The classic ‘Market for Lemons’ paper published by George Akerlof is an often cited one when it comes to government regulation.  It highlights how information deficiencies can lead to market failures, and therefore require regulation.

The paper highlights how used car buyers know that bad cars exist (lemons), but are ill equipped to know where they are, which lowers their willingness to pay for cars.  This uncertainty in the demand side then discourages those on the supply side from offering up high quality cars.  In other words, everyone loses.

Trust is a major component of overcoming this issue, and it’s a topic I’ve touched on a number of times in terms of the sharing economy, with services such as Traity and eRated emerging to try and provide accurate reflections of reputation online.

A recent paper highlights how the sharing economy, and the kind of services mentioned above, are doing the kind of job that regulators could only have dreamed of, and indeed have largely failed at over the past few decades.

How the sharing economy solves the market for lemons

The sharing economy has heralded a fascinating exploration of trust.  It sees millions of transactions completed with a level of trust in strangers that would have seemed bizarrely foolhardy even a few years ago.

The paper argues that the sharing economy has provided just the kind of market based solution to the lemons problem that Friedrech Hayek promoted.  Indeed, the rise of the sharing economy could be seen as the natural exploitation of such a weakness in the market.  It was less a failure as an opportunity.

The reputation that is at the heart of the sharing economy acts as a powerful incentive to both constrain opportunistic behavior, and to also incentivize honest transactions between people.

That the sharing economy has proved so adroit at solving both the reputation issues inherent in the market and also the asymmetrical information challenge has been fundamental to its success.

Platform based methods

The paper highlights the various platform level attempts to improve trust in the system, including the insurance offered by AirBnB and Turo.  These moves provide both seller and buyer with a degree of security, thus improving the lot of both sides.

It also documents the way various platforms are using big data algorithms to better understand transactions.  For instance, AirBnB will monitor numerous elements of a transaction for signs of money laundering or reputation rigging, with a team of 80 or so people tasked with ensuring the validity of transactions undertaken via the platform.

Peer based methods

There are also a number of peer to peer based mechanisms for communicating trust.  These primarily consist of the ratings and feedback that are commonplace throughout the web, from Amazon to Yelp, with many of the social channels provided for customer feedback now the best way to achieve closure on your concerns.

The sharing economy has arguably made this method of analysis even more prominent however, with both parties using such ratings to gain information about the other.

By providing feedback about behavior, penalizing negative actions, signaling desired outcomes, and rewarding users, reputational and recommender systems are providing socializing functions and becoming valuable tools for organizing online environments.

Such mechanisms have made transacting via the sharing economy remarkable safe and reliable, with the 0.01% ‘success’ rate on AirBnB common throughout the sector.

The paper provides an excellent insight into the various aspects of trust in the sharing economy, and indeed some of the challenges that are still to be overcome.  Well worth a read if you work in this area.