Sharing economy platforms have become extremely popular in the last few years, and they have changed the way in which we commute, travel, and borrow among many other activities. Despite their popularity among consumers, such companies are poorly regulated. For example, Airbnb, one of the most successful examples of sharing economy platform, is often criticized by regulators and policy makers. 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. Here we propose to gather evidence from the Web. After crawling Airbnb data for the entire city of London, we find out where and when Airbnb listings are offered and, by matching such listing information with census and hotel data, we determine the socio-economic conditions of the areas that actually benefit from the hospitality platform. The reality is more nuanced than one would expect, and it has changed over the years. Airbnb demand and offering have changed over time, and traditional regulations have not been able to respond to those changes. That is why, finally, we rely on our data analysis to envision regulations that are responsive to real-Time demands, contributing to the emerging idea of "algorithmic regulation".

Who benefits from the "sharing" economy of airbnb?

Quattrone G.;
2016-01-01

Abstract

Sharing economy platforms have become extremely popular in the last few years, and they have changed the way in which we commute, travel, and borrow among many other activities. Despite their popularity among consumers, such companies are poorly regulated. For example, Airbnb, one of the most successful examples of sharing economy platform, is often criticized by regulators and policy makers. 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. Here we propose to gather evidence from the Web. After crawling Airbnb data for the entire city of London, we find out where and when Airbnb listings are offered and, by matching such listing information with census and hotel data, we determine the socio-economic conditions of the areas that actually benefit from the hospitality platform. The reality is more nuanced than one would expect, and it has changed over the years. Airbnb demand and offering have changed over time, and traditional regulations have not been able to respond to those changes. That is why, finally, we rely on our data analysis to envision regulations that are responsive to real-Time demands, contributing to the emerging idea of "algorithmic regulation".
2016
25th International World Wide Web Conference, WWW 2016
Palais des Congress de Montreal, Canada
2016
25th International World Wide Web Conference, WWW 2016
International World Wide Web Conferences Steering Committee
1385
1393
9781450341431
http://gdac.uqam.ca/WWW2016-Proceedings/forms/proceedings.htm#K
https://dl.acm.org/doi/10.1145/2872427.2874815
Quattrone G.; Proserpio D.; Quercia D.; Capra L.; Musolesi M.
File in questo prodotto:
File Dimensione Formato  
www_2016.pdf

Accesso riservato

Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 7.47 MB
Formato Adobe PDF
7.47 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
2872427.2874815.pdf

Accesso riservato

Tipo di file: PDF EDITORIALE
Dimensione 8.02 MB
Formato Adobe PDF
8.02 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1730542
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 208
  • ???jsp.display-item.citation.isi??? 167
social impact