When browsing Airbnb listings for a weekend getaway, you would not only check cottage amenities but also scroll through previous guest reviews. And if you put up your house for rental on the same platform, you would scrutinise prospective guests beforehand. Wouldn’t you?
Because everyone wants reassurance, especially when it comes to letting strangers into your home. “No one wants to rent to a person who used the last rental as a temporary brothel or drug den,” as a New York Times article puts it.
Controlling online transactions between strangers
After all, there is no way online platforms such as Airbnb, Turo or Uber (the so-called sharing economy) can control each and every transaction. This is why, to maintain trust in their platforms, they decentralise control to users. How? Via evaluations – while retaining power over the control infrastructure.
In our research paper, we assert that within this platform capitalism, peer-to-peer platforms are a specific case.
We explain that evaluations in a peer-to-peer context are intriguing for two reasons:
Trust is a two-way concern, since any user of the platform can both provide a service and offer one. This introduces reciprocity in the evaluation.
Access-based consumption changes what is at stake in online reviews. The users still own their apartments after a rental, unlike in standard sale transactions, consequently reviews relate to personal dimensions as private lives are engaged in a market.
Airbnb: a “netnography”
To investigate the mechanisms through which users appropriate platforms, we drew on a case study of the home-renting platform Airbnb (a giant now valued at $95 billion). We conducted an online ethnography or netnography, analysing more than 300 user-generated reviews of rentals in major European locations, and conducted 17 interviews with Airbnb users and one with an executive from the platform.
And what we found wasn’t a happy, touchy-feely “community” (the official Airbnb term for its collective of users) engaging in the so-called sharing economy. Instead, evaluation produces what we call narcissistic entrepreneurs of the self. Peer-to-peer platforms provide users with a structure to assetise and maximise the value of private belongings and skills on marketplaces. As such they turn individuals into what Foucault would term “entrepreneurs of the self” – individuals who view themselves as their own capital, producer, and source of earnings.
Evaluation processes on peer-to-peer platforms stir up users’ narcissism because users rely on the peer evaluations that they give and receive to reaffirm their personal characteristics. On peer-to-peer platforms, users aren’t only engaged in monetary maximisation but they also seek to increase their own worth as a person and the evaluation infrastructure incites them to behave so. The public, overwhelmingly positive, evaluation system extends the mere review process and encompasses profile setting, and photos’ posting for instance. It functions as a mirror, allowing users to seek confirmation and validation from positive reviews while also experiencing distress from negative feedback.
Such evaluation processes consolidate a community that is only for show and have been developed to support an appealing, efficient market.
How does this work in practice?
The rise of narcissistic entrepreneurs
Airbnb requires users to set up an individual profile and encourages them to provide personal details. Whether users like it or not – and some interviewees stated it was “a drag” – they oblige, understanding that it is part of “the game”, and usually post cheery self-descriptions. This embodies transactions and anchors the use of the platform to a seemingly virtual community. It also broadens the stake of evaluation. Indeed, while the “location” criterion clearly applies to the home, “communication” applies to the person. So in a subtle way, the object of the evaluation shifts from the service to the user’s own worth.
The norm for reviews on the platform is strongly positive, with recurring comments of “amazing,” “lovely” and “wonderful” apartments. In fact, we noted a standard set at perfection or near-perfection with ratings never dropping below 4.5 out of 5 in the platforms’ largest cities in terms of ratings (Los Angeles, Paris, New York and London).
Actually, bad evaluations are taboo. Instead, users deal with unpleasant experiences (from smelly refrigerators to bedbugs or even theft) either through private e-mails with the other party or euphemistic public comments, so as not to hurt the other user. Still, the comments are outwardly positive, but users place subtle hints that can alert the rest of the community, without the risk of appearing overcritical.
How Airbnb reproduces class biases
So publicly criticising others on peer-to-peer platforms is problematic, also because potentially it defines the user giving the review as “bitchy” or “an angry nitpicker.” Conversely, giving out good reviews is described as a pleasure by users, like granting a prize. Hosts on the receiving end feel like they have been awarded a “gold star at school.” In our article, we cite the example of one user pleased to appear non-racist because he took a booking from an African-American. We conclude that reviews are material to make sense of the self and an opportunity to show an ideal projection of the self.
Digging deeper into the subtleties of the process, we explain that users also make sense of themselves through the fellow users they select by decoding weak signals in reviews. While the platform officially encourages the posting of personal information to reduce the uncertainty of the transaction, users do so by seeking out peers: people who seem like them. For example, Igor, a French person employed in what he refers to as trendy art galleries, clarified that his listing was solely in the English language to “avoid non–English speaking French people, the worst kind. They only do touristy stuff”. By steering clear of what he termed “losers,” he found comfort in his trendiness.
As a guest, Violet explained that when selecting accommodation, she seeks a comparable neighbourhood to her own. She argued that Airbnb is “all about people with money who want to stay in an apartment that belongs to someone like them, from the same socio-professional category, but who do not want to meet that someone!” However, not all users possess such reflexivity, with many relying on their “instinct” or claiming their open-mindedness when selecting hosts or guests.
Blatant discrimination
In stark contrast to this appearance of tolerance, many users exclude others based on racist or sexist considerations. As Clara revealed, “I know which nationalities I do not want staying in my home… ” Ultimately, the selection processes employed by Airbnb users reveal a significant gap between their professed open-mindedness and their actual inclination to choose users who resemble themselves. They end up discriminating more or less consciously based on social, racial or class grounds (spelling errors, racial stereotypes, perception of a guest’s home city as crime-ridden, etc.). They turn the assessment mirror back at others and, in doing so, rationalise processes of exclusion.
Implementing social reproduction schemes is one way to secure a perfect evaluation and limit risk. Behind the facade of community, online evaluation processes push users into schemes of social reproduction. Users’ narcissism then works as a cost-effective control infrastructure that keeps the market fluid.
Cheap and optimal control
Therefore, compared to evaluation in a corporate context, evaluation on peer-to-peer platforms guarantees cheap and optimal control. It is decentralised to users, and builds on reciprocity and narcissism so as to secure the fluidity of transactions without fuelling competition between users.
Beyond the specific context of online peer-to-peer platforms, this case says something about the pervasiveness of evaluation in our digitalised and algorithmic society. It pushes us into social reproduction and produces narcissistic entrepreneurs of the self, whose critical capacities are stifled in the face of evaluative mechanisms.
The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.
This article was originally published on The Conversation. Read the original article.
