Events

Prof. Yu Jeffrey Hu
Professor and Accenture Chair
Daniels School of Business
Purdue University

Despite the popularity of product recommendations on online investment platforms, few studies have explored their impact on investor behaviors. Using data from a global e-commerce platform, we apply regression discontinuity design to causally examine the effects of product recommendations on online investors’ mutual fund investments. Our findings indicate that recommended funds experience a significant rise in purchases. However, investors suffer significantly worse investment returns after purchasing recommended funds, and this negative impact is also most significant for investors with low socioeconomic status. To explain this disparity, we find investors tend to gather less information and expend reduced effort in fund research when buying recommended funds. Furthermore, recommended funds are more likely to perform worse than non-recommended funds when investors make the purchase, potentially due to price overreaction. We also find that investors tend to hold recommended funds for shorter time than non-recommended funds. In conclusion, product recommendations make investors behave more irrationally and these negative consequences are most significant for investors with low socioeconomic status.

Yu Jeffrey Hu is a Full Professor and Accenture Chair at Purdue University’s Daniels School of Business. He is also a Distinguished Fellow of INFORMS Information Systems Society, and has been a Digital Fellow at MIT’s Initiative on Digital Economy. He is a world-renowned expert on AI, analytics, digital economy, digital transformation, electronic commerce, omni-channel retailing, offline commerce, social media, and fintech. His research uses AI, econometric, and analytical models to study technology-driven consumer behaviors in environments such as electronic commerce, omni-channel retailing, offline commerce, social media, mobile app, and fintech.