Re-designing Recommendation on VolunteerMatch: Theory and Practice
In this talk, I describe our collaboration with VolunteerMatch (VM), the largest nationwide platform that connects nonprofits with volunteers. Through our work with VM, we have identified a key feature shared by many matching platforms (including Etsy, DonorsChoose, and VM): the supply side (e.g., nonprofits on the VM platform) not only relies on the platform’s internal recommendation algorithm to draw traffic but also utilizes other channels, such as social media, to attract external visitors. Such visitors arrive via direct links to their intended options, thus bypassing the platform’s recommendation algorithm. For example, of the 1.3 million monthly visitors to the VM platform, approximately 30% are external traffic directed to VM as a result of off-platform outreach activities, such as when nonprofits publicize volunteering opportunities on LinkedIn or Facebook. This motivated us to introduce the problem of online matching with multi-channel traffic, a variant of a canonical online matching problem. Taking a competitive analysis approach, we first demonstrate the shortcomings of a commonly-used algorithm that is optimal in the absence of external traffic. Then, we propose a new algorithm that achieves a near-optimal competitive ratio in certain regimes. Beyond theoretical guarantees, we demonstrate our algorithm’s practical effectiveness in simulations based on VM data. Time permitting, I will also report on implementing an improved recommendation algorithm on the VM platform and present data from our ensuing experimentation. (Joint work with Scott Rodilitz, Daniela Saban, and Akshaya Suresh)
Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4036904
Vahideh Manshadi is an Associate Professor of Operations at Yale School of Management. She is also affiliated with the Yale Institute for Network Science, the Department of Statistics and Data Science, and the Cowles Foundation for Research in Economics. Her current research focuses on the operation of online and matching platforms in both the private and public sectors. Her research has been recognized at multiple paper competitions across various INFORMS communities, including Public Sector OR, Auctions and Market Design, and Manufacturing & Service Operations Management. Professor Manshadi serves on the editorial boards of Management Science, Operations Research, and Manufacturing & Service Operations Management. She received her Ph.D. in electrical engineering at Stanford University, where she also received MS degrees in statistics and electrical engineering. Before joining Yale, she was a postdoctoral scholar at the MIT Operations Research Center.