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How to learn to stop worrying and love surge pricing

Uber drivers in a rideshare waiting lot near TPA. (WFLA)

Many of us are accustomed to “surge pricing” when requesting Ubers during rush hour or booking last-minute flights over Christmas. But these types of dynamic or algorithmic pricing strategies are now creeping into daily life — such as in restaurants, gyms and even grocery stores. A recent Wall Street Journal article reported on a customer’s anger when his local bowling alley charged him three times the normal rate using a demand-based, algorithmic pricing strategy.

Not surprisingly, calls to regulate companies that use algorithmic-based pricing are now on the rise. And while it’s fair to say that customers aren’t enamored with this practice, demand-based pricing strategies tend to make us better off. 

Economists agree that the main benefit of dynamic pricing strategies is that it can help balance supply to meet customer demand. No case is clearer than that of ridesharing, where dynamic pricing strategies and a flexible labor supply are at the core of the business.

For example, when there is a mass transit malfunction in your area, the price of your Uber will undoubtedly increase. Beyond irritating customers, this algorithm-generated high price serves two important purposes: First, some customers who merely had a slight preference for the Uber may reconsider it and decide to walk instead, cancel evening plans or stay longer in the office until the price falls again.

In other words, surge pricing is a way of asking customers: “Do you really need to take this ride right now?” This rationing by price helps to minimize the number of riders using the service frivolously during the high-demand time. And it helps to ensure that those who need or value the rideshare most take that ride.

The second effect of the higher price is that it serves as a signal to Uber drivers to get out on the road. There are people who need the ride, and they are willing to pay handsomely. Drivers see that they can make good money servicing a particular area at a particular time, and this encourages them to supply rides where they are needed.

Indeed, in one study, economists found that drivers extended their sessions and provided significantly more rides when they saw surge pricing in a particular geographic area. Another study’s comparison to New York City taxicabs, where there is no dynamic pricing (only slight peak-hours fare increases twice a day), showed that the number of Uber and Lyft rides rose by 22 percent during rainy hours compared to just 5 percent for ordinary taxis.

This is exactly what ridesharing companies strive to do: be seen as a reliable ride by ensuring that there are enough drivers available to meet the demand.

The ridesharing company Gett’s experimentation with fixed prices – which earned it the title of “Uber without Surge Pricing” – quickly failed in New York City and demonstrated what happens without dynamic pricing in a market where customers demand immediate service. Gett users often had to wait longer than 45 minutes to find a ride at peak hours or on rainy days because not enough drivers were available.

On the surface, the argument for dynamic pricing might seem weaker when supply is fixed. For example, is it fair for companies to charge exorbitant prices for hotel rooms and concert seats? Take a recent Bruce Springsteen concert where tickets were at one point selling for as much as $5,000.

What many people tend to forget is that fluctuating prices can go both up anddown — and indeed, when fans refused to pay that much, prices did start to drop. In the end, more than half of all fans paid less than $200 per ticket for that concert. Airline tickets have become affordable for many millions of Americans who take advantage of low prices by booking far in advance and during off-peak hours.

No one wants to see the price of an apple fluctuate hour by hour or soar to $15 during grocery shopping rush hour. But few will complain that some stores are already starting to experiment with demand-based pricing strategies by using an algorithm that drops the price of baked goods or produce as they near their expiration.

So, while ridesharing-style dynamic pricing strategies in grocery stores are unlikely to become the norm, mild uses of demand-based pricing strategies in everyday life can go a long way toward meeting customer needs, reducing waiting times and even minimizing food waste. Let’s not dismiss the idea before we see what it can do.

Liya Palagashvili is a senior research fellow with the Mercatus Center at George Mason University.