Hi, I'm Dennis Zhang.

I am a tenured associate professor of Operations Management as well as Marketing (Courtesy) at the Olin Business School. My research focuses on data-driven business decision making. I use machine learning, causal inference and structural estimation with data to improve business decisions.

Research

Link to SSRN, Google Scholar

Publications

  1. "A High-Dimensional Choice Model for Online Retailing," with Zhaohui Jiang and Jun Li, Management Science (2023).
  2. "The Impact of Social Nudges on User-Generated Content for Social Network Platforms.," with Zhiyu Zeng, Hengchen Dai, Heng Zhang, Renyu Zhang and Max Shen, Management Science (2022). [ GitHub]
  3. "The Impact of COVID-19 Pandemic on Gig Economy Labor Supply," with Xinyu Cao and Lei Huang, Manufacturing & Service Operations Management (2022).
  4. "The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: Evidence from Field Experiments," with Bing Bai, Hengchen Dai, Fuqiang Zhang and Haoyuan Hu, Manufacturing & Service Operations Management (2022).
  5. "Cold Start on Online Advertising Platforms: Data-Driven Algorithms and Field Experiment.," with Zikun Ye, Heng Zhang, Renyu Zhang and Xin Chen, Management Science (2022). [ GitHub]
  6. "Can Deep Reinforcement Learning Improve Inventory Management? Performance on Dual Sourcing, Lost Sales and Multi-Echelon Problems," with Joren Gijsbrechts, Robert N. Boute, Jan A. Van Mieghem, Manufacturing & Service Operations Management (2021). [ GitHub]
  7. "Customer Choice Models versus Machine Learning: Finding Optimal Product Displays on Alibaba," with Jake Feldman, Operations Research (2021). [ GitHub]
  8. "How Does Bonus Payment Affect the Demand for Auto Loans and Their Delinquency?," with Zhenling Jiang and Tat Chan, Journal of Marketing Research (2021).
  9. "Predicting Human Discretion to Adjust Algorithmic Prescription: A Large-Scale Field Experiment in Bin Packing Warehouse Operations," with Jiankun Sun, Haoyuan Hu and Jan A. Van Mieghem,Management Science (2020).
  10. "Information Sharing on Retail Platforms," with Zekun Liu and Fuqinag Zhang, Manufacturing & Service Operations Management (2020).
  11. "NetEase Cloud Music Data," with Ming Hu, Manufacturing & Service Operations Management (2020).
  12. "The Value of Pop-Up Stores on Retailing Platforms: Evidence from a Field Experiment with Alibaba," with Hengchen Dai and Lingxiu Dong, Management Science (2019).
  13. "The Long-term and Spillover Effects of Price Promotions on Retailing Platforms: Evidence from a Large Randomized Experiment on Alibaba," with Hengchen Dai and Lingxiu Dong, Management Science (2019).
  14. "Peer Bargaining and Productivity in Teams: Gender and the Inequitable Division of Pay," with Lamar Pierce and Laura W. Wang, Manufacturing & Service Operations Management (2019).
  15. "Prosocial Goal Pursuit in Crowdfunding: Evidence from Kickstarter," with Hengchen Dai, Journal of Marketing Research (2018).
  16. "Reducing Discrimination with Reviews in the Sharing Economy: Evidence from Field Experiments on Airbnb," with Ruomeng Cui and Jun Li, Management Science (2018).
  17. "Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon," with Ruomeng Cui and Achal Bassamboo, Management Science (2017).
  18. "The Operational Value of Social Media Information," with Ruomeng Cui, Antonio Moreno and Santiago Gallino, Production and Operations Management (2017).
  19. "Does Social Interaction Improve Learning Outcomes? Evidence from Field Experiments on Massive Open Online Courses (MOOCs)," with Gad Allon and Jan Van Mieghem, Manufacturing & Service Operations Management (2016).
  20. "Hospital Readmission Reduction Program: An Economic and Operational Analysis," with Itai Gurvich, Jan A. Van Mieghem, Eric Park, Mark Williams and Robert Young, Management Science (2016).

