Thousands and thousands of People faucet their smartphone screens each day to order rides, groceries, or dinner, hooked on the seamless comfort of the gig economic system.
But beneath this frictionless interface lies a brewing warfare.
On one aspect, consumers are squeezed by risky and erratic surge pricing, which adjusts to mirror spiking demand or dropping provide. Alternatively, gig employees face manipulative algorithmic payouts, erratic schedules, and the skyrocketing costs of retaining their automobiles on the street.
For years, gig-economy executives have wielded the blunt instrument of surge pricing to handle their workforce. It treats human labor as a frictionless commodity. The logic is easy: If the variety of drivers drops, throw more cash into the pool, and provide will appropriate itself.
However there’s an enormous catch. This technique has created extreme market friction, leaving customers annoyed by excessive costs and platforms scuffling with widespread driver shortages. Compounding the problem, fresh research reveals that drivers don’t truly profit from surge pricing and are more and more demanding compensation reforms.
A working example is Massachusetts, the place that frustration led to the launch of the first U.S. gig-worker union in Could 2026. It adopted a 2024 settlement between the state and rideshare platforms that assured a minimal wage of $34.48 an hour for Lyft and Uber drivers.
As business professors who research consumer psychology and supply chains, we analyzed 2 million supply duties, accomplished by greater than 70,000 drivers for a Fortune 500 retailer from February via April 2022, to unpack this drawback. We found that gig employees aren’t simply pushed by cash. They’re refined micro-entrepreneurs who carry out a strict “psychological audit” of each single job to see if it’s value their time—earlier than hitting the “settle for” button.
By understanding these hidden frictions amongst drivers, platforms can cease overcharging customers and begin designing work that aligns with the drivers’ preferences and makes their jobs more satisfying.
The three dimensions of friction
Domingo, an Uber driver who declined to offer his final title, captured these systemic frictions in a 2023 CBS interview.
“It feels just like the algorithm is turned towards you,” he mentioned. He recalled an evening when he had accomplished 95 of the 96 journeys required for a $100 bonus, solely to be left ready 45 minutes in a busy space for his remaining experience. That led him to imagine the platform was deliberately baiting him to remain on-line.
This instance underscores why it’s so necessary to contemplate the driving force’s perspective to grasp why conventional money incentives in surge pricing fail.
With inflation squeezing their margins and rideshare platforms demanding a large share of their earnings, a driver’s split-second choice to simply accept a fare is a high-stakes calculation of enterprise survival.
It’s not simply the cash
In impact, drivers think about greater than the top-line greenback determine, we found. As an alternative, they evaluate three distinct factors.
First is what we name the “effectivity paradox.” Drivers are aware of their pay-per-mile ratio, in order that they deal with their private autos like small company fleets the place each mile is a capital expenditure. By that logic, if a route is lengthy and inefficient, platforms ought to merely increase drivers’ pay and cross on the fare hike to the passenger.
However it seems that greater pay alone doesn’t assure {that a} lengthy, remoted route is value it for the driving force. We discovered that when compensation rises from $7 to $45 per experience, drivers have been solely 50% extra inclined to simply accept “inefficient” duties, corresponding to lengthy distances with few drop-offs. In contrast, their acceptance charge of “environment friendly” duties, protecting brief distances with dense clusters, shot up by 70%.
Why did drivers choose high-density quantity over uncooked mileage premiums? As a result of they clear extra prospects and acquire greater earnings, which appears like a win for his or her microbusiness. To acknowledge this calculation, platforms ought to group rides and deliveries into tight, localized clusters as a substitute of closely subsidizing lengthy, remoted routes, in recognition that drivers prioritize route effectivity.
The second issue is what we name the “uncertainty tax.” Past the odometer, rideshare drivers value in behavioral and operational uncertainty. This friction is most seen throughout advanced pickups, corresponding to chaotic airport terminals or large sports activities stadiums, the place they usually must circle round and round earlier than discovering their buyer.
To drivers, this type of pickup is a risky danger that drains time and burns gasoline, one other hidden tax.
Surge pricing tries to incentivize drivers to simply accept a high-friction pickup. However there’s a greater means: Platforms may let passengers choose into “low-friction hubs,” like strolling one block away to a straightforward pull-off zone, in alternate for a lower cost. This reduces the price of uncertainty for rider and driver alike.
And final, there’s the “sundown threshold.” The ultimate and most inflexible issue is the private and bodily value of being on the street after darkish. Regardless of the strain to generate profits, gig drivers closely worth their security and private life above the additional greenback earned.
Our analysis confirms that the desirability of a supply job drops off sharply at sundown, whatever the base pay. Fatigue and security considerations create an operational drag that cash alone has a notoriously onerous time overcoming. To deal with the reluctance, platforms may shift nonurgent night orders—say, for groceries—to the next morning. This strategy mitigates the necessity to supply expensive incentives to exhausted drivers working previous sundown.
What about customers?
As a result of algorithmic platforms cross the price of driver friction on to the consumer, customers hate surge pricing. While you encounter an enormous upcharge, the algorithm isn’t simply telling you that there are too few drivers. It’s telling you that your particular order represents excessive friction for the accessible fleet.
However customers can take steps on their very own to restructure their orders and reduce the driving force’s “psychological audit” penalty.
A technique is to keep away from the uncertainty brought on by unattended supply. With measures like choosing the “go away at my door” possibility or offering clear gate codes, the patron can scale back the “uncertainty tax” imposed on drivers. When algorithms see these frictions falling away, the necessity for a driver premium plummets, deflating the surge value.
One other means is to rethink timing and scheduling, basically what platforms may do on their aspect. Particularly, customers ought to keep away from peak sundown and dinner rushes for nonperishable items.
Ordering gadgets for a versatile morning supply window, for instance, makes essentially the most of “good postponement.” Algorithms can maintain nonurgent gadgets for the subsequent morning, when extra drivers can be found and able to take orders, for a lower cost. The night “inconvenience premium” disappears.
Lastly, customers ought to be good about order bundling. As an alternative of inserting three separate orders all through the week from totally different native spots, for instance, they’ll consolidate purchases right into a single drop. This straight aligns with the driving force’s want for high-density, low-mileage clusters, successfully neutralizing the “effectivity paradox.”
A win-win final result
Finally, our analysis reveals that gig employees and customers alike can create a win-win final result by shifting their approaches.
Shoppers can get monetary savings by decreasing uncertainty, bundling and pooling orders strategically and timing them to keep away from the sundown penalty. And drivers can acquire extra management over the algorithm and their earnings—prioritizing density over distance, holding out for greater baseline premiums on advanced deliveries, and aligning their schedules with daylight when security dangers and bodily fatigue are lowest.
Simply as necessary, drivers are taking issues into their very own arms on the political stage. Together with the profitable unionizing push in Massachusetts, rideshare drivers secured the correct to organize in California in 2025, and Illinois is considering comparable laws.
Christopher S. Tang is a professor of provide chain administration on the University of California, Los Angeles.
David Dobrzykowski is a Bickerstaff Chair and professor of provide chain administration at Auburn University.
Nicolo Masorgo is an assistant professor of administration at Miami University.
This text is republished from The Conversation below a Inventive Commons license. Learn the original article.
