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Key Factors Affecting the Price of Airbnb Listings: A Geographically Weighted Approach

Zhihua Zhang (), Rachel J. C. Chen (), Lee D. Han () and Lu Yang ()
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Zhihua Zhang: Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, TN 37996-2313, USA
Rachel J. C. Chen: Center for Sustainable Business and Development, The University of Tennessee, 311 Conference Center Building, Knoxville, TN 37996-4134, USA
Lee D. Han: Department of Civil and Environmental Engineering, 319 John D. Tickle Building, The University of Tennessee, Knoxville, TN 37996-2313, USA
Lu Yang: Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, TN 37996-2313, USA

Sustainability, 2017, vol. 9, issue 9, 1-13

Abstract: Airbnb has been increasingly gaining popularity since 2008 due to its low prices and direct interactions with the local community. This paper employed a general linear model (GLM) and a geographically weighted regression (GWR) model to identify the key factors affecting Airbnb listing prices using data sets of 794 samples of Airbnb listings of business units in Metro Nashville, Tennessee. The results showed that the GWR model performs better than the GLM in terms of accuracy and affected variable selections. Statistically significant differences varied across regions in Metro Nashville. The coefficients illustrate a decreasing trend while there is an increase in the distance from the listed units to the convention center, which indicates that Airbnb listing prices are more sensitive to the distance from the convention center in the central area than in other areas. These findings can also provide implications for stakeholders such as Airbnb hosts to gain a better understanding of the market situation and formulate a suitable pricing strategy.

Keywords: Airbnb; sharing economy; price; GWR; factors (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2017
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