Selected Papers Under Review

  1. "Deep Learning Based Causal Inference for Large-Scale Combinatorial Experiments: Theory and Empirical Evidence," with Zikun Ye, Zhiqi Zhang, Heng Zhang, Renyu Zhang, reject and resubmit in Management Science.
  2. "The Value of Logistic Flexibility in E-commerce," with Bing Bai, Tat Chan and Fuqiang Zhang, major revision in Management Science.
  3. "The Effects of Diversity in Algorithmic Recommendations on Digital Content Consumption: A Field Experiment," with Guangying Chen and Tat Chan, under revision.
  4. "The Choice Overload Effect in Online Retailing Platforms," with Xiaoyang Long, Jiankun Sun and Hengchen Dai, major revision in Manufacturing & Service Operations Management.
  5. "The Value of Customer-Related Information on Service Platforms: Evidence From a Large Field Experiment," with Zhiyu Zeng, Nick Clyde, Hengchen Dai and Max Shen, major revision in Manufacturing & Service Operations Management.

Books, Practitioner and Conference Publications

  1. "Deep Learning Based Causal Inference for Large-Scale Combinatorial Experiments: Theory and Empirical Evidence," with Zikun Ye, Zhiqi Zhang, Heng Zhang, Renyu Zhang, 23th ACM Conference on Economics and Computation (EC'23) (2023)
  2. "Applied Machine Learning in Operations Management,” with Hamsa Bastani and Heng Zhang Innovative Technology at the Interface of Finance and Operations (2020).
  3. "Agent Pricing in the Sharing Economy: Evidence from Airbnb. Sharing Economy: Making Supply Meet Demand,” with Antonio Moreno and Jun Li , M. Hu (Ed.), in Springer Series in Supply Chain Management, C. Tang (2018).
  4. "A Better Way to Fight Discrimination in the Sharing Economy,” with Jun Li and Ruomeng Cui, Harvard Business Review (2017).
  5. "Achieving Flexibility in LDPC Code Design by Absorbing Set Elimination," with Jiadong Wang, Shayan Srinivasa and Lara Dolecek, Proc. Asilomar Conference on Signals, Systems, and Computers (2011).

Editorial Service

  • Area Editor, Machine Learning and Data Science, at Operations Research
  • Associate Editor, Marketing Department, at Management Science
  • Associate Editor at Manufacturing & Service Operations Management
  • Senior Editor, Marketing Department, at Production and Operations Management

Ph.D. Students

    Current Advisees

    1. Marketing: Guangying Chen (Expected 2024), Annie Shi (Expected 2024), Cheolho Song, Shilei Luo, Cheng Lu
    2. Operations Management: Nick Clyde (Expected 2024), Chenshan Hu, Zihan Zhao, Zhiqi Zhang, Sikun Xu

    Past Advisees:

    1. Daniel Chen, Wharton OM PhD, Committee Member and Coauthor (2024). Assistant Professor of Operations Management in Boston College
    2. Zikun Ye, UIUC IE PhD, Committee Co-Chair (2023). Assistant Professor of Marketing in University of Washington
    3. Bing Bai, WashU Olin OM PhD, Committee Co-Chair (2023). Assistant Professor of Operations Management in McGill University
    4. Joren Gijsbrechts, KU Leuven OM PhD, Committee Member and JMP Coauthor (2020). Assistant Professor of Operations Management in Catolica Lisbon School of Business and Economics
    5. Zhenling Jiang, WashU Olin Marketing PhD, Committee Member and Coauthor (2019). Assistant Professor of Marketing at the Wharton School of University of Pennsylvania
    6. Jiankun Sun, Northwestern Kellogg OM PhD, Committee Member and JMP Coauthor (2019). Assistant Professor of Operations Management at Imperial College Business School, London

    Past Students (Committee Member):

    1. Yang Fan (2023). External Committee Reader. Assistant Professor at NEOMA Business School, France
    2. Fasheng Xu (2019). Assistant Professor at Whitman School of Management, Syracuse University.
    3. Duo Shi (2019). Assistant Professor at CUHK Business School, Shenzhen

Awards

Career Awards

  • Winner, 2022 POMS Chelliah Sriskandarajah Early Career Research Accomplishments Award

