Gig economy work has been presented as flexible, independent work. However, many workers want predictable earnings. Segmenting platforms by risk appetite might be one solution.
Aswath Damodaran, our business school corporate finance professor, calls risk the “feeling in the pit of your stomach as you watch the only stock you own meltdown and you can’t get through to your broker.” Both accurate and poetic.
The risk in investing is well understood. But what about the risk inherent in our livelihood?
The rise of marketplaces
The past decade has seen the emergence of a new business model – the online marketplace. This model has taken many forms – aggregators, social networks, and gig-economy platforms. However, at their core, they are a way for companies to facilitate transactions between buyers and sellers. Record-low unemployment drove many workers to these platforms for higher pay and flexibility. Now, with the world thrown into chaos over COVID-19, many platform economy workers are reckoning with the downsides of the risk they assumed to work in this brave new world.
Rewarding risk
Here’s the thing though – platforms reward risk-taking behavior. Below is a graph from an article about the variability in earnings for Uber X drivers. It shows the hourly earnings vs. the number of hours worked by Uber X drivers in 2014.
Let’s unpack this. Drivers who drive fewer hours see much higher variability in earnings. They experience very high-highs but also very low-lows. On the other hand, drivers who drive full time (greater than 40 hours a week) see slightly higher average earnings but don’t experience as many high-highs.
Note: That slight upward trend in average earnings per hour could be due to a number of factors: quantity-incentives from the platform, more seasoned drivers earning better tips, or drivers who choose to call it quits after completing a trip with a large payout.
An Uber driver’s potential earnings are dependent on three critical factors – the part of town they’re in, the demand for taxi rides at a particular time in that part in the city, and the competition from other Uber drivers. Thus, Uber drivers’ earnings depend heavily on their ability to pick a time and place in the city where demand is high, yet competition is low. Let’s call these “time-space” combinations. Drivers who drive longer than 40 hours-a-week can allocate their time over many more “time-space” combinations, effectively hedging their bets. Limiting their upside, but also their downside. While driving part-time is the equivalent of being invested in only one stock waiting for it to meltdown, diversifying across a higher number of hours is the equivalent of buying the Vanguard S&P 500 ETF and forgetting about tracking your portfolio.
These risk-reward trade-offs appear time and time again in online marketplaces. Here’s a line from a post on the Airbnb blog advising hosts about how to pick their cancellation policy:
“You can offer a non-refundable option for 10% less, alongside Flexible or Moderate. Not only will this strategy help safeguard a majority of your revenue, it may also lead to more bookings. Marketplace test data shows that hosts who offer this option earn more revenue when compared to offering just Flexible or Moderate alone.”
– How to choose the right cancellation policy for you, Airbnb Blog
The translation: Protecting yourself from the downside comes at a cost. To be precise – 10% of your nightly rate.
Building for risk
Until now, most online marketplaces have played a delicate game of attempting to build for both the part-time workers (risk-friendly workers) and the full-timers (risk-averse workers). However, the COVID-19 pandemic has made it abundantly clear that gaps exist in the market.
Both Uber and Lyft encourage drivers to “be [their] own boss.” But for a majority of workers, “consistency of earnings” remains a top concern.
For now, the question remains – will these platforms continue to dominate in a world where workers become increasingly risk-averse or will new platforms emerge that build-for-risk?
This is part 1 of a series that we’re writing about risk in online marketplaces. You can click here to see part 2.
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I’m a product and strategy professional with 6+ years of experience in consumer technology and strategy consulting. I write about product management, business strategy and my experiences as a young professional in consumer and B2B software.
I am a finance and strategy analyst with an entrepreneurial background and research experience at the Federal Reserve. I am interested in tech products, network economics, and corporate finance.
Historically businesses have survived risk whereever there is high friction to migrate, lack of options and due to loyalty. However some products seem to successfully tackle for each of these.
Nice article! 👍