Location of Airbnb and hotels: the spatial distribution and relationships

Abstract

Purpose The purpose of this study is to compare the spatial distribution of Airbnb and hotels in London and examine the relationship between demographic, socioeconomic and environmental factors and the supply of these two types of lodging supply. Design/methodology/approach Local information of Airbnb listings in London was collected through Insideairbnb.com. Gathered data were examined using geo-spatial auto-correlation analysis and spatial econometric models. Findings The results indicate that Airbnb predominates in the areas around popular tourist attractions and the peripheral areas of the city, while in the downtown area Airbnb and hotels are in the state of coexistence. The mono-centric model and the agglomeration model could be extended to the context of peer-to-peer accommodation. The location of Airbnb and traditional hotels capitalizes on different factors. Research limitations/implications The study is based on secondary data due to data availability. And, it is based on the case of London, so the findings may not reflect the situation of small cities and rural destinations. Practical implications This study not only gives suggestions for local councils to regulate the location of hotels and Airbnb but also provides professional landlords with reference to choosing Airbnb location. Originality/value This study extends the hotel location theoretical models into the context of Airbnb and sheds lights on the distinction between these two business models in terms of location factors.

Sharing economy in the new hospitality: consumer perspective

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Evaluating the Health of Urban Human Settlements

“…Spatial autocorrelation analysis: Spatial autocorrelation methods can be roughly divided into two categories according to their functions: global autocorrelation and local autocorrelation [42][43][44]. Global spatial autocorrelation describes the spatial characteristics of a phenomenon in the whole region and measures the degree of agglomeration in areas with similar human settlements.…”

Images’ features and Airbnb listing price: the mediation effect of visual aesthetic perception

“…com, a publicly accessible website that aligns with the principles of information openness. Furthermore, the study finds little difference between Insideairbnb and AirDNA (La et al, 2022). To accurately portray the Airbnb supply situation, data on the cumulative number of Airbnb listings and images related to Airbnb in the Beijing market were collected, spanning from March 2011 to October 2020.…”

“…Airbnb, a brand in the sharing accommodation industry, is gaining increasing consumer attention (La et al , 2022). It offers a range of experiences and pricing options, which are crucial for consumer decision-making and the overall success of the industry (Zhao et al , 2023).…”