Year: 2019
Type: dissertation
Abstract: In the last several years, Airbnb and other short-term rental (STR) services have grown precipitously across Canada, but very little is known about the scale and character of this activity or its impact on housing.This study presents a two-part approach to short-term rental investigations which includes: (1) a comprehensive examination of short-term rental markets with a focus on the types of rentals which comprise the market and their effects on housing, and (2) a lifecycle analysis that demonstrates how the behaviors of a market's constituent listings can be expected to vary throughout their lives.The subsequent findings can be leveraged by planners and policymakers to proactively tailor short-term rental regulations to prevent the anticipated negative externalities associated with their specific STR market.Relying on spatial analysis of big data, this study applies this approach to evaluate the Canadian Airbnb market.Airbnb activity is highly concentrated geographically-nearly half of all active listings are located in the Toronto, Montréal and Vancouver metropolitan areas-and highly concentrated among hosts, the top 10% of whom earn a majority of all revenue.Contrary to the rhetoric of "home sharing", almost 50% of all Airbnb revenue last year was generated by commercial operators who manage multiple listings.Moreover, 31,000 entire homes were rented frequently enough last year that they are unlikely to house a permanent resident.This housing pressure disproportionately affects West Coast cities.While current Airbnb activity is concentrated in major cities, active listings, total revenue, hosts with multiple listings, and frequently rented entire-home listings are all growing at substantially higher rates in small towns and rural areas.The results of the lifecycle analysis reveal that patterns of activity vary predictably along a number of dimensions related to a listing's type, location, and occupancy-rate status.This suggests that, if armed with knowledge of the basic characteristics of STRs within their jurisdiction, planners and policymakers can effectively predict the evolutionary patterns of their local STR market and develop targeted regulatory frameworks.
Source: eScholarship@McGill (McGill)
Author: Combs, Jennifer
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7071214597