That’s the question users (referred to as “hosts”) on platforms like Airbnb and the car-sharing company Turo face when deciding when to list their homes, vehicles, and other items for rent.
It’s also a question of interest to Achal Bassamboo, a Kellogg professor of operations. Platforms like these are estimated to drive revenue of $335 billion by 2025, so it’s important to understand their dynamics. While past research has looked mainly at how buyers act on such platforms, Bassamboo and Kellogg doctoral student Neha Sharma were interested in seller behavior: specifically, “whether they list [their items] as soon as they know they have availability or wait until later to commit,” Bassamboo says.
There are pros and cons to both approaches. If the seller lists an item further in advance of its availability, they’re increasing the possibility that their item will be rented. But it may also mean lower revenue because demand may not be as high or the platform may offer discounts for early booking.
In contrast, if they wait to list until closer to the actual availability date, they risk not renting it out at all. But they could also enjoy greater revenue because buyers may have a more urgent need—and may be willing to pay more, as illustrated by the “surge pricing” many platforms charge.
With collaborators Sumanta Singha and Milind Sohoni of the Indian School of Business, the researchers created a model of seller and buyer behavior on a hypothetical platform. They found that sellers tended to wait until close to the time their item was available before listing it, in hopes of maximizing their profits. But over time this behavior resulted in low availability of items at specific times and lower returns for both sellers and the platform.
The best solution, the researchers found, was for the platform to offer sellers incentives—like a higher percentage of the sale—to list earlier.
A model platform
The researchers’ questions about the timing of listings were sparked by real-world observations.
Working with an India-based platform that enables car owners to rent out their vehicles to other users—with over 3,000 rentals completed per day—they saw that as renters gained more experience with the platform, they tended to list their cars later, closer to the time they would actually become available.
“We wanted to know if that was good for the platform, and whether it made sense for the platform to consider different types of contracts and incentives, given that seller behavior,” Sharma says.
To explore these questions, the researchers created a model of a platform on which prices would be dynamically adjusted based on capacity. Larger capacity on the platform—such as more cars to rent—generally resulted in lower prices. That is, unlike other consumer-to-consumer platforms, like Airbnb, the researchers’ platform sets prices rather than the seller.
“The platform sets the prices,” Sharma says, “but it takes into account the state of the world”—including factors influencing supply, such as volume of offerings available, and demand, which can be driven by factors like time of year and weather.
In their model the platform also takes a fixed percentage of the selling price as its fee, regardless of when the listing is made. As for the customers, they fell into two broad categories in the model: those who wanted to book well in advance of their need, and those who sought to secure a booking just in time for their need. Similarly, users could list well in advance of expected availability or just before.
The waiting game
As on the real-life rental-car platform, under some demand distributions the model showed that users tended to wait to list their items until very close to the time they would be available. “They saw no point in getting their asset booked in advance and getting a lower price for it,” Sharma says. “So they decided to commit later, when they felt they could get a higher price.”
Not surprisingly, this wasn’t ideal for buyers, especially those seeking early bookings. “If all the suppliers are listing later, it results in service breakdowns for buyers who want to get the asset early on,” Sharma says. “They come on the site and find nothing available.”
In line with this, they found that customers who wanted to book very close to their time of need had 60 percent more options than those who sought to book early. “It’s really bad that a large part of your customer population cannot be served now because of the behavior of the suppliers,” Sharma says.
Moreover, as supply grows when users list closer to a given date, these users and the platform both lose because the large supply means lower prices. Essentially, even if individual users believe they’ll make more money by waiting to list, doing so en masse means that they and the platform ultimately make less money.
“If some of the supply had come online earlier,” Sharma says, “it could have meant higher prices for the platform and a higher service level.”
A matter of incentives
What can a platform do to drive the best outcomes?
“It’s no surprise that if the platform takes full control of when to list items, it will come out ahead,” Bassamboo says. But that may not sit well with users who are renting out their property and could potentially reduce supply if people decide not to list their offerings.
A second, more feasible solution has to do with sharing information, Sharma says, though it is not ideal: “The users who are renting out their property have some belief about what demand is going to look like. But the platform can provide them more information about the demand distribution, and that will help them decide when to list and prevent service breakdowns and lower revenue for both the users who are renting and the platform.”
Still, this approach can be complicated as it’s unclear exactly what information to share, and owners who are listing have other options, such as third-party tools that help them understand demand patterns.
A third, and better, option is for platforms to offer contracts that incentivize users to list earlier. For example, the platform could take a lower percentage of the rental prices for users who list well in advance of availability and a higher percentage for those who wait until the last minute. “We find that’s the optimal thing to do,” Sharma says.
Indeed, the car-rental platform the researchers worked with is already considering how to change their contracts and incentives based on the findings.
“Using the percentage this way better aligns incentives of both sides of the markets (users who are listing and users who are renting),” Bassamboo says. “The renter gets to rent the product earlier and for less money, and the owner of the vehicle gets to enjoy a bigger percentage of the rent collected by the platform.”