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Yanhao "Max" Wei

Assistant Professor of Marketing
Building
HOH
Room / Office
306

PhD, University of Pennsylvania; BS, Bocconi University

Max develops models to analyze market data. One of his research areas focuses on the network structures in markets, deriving insights from the connections between consumers (social networks) as well as products (e.g., product similarity, combinatorial creativity). The other area of his research is at marketing-finance intersection. He studies how consumers or investors make decisions in financial markets, such as mutual funds, cryptocurrency, crowdfunding, and credit scoring.

Max's research has been published in Management Science, Marketing Science, Review of Financial Studies, Economic Journal, and Quantitative Marketing & Econ. He teaches the undergraduate marketing core.
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Yanhao "Max" Wei, Nikolai Roussanov, Hongxun Ruan () "Marketing Mutual Funds ,"  Review of Financial Studies.
Yanhao "Max" Wei, Jihoon Hong, Gerard Tellis () "Machine Learning From Success: How Similarity Networks Help to Design Winning Projects in Crowdfunding? ,".
Yanhao "Max" Wei, Nikolai Roussanov, Hongxun Ruan () "Mutual fund flows and performance in (imperfectly) rational markets? ,".
Yanhao "Max" Wei, Zhenling Jiang () "Estimating Parameters of Structural Models Using Neural Networks. ,".
Yanhao "Max" Wei, Hongxun Ruan () "Do connected holdings help firms innovate? ,".
Yanhao "Max" Wei, Linli Xu, Yi Zhu () "Does surge pricing affect customer complaint rate? ,".
Yanhao "Max" Wei, Wensi Zhang, Sha Yang, Xi Cheng () "Online Communities and Social Network Structure ,".
Yanhao Wei () "The Similarity Network of Motion Pictures ,"  Management Science.
Yanhao Wei () "Airline Networks, Traffic Densities, and the Value of Links. ,"  Quantitative Marketing and Economics.
Yanhao Wei, Joseph Harrington () "What Can the Duration of Discovered Cartels Tell Us About the Duration of All Cartels? ,"  Economic Journal  127.
Yanhao Wei, Pinar Yildirim, Christophe Van den Bulte, Chris Dellarocas () "Credit Scoring with Social Network Data ,"  Marketing Science  35, 234 - 258.