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Spatial and socioeconomic analysis of host participation in the sharing economy : Airbnb in New York City

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In recent years, short-term sharing accommodation platforms such as Airbnb have made rapid forays in populous cities worldwide, impacting neighborhoods profoundly. Emerging work has focused on demand-side motivations to engage in the sharing economy. The purpose of this paper is to analyze rarely examined supply-side motivations of providers.


To address this gap and to illuminate understanding of how Airbnb supply is configured and influenced, this study examines spatial patterns and socioeconomic influences on participation in the sharing accommodation economy by Airbnb hosts in New York City (NYC). An exploratory conceptual model of host participation is induced, which posits associations of demographic, economic, employment, social capital attributes, and attitudes toward trust and sustainability with host participation, measured by Airbnb property density in neighborhoods. Methods employed include ordinary least squares (OLS) regression, k-means cluster analysis and spatial analytics.


Spatially, clusters of high host densities are in Manhattan and northern Brooklyn and there is little proportionate change longitudinally. OLS regression findings reveal that gender ratio, black race/ethnicity, median household income, and professional, scientific, and technical occupation, and attitudes toward sustainability for property types are dominant correlates of property density, while host trust in customers is not supported.

Research limitations/implications

These results along with differences between Queens and Manhattan boroughs have implications for hosts sharing their homes and for city managers to formulate policies and regulate short-term rental markets in impacted neighborhoods.


The study is novel in conceptualizing and analyzing the supply-side provider motivations of the sharing accommodation economy. Geostatistical analysis of property densities to gauge host participation is novel. Value stems from new insights on NYC’s short-term homesharing market.
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Keywords: Community; Empirical study; Gender; Individual attribute; Level of analysis; Methodology; Panel data; Trust; Unit attribute

Document Type: Research Article

Affiliations: 1: School of Business, University of Redlands, Redlands, California, USA 2: Computer Information Systems, College of Business Administration, California State Polytechnic University, Pomona, California, USA

Publication date: June 18, 2020

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