SPATIOTEMPORAL PATTERNS AND SOCIOECONOMIC DIMENSIONS OF SHARED ACCOMMODATIONS: THE CASE OF AIRBNB IN LOS ANGELES, CALIFORNIA
- University of Redlands, School of Business, USA
Keywords: Sharing Economy, Airbnb, Socioeconomic, Spatiotemporal, Los Angeles, Spatial Autocorrelation, Regression
Abstract. In recent years, disruptive innovation by peer-to-peer platforms in a variety of industries, notably transportation and hospitality have altered the way individuals consume everyday essential services. With growth in sharing economy platforms such as Uber for ridesharing and Airbnb for short-term accommodations, interest in examining spatiotemporal patterns of participation in the sharing economy by suppliers and consumers is increasing. This research is motivated by key questions: who are the sharing economy workers, where are they located, and does their location influence their participation in the sharing economy? This paper is the first systematic effort to analyze spatiotemporal patterns of participation by hosts in the shared accommodation-based economy. Using three different kinds of shared accommodations listed in a 3-year period in the popular short-term accommodation platform, Airbnb, we examine spatiotemporal dimensions of host participation in a major U.S. market, Los Angeles CA. The paper also develops a conceptual model by positing associations of demographic, socioeconomic, occupational, and social capital attributes of hosts, along with their attitudes toward trust and greener consumption with hosts’ participation in a shared accommodation market. Results confirm host participation to be influenced by young dependency ratio, the potential of supplemental income, as well as the sustainability potential of collaborative consumption, along with finance, insurance, and real estate occupation, but not so much by trust for our overall study area. These results add new insights to limited prior knowledge about the sharing economy worker and have policy implications.