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4/25: Daniela H. Saban – Online Algorithms for Matching Platforms with Multi-Channel Traffic

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IEOR Seminar Series: 4/25 with Daniela H Saban - Online Algorithms for Matching Platforms with Multi-Channel Traffic

 

Monday, April 25 | 3:30 pm - 4:30 pm
George B. Dantzig Auditorium (1174 Etcheverry Hall)

 

Description: 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 recommendation 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 our progress in implementing an improved recommendation algorithm on the VM platform. (Joint work with Vahideh Manshadi, Scott Rodilitz, and Akshaya Suresh)

 

Bio: Daniela Saban is an Associate Professor of Operations, Information, and Technology at Stanford University’s Graduate School of Business. Her research explores issues related to the design and operations of online marketplaces, including online matching markets and procurement platforms. Prior to joining Stanford, Daniela spent a semester as a visiting scholar in the Simons Institute for the Theory of Computing at UC Berkeley. She received her PhD in Decision, Risk, and Operations from Columbia Business School and holds a B.Sc. and an M.Sc. in Computer Science from Universidad de Buenos Aires.She currently serves as an associate editor for Management Science, Manufacturing & Service Operations Management (M&SOM), Mathematics of Operations Research, Operations Research, and Operations Research Letters.