Dynamic pricing can help both consumers and the environment
From big-box and grocery stores to airlines, “dynamic pricing” — where prices fluctuate in real-time based on supply and demand — is poised to become a larger part of the American shopping experience.
The more computational power companies gain by utilizing artificial intelligence, the more you’ll see shifting prices in local shops and restaurants. But, as we learned a few months ago when Wendy’s announced plans to increase its menu prices during its busiest hours, the customer backlash can be fierce.
That’s part of the reason AI’s potential to unleash across-the-board dynamic pricing is also gaining attention from policymakers and regulators. Just last week, the Justice Department’s top antitrust official warned that using AI to set prices could be viewed as “price fixing” and therefore be an antitrust concern.
But for those of us who care about sustainability and an inclusive economy, more dynamic pricing in our daily lives should actually be cause for excitement.
Today, most businesses use fixed pricing for everyday items. For example, grocery stores carry some excess inventory to manage fluctuations in demand. As a result, customers might pay slightly higher prices for each item (a “premium”) to have the goods available to them at a consistent price throughout the day and to cover the costs of perishable goods that go unsold. Traditionally, grocery stores have found that it’s more profitable to avoid surprising their consumers with fluctuating pricing based on supply and demand.
There are costs to this uniform pricing approach. Grocery stores experience extensive food waste due to consumers’ reluctance to buy expiring produce or other products. Shelves can be empty during times of high demand, such as just before a hurricane or snowstorm. Long checkout lines are common during customers’ rush-hour shopping stops.
Imagine if grocery stores and restaurants instead priced food the way airlines price fares. Airlines may not have the most popular business models overall, but their use of dynamic pricing has allowed many of us to obtain cheap flights and even travel around the world by booking in advance for lower-demand months. This strategy helps fill seats that would otherwise go empty, optimizing travel schedules, reducing per-passenger carbon footprints and providing savings for early planners.
Similarly, pricing algorithms in restaurants and grocery stores can identify low-demand hours or expiring food and assign a lower price tag, which makes buying food and going out more affordable for more people.
It’s not a new concept. Take, for instance, innovative tools like Too Good To Go, which utilizes information on low-demand hours for food at restaurants and perishables from grocery stores. It’s become particularly popular in cities like D.C., where young people live alone in high-cost areas with demanding jobs and can use quick and affordable meals.
Indeed, new research is providing evidence of this exact phenomenon. One study found that dynamic pricing discounts encourage consumers to purchase the oldest items, partly because such pricing discourages them from searching for fresher items. The study concluded that dynamic pricing and shelf rotation can reduce food waste by as much as 30 percent. This is consistent with another study that simulated dynamic pricing and found that it can reduce food waste by 21 percent.
So, while some of the fears surrounding dynamic pricing are understandable — no one wants to pay $20 for a gallon of milk — it is easy to forget that prices move both up and down. Better yet, when you add it all up, gains in efficiency tend to mean lower prices overall.
Environmentalists and those who care about food waste should embrace the change. So should anyone who likes a good deal.
Liya Palagashvili is a senior research fellow with the Mercatus Center at George Mason University and author of the chapter on dynamic pricing in “The War on Prices: How Popular Misconceptions about Inflation, Prices, and Value Create Bad Policy.” Revana Sharfuddin is a Mercatus predoctoral researcher.
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