INFORMS Journal Manufacturing & Service Operations Management New Study Key Takeaways:
- User behavior shows that when a user has several matches, they are less likely to “like” other profiles.
- Accounting for user preferences and current user experience, a new algorithm can increase the number of matches by at least 27%.
- These findings can be applied to freelance or task-based work, ridesharing and travel accommodations.
BALTIMORE, MD, September 8, 2022 – Online dating is one of the top ways people meet in 2022. That said, matchmaking – online or offline – is never a perfect process. New research published in the INFORMS journal Manufacturing & Service Operations Management showcases a new algorithm to increase dating site matches by analyzing individual user preferences and whether the user currently has a lot of matches.
The study, “Improving Match Rates in Dating Markets through Assortment Optimization,” was conducted by Daniela Saban of Stanford University, Ignacio Rios of the University of Texas at Dallas and Fanyin Zheng of Columbia University. The researchers used data from a dating site that only allows users to view a certain number of profiles per day, no matter how many times they log on. But how do you choose which profile to show to a user and when?
“Users become pickier if they currently have a lot of matches, so their probability of liking a new profile decreases,” says Saban, an associate professor of operations, information and technology in the Stanford Graduate School of Business. “By incorporating this user history and individual preferences, our new algorithm can increase the number of matches generated by at least 27%.”
“There’s a lot of emphasis on correctly understanding user preferences and matching that way, but that’s not all that should be considered. Our work shows there’s a lot of improvement that can be made to better understand how users’ decisions change based on their recent experience on the platform. Keeping this in mind, we can increase new matches by carefully “timing” when we show users some profiles that are more likely to end in a match. If a user has had many matches recently, then it is better to wait to show them profiles that are likely to generate a match, and in the meantime show other profiles that are less likely to end in a match,” says Rios, an assistant professor in the Naveen Jindal School of Management at UT Dallas.
The researchers emphasize that these findings are also relevant to other types of online matching platforms, including those for freelance or task-based work, ridesharing and travel accommodations.
About INFORMS and Manufacturing & Service Operations Management
INFORMS is the leading international association for operations research and analytics professionals. Manufacturing & Service Operations Management, one of 17 journals published by INFORMS, is a premier academic journal that covers the production and operations management of goods and services including technology management, productivity and quality management, product development, cross-functional coordination and practice-based research. More information is available at www.informs.org or @informs.
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