Paper Awards

  • (2023) Finalist, 2023 Best Paer in Operations Research ("Customer Choice Models versus Machine Learning: Finding Optimal Product Displays on Alibaba.")
  • (2023) Winner, 2023 Best OM Paper in Management Science ("Reducing Discrimination with Reviews in the Sharing Economy: Evidence from Field Experiments on Airbnb.")
  • (2022) Finalist, 2022 Best OM Paper in Management Science ("Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon.")
  • (2022) Industry Studies Association’s 2021 Ralph Gomory Best Industry Studies Paper Award ("Peer Bargaining and Productivity in Teams: Evidence on the Inequitable Division of Pay.")
  • (2021) Finalist, INFORMS Revenue Management and Pricing Section Jeff McGill Student Paper Prize. ("Cold Start to Improve Market Thickness on Online Advertising Platforms: Data-Driven Algorithms and Field Experiments.")
  • (2021) Finalist, 2021 Behavioral Operations Management Best Working Paper Award. ("Wage Transparency, Negotiation,and Reference-dependent Utility.")
  • (2021) Finalist, 2021 Wharton People Analytics White Paper Competition. ("The Impact of AI on Workers’ Perceived Fairness: Evidence from a Field Experiment.")
  • (2021) Finalist, Best Accepted Papers in 2021 Academy of Management Meeting. ("The Impact of AI on Workers’ Perceived Fairness: Evidence from a Field Experiment.")
  • (2021) Honorable Mention, M&SOM 2020 Responsible Research Award. ("Reducing Discrimination with Reviews in the Sharing Economy: Evidence from Field Experiments on Airbnb.")
  • (2020) Finalist, 2020 POM-CBOM Junior Scholar Competition. ("The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: Evidence from Field Experiments.")
  • (2020) Winner, 2020 Olin Research Award. ("Predicting Human Discretion to Adjust Algorithmic Prescription: A Large-Scale Field Experiment in Bin Packing Warehouse Operations.")
  • (2019) Winner, 2019 Revenue Management Practice Award. ("Taking Assortment Optimization from Theory to Practice: Evidence from Large Field Experiments on Alibaba.")
  • (2019) Finalist, 2019 Best Service Science Paper Award Competition. ("The Spillover Effects of Employee-Customer Interactions: Field Evidence from an Online Education Platform")
  • (2019) Finalist, 2019 Innovative Applications in Analytics Award. ("Taking Assortment Optimization from Theory to Practice: Evidence from Large Field Experiments on Alibaba.")
  • (2019) Winner, 2019 Olin Research Award. ("Taking Assortment Optimization from Theory to Practice: Evidence from Large Field Experiments on Alibaba."
  • (2018) Finalist, Competition at the 2018 Wharton People Analytics Conference. ("Peer Bargaining and Productivity in Teams: Evidence on the Inequitable Division of Pay.")
  • (2018) Finalist, 2018 POMS Applied Research Challenge. ("How Do Price Promotions Affect Customer Behavior on Retailing Platforms? Evidence from a Large Randomized Experiment on Alibaba.")
  • (2018) Finalist, 2018 POM-CBOM Junior Scholar Competition. ("How Do Price Promotions Affect Customer Behavior on Retailing Platforms? Evidence from a Large Randomized Experiment on Alibaba.")
  • (2017) Winner, 2017 Behavioral Operations Management Best Working Paper Award. ("Discrimination with Incomplete Information in the Sharing Economy: Evidence from Field Experiments on Airbnb.")
  • (2014) Winner, 2014 POMS College of Healthcare Operations Management Best Paper Award. ("Hospital Readmission Reduction Program: An Economic and Operational Analysis.")

Service Awards

  • (2019) Management Science Distinguished Service Award
  • (2019) M&SOM Meritorious Service Award
  • (2018) Management Science Distinguished Service Award
  • (2018) M&SOM Meritorious Service Award
  • (2017) Management Science Distinguished Service Award
  • (2017) M&SOM Meritorious Service Award

Teaching Awards

  • (2019) Reid Teaching Award---Master of Science in Business Analytics–Financial Technology
  • (2019) Reid Teaching Award---Master of Science in Business Analytics–Customer

Contact me!

You can find me via email: denniszhang AT wustl.edu

Office: Bauer Hall 406, 1 Brookings Dr., St. Louis, MO 63130.

© 2023-2024 Dennis J. Zhang