Editor's Note

What’s Up, Uber?!

We found no shortage of reasons for Uber to be criticized over the past 2 years. Claims of sexual harassment, misogyny and discrimination. A reported threat to smear the reputation of a journalist who was critical of the company. Charging riders inflated rates during a terrorist attack in London. Claims that data about people were collected after they deleted the Uber app from their mobile device. Charges that the company incentivizes Uber drivers to work when they’re fatigued.

These can be reasons for why you might not want to solicit the ride-sharing, or ride-hailing, company. Add to this: A pricing strategy that is just plain discriminatory from a consumer standpoint: so-called personalized pricing.

You might recall that, in this same space in our July/August 2017 issue, I wrote in “Prying Eyes” about our report on consumers’ digital privacy, or lack thereof. An element of that editorial explained that the data that online retailers collect are plugged into algorithms to produce prices for goods that are tailored to individuals. I wrote, “How angry it makes me to know that a price that I find when I’m shopping for a product isn’t the price that is provided to every consumer, because the data might indicate that I’m more likely to buy a product than another consumer is and, therefore, the price might be higher for me.”

Uber’s personalized-pricing model would charge higher fares to customers whom Uber believes have the means to pay more. As we explain in “The Shifting Ride-Share Marketplace: Fare Game,” Uber’s algorithm might decide that a person who beckons an Uber driver to an affluent neighborhood to catch a ride to an upscale restaurant is able to pay a higher fare than is a rider who asks to be picked up in a poor neighborhood for a ride to Aldi.

Economists point out that personalized pricing, or price discrimination, which can be broken into three types, isn’t uncommon. (Limited space here prohibits an explanation of what distinguishes first-degree personalized pricing from second degree and third degree, but the form that Uber is testing falls into the last category.) Economists even note that society can benefit from such a practice.

“Third-degree [price discrimination] can actually increase consumer welfare if it permits firms to enter markets that wouldn’t otherwise be economically viable,” says Jordi McKenzie of the Department of Economics at Macquarie University. By this, McKenzie refers to the taxi industry. “Uber has brought competition to a monopoly industry, and the taxi industry is having to up its game to compete,” he says.

Sorry, but I’m not convinced. I join Scott Duke Kominers, who is an associate professor at Harvard Business School, when he doubts that Uber’s personalized-pricing goal is to improve market access. Kominers offered the following suggestion in an op-ed piece that was posted at Bloomberg.com as a possible way to outsmart Uber’s algorithms: “We can try to trick its algorithms into believing that we have low willingness to pay” if we inject false signals into the data stream. “We could open the app at random, check the prices on routes we sometimes take and then close the app without calling for a ride—just to make ourselves look price-sensitive,” he says. Kominers adds that considering and sometimes taking rides to unusual locations also might baffle Uber’s estimates of your ride preferences.

“If Uber’s customers start trying to game the pricing algorithms, that could throw off Uber’s demand estimates, leading to uncertainty not only in pricing but also in availability . . ..”

I like it. Maybe we should start a (ride) hail storm!

Rich Dzierwa, Editor