{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T23:57:32Z","timestamp":1770681452903,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T00:00:00Z","timestamp":1703030400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"School of Business and Society, University of Redlands"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>This paper examines spatiotemporal patterns and socioeconomic influences on host participation in Airbnb\u2019s short-term rental (STR) marketplace in San Francisco during the years 2019\u20132022, a four-year period that spans the COVID-19 pandemic. This provides the motivation for the study to examine how San Francisco\u2019s demographic and socioeconomic fluctuations influenced Airbnb hosts to rent their properties on the platform. To do so, Airbnb property densities, indicators of host participation, are estimated at the census tract level and subsequently mapped in a GIS along with points of interest (POIs) located all over the city. Mapping unveils spatiotemporal patterns and changes in Airbnb property densities, which are also analyzed for spatial autocorrelation using Moran\u2019s I. Clusters and outliers of property densities are identified using K-means clustering and geostatistical methods such as local indicators of spatial association (LISA) analysis. Locationally, San Francisco\u2019s Airbnb hotspots are not located in the city\u2019s core, unlike other major Airbnb markets in metropolitan areas. Instead, such hotspots are in the city\u2019s northeastern neighborhoods around ethnic enclaves, in close proximity to POIs that are frequented by visitors, and have a higher proportion of hotel and lodging employment and lower median household income. A conceptual model posits associations of Airbnb property densities with sixteen demographic, socioeconomic factors, indicators of trust, social capital, and sustainability, along with proximity to points of interest. Ordinary least squares (OLS) regressions reveal that occupation in professional, scientific, and technical services, hotel and lodging employment, proximity to POIs, and proportion of Asian population are the dominant factors influencing host participation in San Francisco\u2019s shared accommodation economy. The occupational influences are novel findings for San Francisco. These influences vary somewhat for two main types of properties\u2014entire home\/apartment and private rooms. Implications of these findings are discussed in relation to supply side motivations of Airbnb hosts to participate in San Francisco\u2019s STR marketplace.<\/jats:p>","DOI":"10.3390\/ijgi13010004","type":"journal-article","created":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T11:24:33Z","timestamp":1703071473000},"page":"4","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Spatiotemporal Patterns and Socioeconomic Influences on Host Participation in Short-Term Rental Markets: Airbnb in San Francisco"],"prefix":"10.3390","volume":"13","author":[{"given":"Avijit","family":"Sarkar","sequence":"first","affiliation":[{"name":"School of Business & Society, University of Redlands, Redlands, CA 92373, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9048-324X","authenticated-orcid":false,"given":"James B.","family":"Pick","sequence":"additional","affiliation":[{"name":"School of Business & Society, University of Redlands, Redlands, CA 92373, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaista","family":"Jabeen","sequence":"additional","affiliation":[{"name":"Department of GIS, University of Redlands, Redlands, CA 92373, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,20]]},"reference":[{"key":"ref_1","unstructured":"NTIA (2023, June 19). 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