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Built environment and airbnb spatial distribution in Hong Kong: A case study considering the spatial heterogeneity and multiscale effects
16 references·0 citing·40 second hop
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References

  • 1996Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity3,562 cited
  • 2013Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector1,853 cited
  • 1991The Modifiable Areal Unit Problem in Multivariate Statistical Analysis1,558 cited
  • 2017Multiscale Geographically Weighted Regression (MGWR)1,381 cited
  • 2003Spatial Externalities, Spatial Multipliers, And Spatial Econometrics1,039 cited
  • 2019mgwr: A Python Implementation of Multiscale Geographically Weighted Regression for Investigating Process Spatial Heterogeneity and Scale829 cited
  • 2017The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona676 cited
  • 2017When Tourists Move In: How Should Urban Planners Respond to Airbnb?540 cited
  • 1992WHAT ATTRACTS FOREIGN MULTINATIONAL CORPORATIONS? EVIDENCE FROM BRANCH PLANT LOCATION IN THE UNITED STATES453 cited
  • 2019Inference in Multiscale Geographically Weighted Regression414 cited
  • 2018Regulating Airbnb: how cities deal with perceived negative externalities of short-term rentals404 cited
  • 2020Do short-term rental platforms affect housing markets? Evidence from Airbnb in Barcelona367 cited
  • 2004The Validity and Usefulness of Laws in Geographic Information Science and Geography337 cited
  • 2018

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Consumer segmentation within the sharing economy: The case of Airbnb
305 cited
  • 2016Geographically weighted regression and multicollinearity: dispelling the myth299 cited
  • 2020Sharing economy business models for sustainability283 cited
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