Offer incentives to improve wait-list management — and matches.
What do parents hoping to enroll their children in a neighborhood daycare, patients awaiting organ transplants, football fans looking for season or playoff tickets, and applicants to public housing all have in common? They’re all in line — often waiting for their numbers to come up on long waiting lists for scarce resources managed on a first-come, first-served basis.
The main weakness of the waiting list as a tool for managing demand, says Professor Jacob Leshno, is that overloaded lists with long wait times discourage people from turning down offers, leading to poor matches. In public housing, for example, potential renters may jump at the first apartment offered even if it lacks access to good transportation or work options, lest another apartment not be offered for months — or longer. Season ticket seekers might settle for less desirable seats just to make sure they have the option to catch all their team’s games. When Sony’s Playstation 4 (PS4) was on backorder in late 2013, many consumers appear to have opted for Microsoft’s Xbox One.
You can use this research to make matching systems more effective.
Leshno modeled different types of matching systems to determine which would lead to the most effective assignments. The goal was to create the best matches for the most people possible — in public housing, for example, that means encouraging renters to turn down apartments that are not well suited for their needs, enabling others to consider them. The more people who can consider an apartment the more likely it is the apartment will be assigned to a renter who really wants it.
Leshno showed that it can be tricky to get people to decline bad options. Renters will trade off the possibility of getting a better against a longer wait, and will decline bad options only if they expect a better offer soon enough. Leshno analyzed different policies for managing the waiting lists, identifying a simple policy that ensures the greatest number of people avoid bad matches. To encourage people to avoid bad matches,wait listed people who decline their first offer are placed in a pool that gives them priority when a better option becomes available.
Because everyone in the pool has the same priority, and subsequent offers are made randomly, people who join the pool later are not disadvantaged. This leads the greatest number of people to decline bad options, minimizes mismatches, and creates better outcomes for all — whenever their numbers are called.
Jacob Leshno is assistant professor of decision, risk, and operations at Columbia Business School.
Read the Research
Leshno, Jacob. “Dynamic Matching in Overloaded Waiting Lists.” Working paper, Columbia Business School, 2014.