Shared urbanism: Big data on accommodation sharing in urban Australia

📝 Abstract

As affordability pressures and tight rental markets in global cities mount, online shared accommodation sites proliferate. Home sharing arrangements present dilemmas for planning that aims to improve health and safety standards, while supporting positives such as the usage of dormant stock and the relieving of rental pressures on middle/lower income earners. Currently, no formal data exists on this internationally growing trend. Here, we present a first quantitative glance on shared accommodation practices across all major urban centers of Australia enabled via collection and analysis of thousands of online listings. We examine, countrywide, the spatial and short time scale temporal characteristics of this market, along with preliminary analysis on rents, dwelling types and other characteristics. Findings have implications for housing policy makers and planning practitioners seeking to monitor and respond to housing policy and affordability pressures in formal and informal housing markets.

💡 Analysis

As affordability pressures and tight rental markets in global cities mount, online shared accommodation sites proliferate. Home sharing arrangements present dilemmas for planning that aims to improve health and safety standards, while supporting positives such as the usage of dormant stock and the relieving of rental pressures on middle/lower income earners. Currently, no formal data exists on this internationally growing trend. Here, we present a first quantitative glance on shared accommodation practices across all major urban centers of Australia enabled via collection and analysis of thousands of online listings. We examine, countrywide, the spatial and short time scale temporal characteristics of this market, along with preliminary analysis on rents, dwelling types and other characteristics. Findings have implications for housing policy makers and planning practitioners seeking to monitor and respond to housing policy and affordability pressures in formal and informal housing markets.

📄 Content

Shared urbanism: Big data on accommodation sharing in urban Australia Somwrita Sarkar and Nicole Gurran

Abstract As affordability pressures and tight rental markets in global cities mount, online shared accommodation sites proliferate. Home sharing arrangements present dilemmas for planning that aims to improve health and safety stand- ards, while supporting positives such as the usage of dormant stock and the relieving of rental pressures on middle/lower income earners. Currently, no formal data exists on this internationally growing trend. Here, we present a first quantitative glance on shared accommodation practices across all major urban centers of Australia enabled via collection and analysis of thousands of online listings. We examine, countrywide, the spatial and short time scale temporal characteristics of this market, along with preliminary analysis on rents, dwelling types and other characteristics. Findings have implications for housing policy makers and planning practitioners seeking to monitor and respond to housing policy and affordability pressures in formal and informal housing markets.

S. Sarkar (Corresponding author) Architecture, Design and Planning, The University of Sydney, NSW 2006 Australia.
Email: somwrita.sarkar@sydney.edu.au

N. Gurran Architecture, Design and Planning, The University of Sydney, NSW 2006 Australia.
Email: nicole.gurran@sydney.edu.au

1. Introduction A city is a sum total of its physical-spatial structure and the social, techno- logical, and economic processes that occur within this structure (Batty, 2013). While some aspects of these processes are planned, or regulated, most processes are self-organised, shaped by local peer-to-peer interactions. A particular example of self-organised processes can be observed in the ris- ing phenomenon of the shared economy or what we term as shared urban- ism: peer-to-peer sharing of resources enabling functions such as mobility (car sharing or pooling practices) and accommodation (flatsharing or house- sharing). Such phenomenon present profound but largely unknown and un- explored implications for both mobility as well as housing policy and plan- ning and urban regulation. They represent what may be termed as an “infor- mal sector”. The self-organised behavior of shared urbanism promises more adaptive, more responsive and more resilient cities on the one hand, by “freeing up and using” dormant resources in a largely market driven manner (i.e. no central regulation or control). On the other hand, concerns arise on aspects such as health, equity, discrimination, or distribution outcomes that seem to be simultaneously embedded inherently in these processes, tied deeply to their relationship with the sizes of urban systems (Cottineau, 2016; Sarkar, Phibbs, Simposon and Wasnik, 2016). A natural question arises: as the world urbanises faster than ever, and urban agglomertions grow in num- ber and absolute size, what is the role played by these self-organised peer- to-peer processes? To resolve this dilemma, a deep data-driven understand- ing is needed. Unfortunately, due to their fast-changing, short term and dy- namic nature, they also represent a large data gap in terms of enhancing our understanding of this specific class of socio-economic urban processes and their relationship to spatial structure, since national statistical bodies [such as the Australian Bureau of Statistics (ABS) for Australia] do not have many surveys or programs to capture this type of data.

In line with the major theme of this conference, shared mobility and accom- modation practices in cities represent one of the key areas of “big urban data” generation with a very specific characteristic: the data on sharing is big (in the sense of weekly or daily volumes), but it is also big because of its temporal continuity (Santi, 2014). The websites for each of these services witness hourly, daily and weekly changes, with the added caveat that this data is also extremely ephemeral: listings can disappear as soon as a property is let out. Capturing such data can provide a wealth of information and pol- icy relevant evidence for urban planning, especially because it represents a facet of continuous and ephemeral urban data that is not captured at all through the more traditional and official data collection mechanisms. Exist- ing official data collection channels are much more infrequent and depend- ent on samples, and therefore ill-suited to capture the rich temporal dynam- ics of such processes. Facilitated by the web footprint, it is now possible to capture very large samples of this class of data, more or less continuously, thereby overriding the problem of small or infrequent samples in traditional surveys.

However, with any new data type, strengths as well as limitations should be discussed. In this case too, there are limitations. Firs

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