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ABSTRACT
With the emergence and development of sharing economy, Airbnb has established a global impact. Relatively low price is a major factor of its popularity, but the special pricing mode leads to risk of irrational decisions. Understanding the mechanism is of great practical significance, while existing research is limited in investigation into multidimensional built environment features and heterogeneity analysis from both perspectives of space and time. Based on Hedonic Price Method, combining Ordinary Least Squares and Geographically Weighted Regression, this research explores the influence of built environment features on Airbnb listing price and the spatio-temporal heterogeneity using datasets from December 2022 (low tourist season) and June 2023 (high tourist season) in Copenhagen. It is found that six indicators in three dimensions present statistically significant influence at the local scale, which exhibits great spatial dependence as well as certain temporal non-stationarity. The framework proposed provides methodological reference for subsequent research, and the findings will facilitate more targeted regulation of the pricing of Airbnb by authorities, promote the grasp of the attributes of listings for smarter pricing by hosts, support more reasonable choices by consumers, and contribute to more refined built environment practices by urban designers.
Disclosure statement
No potential conflict of interest was reported by the author(s).