Spatial Distribution and Location Characteristics of Airbnb in Seoul, Korea

Donghwan Ki · Sugie Lee

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Sharing Economy and Platforms Housing Market and Economics Housing, Finance, and Neoliberalism

Abstract

The popularity of the sharing economy, including organizations such as Airbnb and Uber, has increased rapidly over the last few years. Regarding Airbnb, several studies have demonstrated potential problems related to it, such as rising housing costs and worsening residential environments. Despite its popularity and possibility of problems, however, the locational characteristics of Airbnb have not been thoroughly examined in the urban planning and public policy fields. Therefore, this study analyzed the locational characteristics of Airbnb in Seoul and identified potential problems in urban planning. First, we analyzed an operation status of Airbnb in terms of the commercial host. After that, we identified spatial distributions of Airbnb and examined influential factors that affected the locational characteristics of Airbnb using a negative binomial regression model. The results of this study are as follows. First, a considerable number of units were operated by commercial hosts, in contrast to the original concept of Airbnb as being part of the sharing economy. This finding indicates that there would be a potential conflict between Airbnb businesses and housing policy in urban areas. Second, Airbnb units were mainly located in residential areas, especially around multiplexes and townhouses. This finding indicates that Airbnb may decrease the availability of housing in the housing market. Third, Airbnb units were located preferentially in areas adjacent to universities or subway stations, as well as in areas with high ratios of single-person households. Considering these characteristics of Airbnb and the directions of government housing policy, urban scholars and policymakers should pay close attention to the potential conflict between the spatial distributions of Airbnb units and housing policies.

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References

2007Methods to account for spatial autocorrelation in the analysis of species distributional data: a review 2017The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry 2013Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector 2018Airbnb and the rent gap: Gentrification through the sharing economy 2017The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona 2017When Tourists Move In: How Should Urban Planners Respond to Airbnb?2017Is home sharing driving up rents? Evidence from Airbnb in Boston 2016Who Benefits from the "Sharing" Economy of Airbnb?

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2022A global-scale analysis of the sharing economy model – an AirBnB case study 2022Analyzing the influence of short-term rental platforms on housing affordability in global urban destination neighborhoods 2022Spatial distribution of Airbnb and its influencing factors: A case study of Suzhou, China 2023The spatial patterns of Airbnb offers, hotels and attractions: are professional hosts taking over cities?

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