Bloomberg Businessweek May 27th 2022 5:00 AM EDT “Gamification Took Over the Gig Economy. Who’s Really Winning?” “Ride-share drivers say that the pandemic has exacerbated the imbalance with their overlords.” By Jackie Davalos and Drake Bennett
Read Bloomberg Businessweek for all the details.
Summary by 2244
Image from UBER.COM
Concept introduced. “Choice architecture (CA)” the idea dubbed by Richard Thaler that we can manipulate outcomes by proper positioning. As examples, candies in a store at eyesight to entice impulse buying and low minimum payment rates on credit cards to make it easier for users to choose that option and thereby start or continue paying interest on their balances. Thaler argues that CA should also be used in a socially beneficial way like “automatically enrolling workers in 401(k) plans.” CA is being used by Gig companies as well to entice drivers and other gig workers to take transactional assignments.
As it turns out, huge databases, like those available from ridesharing firms, combined with machine learning are helping the “overlords” of these eCommerce firms manage. It allows the likes of Uber to scale up and down to demand quickly and to gain and maintain revenue and profit control over their drivers. By using the algorithms built with the help of data and AI, Uber has been able to entice their “non-employees/contracted workers,” to repeatedly, on a transactional basis, take the carrot Uber wanted most of the time. Essentially this is a “command and control structure, even while [corporations] framed its drivers as independent, self-directed and entrepreneurial.” The Ubers of the world achieved the ability to “take a cut of people’s labor without putting them on staff.” Other examples cited in the article include; Handy, Rover, Grubhub, DoorDash and Uber Eats.
While being an independent worker sounds great and is helpful in granting flexibility in working hours, gig workers have essentially “found themselves managed by incentives and code” that fall short of completely working on their own terms. The work assignments are allocated by “Sophisticated software [that] holds real-time auctions every second, matching prospective customers with drivers or couriers in a vast marketplace.” For companies, there’s less risk as they don't have to on-board and off-board real employees as the market changes. For gig workers, it’s dubbed “nudge theory.”
The ongoing issue for Uber drivers is usually having to accept a rider without much information. If you were working independently you would make a decision based on knowing the parameters of the potential rider’s request. At a minimum you would know in advance where you would pick them up and where you would drop them off. Many drivers claim things are getting worse as they believe there are more variables to consider and that the algorithm rules “are constantly changing.”
At the same time, giving the ability to track all driving activities, Uber and others “keep tabs on [the driver’s] every move: the percentage of available pickups they accept; the time of day they typically work; the neighborhoods they prefer; the ratings passengers assign after a ride.” With a surge in ride demand driver’s are fed incentives to increase pay or to reach the next driver tier. Rising a tier may bring added benefits like “the ability to see a trip’s duration and direction.” Like any job one can be rewarded based on performance. In the case of ride-sharing the metrics are crystal clear not fuzzy like other jobs. The metrics include “maintaining high customer approval ratings, and keeping cancellation rates low.” Reportedly the “thresholds for qualifying for various perks can be stringent…” Uber has responded by saying “‘we fundamentally disagree with the premises’ that the driver pain points have gotten worse.”
Besides the anecdotal complaints of drivers, Pew Research “found that fewer than half of gig platform workers said they understand how their pay was calculated.” Reportedly, “before expenses, driver earnings averaged a little more than $24 an hour in March.” Gas has increased “almost 50%, devouring take-home pay.”
Coming out of the pandemic and now “wait times and fares remain elevated, suggesting constrained supply.” Company revenues have increased but it seems “that [the] once subsidized cheap rides for customers are no longer tenable.”
Gigging the Gig Economy
Influencers have been working, for nearly five years now, to keep up to date and keep gig workers informed as these platforms evolve. Mentioned are Rideshare Guy (Harry Campbell), Rideshare Professor (Torsten Kunert) and even a startup called Solo (reportedly founded by former Uber executives). An experienced driver, Sergio Avedian claims that “‘I like the game. If there’s a way to beat them, I’m going to figure it out.’” Sergio co-hosts a YouTube show “Show Me the Money Club” and “charges $75 for a 45-minute call” to share his knowledge.
Interestingly “86% of drivers work across multiple apps” making it harder for individual gig platforms to be inflexible on payment schemes. Reportedly, these platforms are looking for additional ways to improve retention, by putting the “driver experience…at the center of what we do” but also by creating other programs similar to Amazon’s and Walmart’s efforts to “provide free college tuition for select frontline workers.”