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Article: Built environment and airbnb spatial distribution in Hong Kong: A case study considering the spatial heterogeneity and multiscale effects

TitleBuilt environment and airbnb spatial distribution in Hong Kong: A case study considering the spatial heterogeneity and multiscale effects
Authors
KeywordsBuilt environment
Effect scale
Multiscale geographic weighted regression
Sharing accommodation
Urban planning
Issue Date8-Apr-2024
PublisherElsevier
Citation
Applied Geography, 2024, v. 166 How to Cite?
AbstractAs a new form of tourist accommodation, Airbnb has gained widespread popularity worldwide in Hong Kong. Considering the spatial heterogeneity and multiscale effects, this study employs the Multiscale Geographically Weighted Regression (MGWR) approach to reveal the impact of the built environment on Airbnb distribution in Hong Kong. The main findings are as follows: i) The density of hotels, cultural facilities, and tourist attractions, as well as the supply of residential land and open space (or recreational land), have a significant impact on the spatial distribution of Airbnb and vary according to geographic location; ii) At the local level, open spaces (or recreational land) present positively correlated with Airbnb density in mature tourism areas, yet this correlation reverses in certain localized communities; iii) Factors, such as location, traffic accessibility and caterings, may become less critical for Airbnb's location in highly developed cities like Hong Kong; iv) The density of cultural facilities has a global impact on Airbnb distribution, followed by hotel density, and the effect scale of residential land supply and open spaces (or recreational land) tend to be local. This empirical study can support precise and differentiated planning interventions and policy-making to promote a healthier development of the Airbnb market.
Persistent Identifierhttp://hdl.handle.net/10722/346032
ISSN
2023 Impact Factor: 4.0
2023 SCImago Journal Rankings: 1.204

 

DC FieldValueLanguage
dc.contributor.authorJiang, Xiji-
dc.contributor.authorYe, Dan-
dc.contributor.authorLi, Kaiming-
dc.contributor.authorFeng, Rundong-
dc.contributor.authorWu, Ying-
dc.contributor.authorYang, Tianren-
dc.date.accessioned2024-09-06T00:30:34Z-
dc.date.available2024-09-06T00:30:34Z-
dc.date.issued2024-04-08-
dc.identifier.citationApplied Geography, 2024, v. 166-
dc.identifier.issn0143-6228-
dc.identifier.urihttp://hdl.handle.net/10722/346032-
dc.description.abstractAs a new form of tourist accommodation, Airbnb has gained widespread popularity worldwide in Hong Kong. Considering the spatial heterogeneity and multiscale effects, this study employs the Multiscale Geographically Weighted Regression (MGWR) approach to reveal the impact of the built environment on Airbnb distribution in Hong Kong. The main findings are as follows: i) The density of hotels, cultural facilities, and tourist attractions, as well as the supply of residential land and open space (or recreational land), have a significant impact on the spatial distribution of Airbnb and vary according to geographic location; ii) At the local level, open spaces (or recreational land) present positively correlated with Airbnb density in mature tourism areas, yet this correlation reverses in certain localized communities; iii) Factors, such as location, traffic accessibility and caterings, may become less critical for Airbnb's location in highly developed cities like Hong Kong; iv) The density of cultural facilities has a global impact on Airbnb distribution, followed by hotel density, and the effect scale of residential land supply and open spaces (or recreational land) tend to be local. This empirical study can support precise and differentiated planning interventions and policy-making to promote a healthier development of the Airbnb market.-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofApplied Geography-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBuilt environment-
dc.subjectEffect scale-
dc.subjectMultiscale geographic weighted regression-
dc.subjectSharing accommodation-
dc.subjectUrban planning-
dc.titleBuilt environment and airbnb spatial distribution in Hong Kong: A case study considering the spatial heterogeneity and multiscale effects-
dc.typeArticle-
dc.identifier.doi10.1016/j.apgeog.2024.103262-
dc.identifier.scopuseid_2-s2.0-85189692947-
dc.identifier.volume166-
dc.identifier.eissn1873-7730-
dc.identifier.issnl0143-6228-

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