Web3 for the gig economy


This guest post is authored by Mark Bivens. Mark is a Silicon Valley native and former entrepreneur, having started three companies before “turning to the dark side of VC.”

He is a venture capitalist that travels between Paris and Tokyo (aka the RudeVC). He is the Managing Partner of Shizen Capital (formerly known as Tachi.ai Ventures) in Japan. You can read more on his blog at http://rude.vc or follow him @markbivens. The Japanese translation of this article is available here.

Image credit: RudeVC

I’ve been ruminating on how Web3 could potentially transform gig economy businesses — e.g. Uber, Lyft, Airbnb, Upwork, Taskrabbit, Fiverr, etc. — and whether applying token economics to these activities would even make sense.

Two encounters over the past week have persuaded me that a decentralized model could address some of the failings of these established platforms.

The first encounter was with the founder of one of the world’s newest Web3 ride-hailing projects. The second was with a research paper entitled, “Expanding the Locus of Resistance: Understanding the Co-constitution of Control and Resistance in the Gig Economy,” published by Hatim Rahman, Assistant Professor of Management and Organizations at the Kellogg School of Management, and Wharton management professor Lindsey Cameron.

Rahman and Cameron suggest that the 5-star customer ratings system of these gig economy platforms is broken. They argue that the disproportionate importance of the customer review system subordinates gig workers to essentially a ‘digital boss’, toward whom the workers have little recourse once the rating is finalized and published. The customers, in contrast, do not bear the consequences of negative reviews as acutely as the workers do.

As a result, gig workers devise ways to resist such authority. Tactics can include: carefully vetting a customer’s behavior and prior reviews before accepting the gig, offering discounts once the job is underway in order to elicit a high rating, or even canceling the job before completion in order to avoid a negative review.

As currently structured, the Web2 ratings system abdicates power to people who do not possess a vested interest in the gig worker’s business.

Improving alignment of interests between gig worker and customer strikes me as a way that decentralization can transform these platforms.

Let’s focus on on-demand ride hailing. It’s hard to argue that this concept is not innovative, yet businesses like Uber and Lyft have never reached sustained profitability. Partly this is due to regulatory capture, i.e. when the status of drivers was deemed to be that of employees rather than independent contractors, hence requiring the platform to provide substantial benefits, the economics of the model broke down. Yet despite the regulatory impositions, drivers still struggle to make ends meet, keeping all apps active in order to maximize their driving throughput and undermining any particular loyalty to a single platform.

The thesis of these decentralized ride-hailing projects is essentially that token economics will repair the broken model. Although there still appears to be some experimentation around the specific tokenomics among these new contenders, from what I can understand both drivers and riders will earn platform-specific tokens as they use the service. Token grants could be structured to reward both frequency of usage and longevity, thus fostering loyalty from both the drivers and the riders. If the right to drive for the platform is embedded in an NFT, say, then this right could be transferable and appreciate in value just as the taxi medallions used to do.

Of course, the devil is in the details in the implementation of these models. However, decentralization brings a new dimension to the economic model of the business, which could render it viable again.

We’re at a moment where Web3 has somewhat fallen out of favor as the trendy new thing (albeit not yet in Japan where we’re still catching up). In my experience, when the spotlight on a particular innovation shifts away, this is often the best time for research and reflection on the transformative potential of it.