While many well-researched and written news articles about Airbnb and its impact on housing have been published (some of them linked on my Airbnb timeline), so far there seems to be a bit of a dearth of scholarly writing on the topic. That’s not surprising since academia moves at a much slower pace than media and pop culture (and fittingly so). Below is what I’ve found so far in the way of academic research on Airbnb specifically. I will try to update this list or write more posts as I come across work that is relevant to Airbnb’s impact on rental housing.
*Note: You might need to access some of these articles through a public or university library.
Defining the Price of Hospitality: Networked Hospitality Exchange via Airbnb, by Tapio Ikkala and Airi Lampinen (Poster at the 17th ACM conference on computer supported cooperative work & social computing) Feb 15-19, 2014.
These two Finnish researchers with the Helsinki Institute of Information are interested in social exchange theory. They interviewed 11 Airbnb hosts with the goal of “shed[ding] light on the behaviors and norms in play in a socio-technical system that fosters monetary transactions as a part of exchanges that require coordination and trust between the exchange partners.”
The researchers reached two main conclusions: It’s common for hosts to increase the price of their listing as they accumulate positive reviews, and hosts may choose to offer their listing at a lower price so as to allow them a wider choice of guests. No surprises there, and these patterns seem consistent with landlords in the long-term rental market act.
The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry, by Georgios Zervas, Davide Proserpio and John W. Byers (January 22, 2014)
This study from the Boston University School of Management looks at the one question that many in the hospitality industry are burning to know the answer to: How is Airbnb affecting their sector’s revenues? The authors (including two computer scientists) created a dataset of all Texas Airbnb listings between 2008 and 2013 (22,000 stays) and compared that to a panel of quarterly tax revenues for ten years. Based on their results, they estimate that “a 1% increase in Airbnb listings in Texas results in a 0.05% decrease in quarterly hotel revenues” and that lower-end hotels and those that don’t cater to business travellers were most adversely affected.
Our work is among the first to provide empirical evidence that the sharing economy is significantly changing consumption patterns, as opposed to generating purely incremental activity, as argued in prior work. Studying the case of Airbnb…we identify that its entry into the Texas market has had a quantifiable negative impact on local hotel revenues.
The authors include a lot of technical detail on their methodology in the paper.
Digital Discrimination:The Case of Airbnb.com, by Benjamin G. Edelman and Michael Luca (January 10, 2014)
This study (a working paper) by two professors at Harvard Business School looks at how hosts’ appearance (specifically skin colour and facial features) is related to the amount they charge for their listings and concludes that, “Nonblack hosts are able to charge approximately 12 percent more than black hosts, holding location, rental characteristics, and quality constant. Moreover, black hosts receive a larger price penalty for having a poor location relative to nonblack hosts. These differences highlight the risk of discrimination in online marketplaces, suggesting an important unintended consequence of a seemingly-routine mechanism for building trust.”
While I think this is an interesting topic and I don’t doubt that African-Americans and other people of colour are discriminated against as Airbnb hosts (just like they are everywhere else), I really wonder about the methodology the researchers used to reach their conclusions. To carry out their study, they constructed a dataset of all New York City Airbnb hosts, their profile pictures, and the characteristics of their properties. Part of their analysis involved instructing Amazon Mechanical Turk workers to code each photo into one of eight categories: White; Black; Hispanic; Asian; Unclear, But not White; Multiple Races; Not Applicable; or Unclear/Uncertain.
So, two big things…First of all – using Amazon Mechanical Turk workers to carry out this work? Until I read this paper, I hadn’t even heard of Amazon Mechanical Turk; I certainly didn’t know that some social science academics are using the service to carry out this kind of work (as stated in this Wikipedia article). Aside from the many labour issues this practice raises, how does it affect the reliability of the data? The authors don’t go into any more detail about how they instructed the AMTs, but given that the jobs are structured as piecework, for which workers (working in their own homes) may be paid far less than minimum wage, I really wonder about the the biases that introduces.
The other thing is that coding people into race categories based on photos (especially a single photo posted on a website for marketing purposes) seems like a highly unreliable process that would produce different results from different respondents based on their life experiences and how they themselves have been racialized. The authors don’t explain whether or how they tried to control for those biases (if that would even be possible). If you gave the same ten profile photos to ten people with different ethnic and cultural backgrounds, do you think they would all categorize the race of each person the same way? I don’t. In addition to their own racialization, respondents’ choices might vary by age, religion, location, where they grew up, and gender, among numerous other factors. I think the methodology raise all sorts of questions, so despite my general agreement with the hypothesis, I am dubious about the results.
So far, those are the three main independent academic studies I’ve found on Airbnb.
Arguably, I should include in this 2013 study conducted by Professor Ken Rosen (who has a PhD in economics and is chair of the Fisher Center for Real Estate and Urban Economics at UC Berkeley’s Hass School of Business), though I’m somewhat hesitant to do so, because the study was commissioned by Airbnb. Perhaps entirely coincidentally, the study concludes that, “While short-term rental activity is on the rise…it is such a small share of homes in large cities that the industry can not have a meaningful impact on apartment occupancy or pricing trends.” Decide for yourself: Short-term rentals and the rental housing market.
Certainly, there is more academic research available on the broader subject of short-term housing rentals, of which Airbnb is a subset. I’m guessing there is also lots more on the so-called “sharing economy,” but I think most of that work is outside the scope of my research questions. Here are a few journal articles I’ve perused on short-term rentals:
Residential Short-Term Rentals: Should Local Governments Regulate the ‘Industry’?by Charles Gottlieb in Planning and Environmental Law (January 2013)
This article mentions Airbnb, but has a broader focus, which is why it is in this more general section. Focused on the U.S., this one is very useful for getting an overview on the different regulatory approaches local governments have taken to short-term rentals. These include comprehensive permitting programs and stricter or modified enforcement of existing regulations, such as noise abatement and nuisance bylaws. The author also reviews legal challenges local governments have faced and discusses two examples of state intervention (New York and Florida). He notes that many existing local regulations were not made with short-term rentals in mind and concludes that, “The expansion of home-rental websites presents local governments with a controversial policy debate, requiring them to more clearly choose a direction and decide whether to ban, encourage, or limit short-term rentals through regulation.”
Home Sweet Home? The Efficacy of Rental Restrictions to Promote Neighbourhood Stability, by Ngai Pindell, Saint Louis University Public Law Review 41 (2009)
While this lengthy article is broad and addressed to the U.S. context (referring to the aftermath of the housing bubble in particular), I think it will be quite useful to me and I’ll need to take some time with it. Restrictions on short-term vacation rentals are just one of the types of rental restrictions it covers. The author also addresses attempts to control speculation and evaluates the effectiveness of restrictions. The article concludes with this:
The investment ideal of conventional homeownership has remained unquestioned for too long. Moreover, recent economic events demonstrate that more flexibility in ownership models and regulatory regimes is necessary to preserve the economic stability of individuals and communities. Local governments—close to their constituents and adaptable to change—may be the appropriate sites for new regulatory approaches.
Why do governments hate bed and breakfasts? By Louise Staley, Institute of Public Affairs Review, Vol 59, issue 1 (2007)
In this 2007 article (written before the rise of Airnbnb) the author argues that bed and breakfasts (and farmstays) are over-regulated and suggests ways to change that. She believes that doing so is worthwhile because it will help “diversify rural and regional economies.”
The Institute of Public Affairs is based in Australia and advocates for “the free market of ideas, the free flow of capital, a limited and efficient government, evidence-based public policy, the rule of law, and representative democracy.”