Who benefits from the "Sharing" Economy of Airbnb
 










        
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Paper
Who benefits

Scientific paper pdf bib


Data
London Census data (soon).



Images
London maps of hotels, Airbnb rooms, and Airbnb houses (soon).
























Who benefits from the "Sharing" Economy of Airbnb

Full citation
Giovanni Quattrone, Davide Proserpio, Daniele Quercia, Licia Capra, and Mirco Musolesi
Who Benefits from the “Sharing” Economy of Airbnb?
In Proceedings of the 26th International ACM Conference on World Wide Web (WWW), 2016



Who benefits from Airbnb in London,  how to regulate it with evidence-informed recommendations.
While, in theory, municipalities should regulate the emergence of Airbnb through evidence-based policy making, in practice, they engage in a false dichotomy: some municipalities allow the business without imposing any regulation, while others ban it altogether. That is because there is no evidence upon which to draft policies. A team of five researchers mined the Airbnb data for the entire city of London. In so doing, they found out where and when Airbnb properties are offered and, by matching such information with census and hotel data, they determined the socio-economic conditions of the areas that benefit from Airbnb, and answered five questions.

1. Where are Airbnb properties located?
Not only where hotels are! Hotels are mostly concentrated in the center and near the main airports. Airbnb houses are present in the city center as well, but they also reach adjacent areas, and  Airbnb rooms uniformly cover great part of the city, including suburban areas.

2. Which areas benefit from Airbnb ?
Airbnb has penetrated areas with a vibrant housing market of flats rented by young, tech-savvy, employed, well-educated, and multi-ethnic residents, while it has not fully penetrated areas with a traditional (suburban) housing market of house owners.

3. Has that changed over the years ?
Yes, from 2012 to 2015, Airbnb’s offering has changed quite a bit. Early adopting areas were centrally located and were characterized by young, tech-savvy and ethnically-mixed residents, some of whom were students. After less than two years, Airbnb had started to penetrate areas of two types: it penetrated areas either of flat owners or of medium/low-income renters.

4. Is there any difference between offering and demand ?
Yes. Offering is spread throughout the city (as we have seen), while demand is still concentrated in the central parts of the city.  This indicates that many properties that are listed, but are too far form touristic areas, are not being rented out. Therefore, while, in theory, Airbnb allows travelers to be flexible when choosing locations for their stays (which has the potential to distribute travelers among more diverse areas of the city), in practice, such flexibility is not fully exploited at the moment.

5. What are the policy implications?
The short-term rental market could be legalized through “transferable sharing rights” and, when doing so, cities need to consider three main aspects:

a. New web platforms could offer schemes of “transferable sharing rights” online. Those platforms could be similar to those that sell, say, tickets for the theater: prices could be based on both real-time market demand and on municipal or, even, neighborhood-specific policies.

b. Policies should consider five main factors: future consequences of Airbnb adoption (e.g., externalities created by the short-term rentals), what has been offered (e.g., distinguishing rooms from apartments is essential), development of local economies and the decentralization of the city’s economic activity, sustainability of tourism, and avoidance of short-term rental “hot-spots”.

c. Cities should incentivize the creation of a data sharing ecosystem. Having Airbnb data and, say, census data in the same place makes it possible to track the impact of a policy. Municipalities should constantly evaluate the impact of short-term rentals based on data, and they should accordingly refine their regulations.


FAQs
What was the purpose of this study and what do you hope the results will help achieve?
The goal of this work was to determine who benefits from Airbnb in London, and how that has changed over the years in the entire city. Cities do not know how to regulate the sharing economy but might well use web data to offer evidence-informed policies. Here we have shown one way of doing so. 

Why is this work important?
This work contributes to the general idea of “algorithmic regulation”, which argues for the analysis of large sets of data to produce regulations that are responsive to real-time demands. Such an approach might be used to regulate any civic issue independent of the sharing economy.

Did any of the results surprise you?
Two points come to mind.  The first has to do with the temporal evolution. Early adopters seem to be young, tech-savvy and ethnically-mixed renters (including students), while late-adopters seem to be increasingly lower income renters, year after year. The second point has to do with the profound difference between rooms and apartments. Rooms are offered in areas where properties are generally rented, while  houses are offered in central areas where properties are generally owned.


The research paper can be found here.

For more information, please contact: Daniele Quercia, Head of Social Dynamics at Bell Labs Cambridge UK; email: quercia@cantab.net; skype: dquercia

Notes for editors: The project involves Giovanni Quattrone (University College London), Davide Proserpio (Boston University), Daniele Quercia (Bell Laboratories Cambridge UK), Licia Capra (University College London), and Mirco Musolesi (University College London) . The research paper is published in the International Conference of World Wide Web (ACM WWW) 2016. Any news article covering this research should add a link to this site or to the original research paper here
.