Working Papers

  1. Cost-Aware Calibration of Classifiers. Mochen Yang, Xuan Bi. [SSRN]
  2. Promoting Algorithm Adoption in the Presence of Human Experts: A Field Study. Xue Tan, Mochen Yang, Gang Wang. [SSRN]
  3. EnsembleIV: Creating Instrumental Variables from Ensemble Learners for Robust Statistical Inference. Gordon Burtch, Edward McFowland III, Mochen Yang, Gediminas Adomavicius. [ArXiv]
  4. Algorithmic Governance of Two-Sided Platforms: the Case of Short Video Recommendation. Jinghui Zhang, Mochen Yang, Xuan Bi, Qiang Wei. [SSRN]


  1. Understanding Partnership Formation and Repeated Contributions in Federated Learning: An Analytical Investigation. Xuan Bi, Alok Gupta, Mochen Yang. Management Science, forthcoming. [Journal Link] [SSRN]
  2. User Engagement on Social Media Business Pages: The Interplay between User Comments and Firm Responses. Xiaoye Cheng, Hillol Bala, Mochen Yang. MIS Quarterly, forthcoming.
  3. Judge Me on My Losers: Does Adaptive Robo-Advisors Outperform Human Investors during the COVID-19 Financial Market Crash? Che-Wei Liu, Mochen Yang, Ming-Hui Wen. Production and Operations Management, forthcoming. [SSRN] [Journal Link]
  4. Consumer Acquisitions for Recommender Systems: A Theoretical Framework and Empirical Evaluations. Xuan Bi, Mochen Yang, Gediminas Adomavicius. Information Systems Research, forthcoming. [Journal Link] [SSRN]
  5. Welfare and Fairness Dynamics in Federated Learning: A Client Selection Perspective. Yash Travadi, Le Peng, Xuan Bi, Ju Sun, Mochen Yang. Statistics and Its Interface, forthcoming. [arXiv]
  6. When Algorithms Err: Differential Impact of Early vs. Late Errors on Users’ Reliance on Algorithms. Antino Kim, Mochen Yang, Jingjing Zhang. ACM Transactions on Computer-Human Interaction (TOCHI), 2023. [Journal Link] [SSRN] [Presentation (by Antino Kim)]
  7. Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem. Mochen Yang, Edward McFowland III, Gordon Burtch, Gediminas Adomavicius. INFORMS Journal on Data Science, 2022. [Journal Link] [SSRN] [Code] [Code Demo]
  8. Bidder Support in Multi-Item Multi-Unit Continuous Combinatorial Auctions: A Unifying Theoretical Framework. Gediminas Adomavicius, Alok Gupta, Mochen Yang. Information Systems Research, 2022. [Journal Link] [SSRN]
  9. Integrating Behavioral, Economic, and Technical Insights to Understand and Address Algorithmic Bias: A Human-Centric Perspective. Gediminas Adomavicius, Mochen Yang. ACM Transactions on Management Information Systems (TMIS), 2022. [Journal Link] [SSRN]
  10. Engagement by Design: An Empirical Study of the “Reactions” Feature on Facebook Business Pages. Mochen Yang, Yuqing Ren, Gediminas Adomavicius. ACM Transactions on Computer-Human Interaction (TOCHI), 2020. [Journal Link] [SSRN] [Presentation]
  11. Understanding User-Generated Content and Customer Engagement on Facebook Business Pages. Mochen Yang, Yuqing Ren, Gediminas Adomavicius. Information Systems Research, 2019. [Journal Link] [SSRN] [Podcast]
  12. Efficient Computational Strategies for Dynamic Inventory Liquidation. Mochen Yang, Gediminas Adomavicius, Alok Gupta. Information Systems Research, 2019. [Journal Link] [SSRN]
  13. Designing Real-Time Feedback for Bidders in Homogeneous-Item Continuous Combinatorial Auctions. Gediminas Adomavicius, Alok Gupta, Mochen Yang. MIS Quarterly, 2019. [Journal Link] [SSRN]
  14. Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining. Mochen Yang, Gediminas Adomavicius, Gordon Burtch, Yuqing Ren. Information Systems Research, 2018. [Journal Link] [SSRN]