Tourism Pressure: The paper underscores that Airbnb increases tourist pressure in residential areas that traditionally lack hotel infrastructure. This contributes to the economic and social stress on these neighborhoods, potentially exacerbating issues such as rising rents and gentrification.

Implications

The findings illustrate significant implications for urban planning and policy-making. Airbnb's expansion into residential areas can intensify conflicts arising from increased tourism, potentially disrupting local communities. Policymakers must consider these spatial dynamics when crafting regulations to balance the economic benefits of tourism with the socio-cultural sustainability of urban centers.

Theoretical and Practical Contributions

From a theoretical perspective, the paper enriches the discourse on the sharing economy's impact on urban spaces, providing empirical evidence of Airbnb's differential spatial patterns compared to hotels. Practically, the paper suggests a need for tailored regulatory frameworks to manage the distinct impacts of P2P accommodations in tourist cities effectively.

Future Directions

Continued exploration into the spatial dynamics of accommodation types in other urban contexts is warranted. Further studies could integrate more comprehensive datasets, including real-time analytics, to better understand temporal variations and long-term trends. Additionally, comparative analyses of multiple cities could provide broader insights into global patterns of P2P accommodation growth.

This paper is a vital contribution to the field, offering an intricate view of how digital platforms reshape tourism landscapes, with implications for urban development and governance in the era of collaborative consumption.