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The Analysis of Airbnb Blocking Behavior and Relative Position to Top Tourism
- 1 University of Michigan
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Abstract
With the rapid development of Airbnb in recent years, it has taken the main position in the sharing economy and also brought a great number of challenges to hotel competitors and regulators for its volatile supply. The benefit of agglomeration relative to Airbnb listing position and blocking behavior of listings has been discussed by Xie et al. (2019) and Peng (2020), and how the locational factor affects the blocking behavior remained unanswered. This paper will select the New York Airbnb listing data from Oct. 2014 to Dec. 2016 to compile the distance binary variables in 3 groups to identify whether they are near the top 10 attraction and then perform the logistic regression and t-test, which delineates the relationship between blocking behaviors and distance to attractions. We find that almost all top attraction variables significantly affect the Airbnb listings’ blocking behaviors, but no clear pattern of direction is shown. Considering the negative elasticity of income for NYC cab working hours, this paper performs t-tests on attractions’ yearly revenue indicating that while the coefficient estimates are both positive, their yearly revenue consistently has no significant differences of income in the 200m radius distance variable and no consistent result can be obtained in comparing attractions’ yearly revenue with opposite signs coefficient.
Keywords
sharing economy, blocking behavior, locational factor, Airbnb
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Cite this article
Xia,L. (2024). The Analysis of Airbnb Blocking Behavior and Relative Position to Top Tourism. Journal of Applied Economics and Policy Studies,5,15-28.
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