Philip R. Zhang
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Research

My research applies AI and data science to address fundamental business operations issues under the emerging trends in technology, marketplaces, and society. I am particularly enthusiastic about developing data science methodologies (machine learning, causal inference, and data-driven optimization) to evaluate and optimize the operations strategies in the contexts of online platforms and marketplaces, sharing economy, and social networks, especially their recommendation, advertising, pricing, and matching policies. I am also a strong adherent to the philosophy that business research should push the "efficient frontier" of intellectual depth and practical impact, thus striving to implement my research in business practice whenever applicable.

Research Interests

Methodologies

Machine learning and deep learning; causal inference and econometrics; reinforcement learning; data-driven optimization.

Applications

Online platforms and marketplaces; social networks; AI ethics; revenue management and pricing; inventory and supply chain management.

Research Papers

[Google Scholar Profile] [SSRN Author Page]

Peer-Refereed Publications

  1. Dynamic Pricing and Inventory Management under Inventory-Dependent Demand, Operations Research, 62(5), 2014, 1077-1094 (with Nan Yang) [Online Appendix].

  2. Dynamic Pricing and Inventory Management under Fluctuating Procurement Costs, Manufacturing & Service Operations Management, 17(3), 2015, 321-334 (with Guang Xiao and Nan Yang) [Online Appendix].

  3. Dynamic Supply Risk Management with Signal-Based Forecast, Multi-Sourcing, and Discretionary Selling, Production and Operations Management, 26(7), 2017, 1399-1415 (with Long Gao, Nan Yang, and Ting Luo) [Online Appendix].

  4. Trade-in Remanufacturing, Customer Purchasing Behavior, and Government Policy, Manufacturing & Service Operations Management, 20(4), 2018, 601-616 (with Fuqiang Zhang) [Online Appendix].
      5. --- Finalist award in the POMS College of Supply Chain Management 2015 Best Student Paper Competition.

  5. Comparative Statics Analysis of An Inventory Management Model with Dynamic Pricing, Market Environment Fluctuation, and Delayed Differentiation, Production and Operations Management, 31(1), 2022, 341-357 (with Nan Yang).

  6. Carpool Services for Ride-sharing Platforms: Price and Welfare Implications, Naval Research Logistics, 69(4), 2022, 550-565 (with Xuan Wang) [Online Appendix].

  7. Competition and Coopetition for Two-sided Platforms, Production and Operations Management, 31(5), 2022, 1997-2014 (with Maxime Cohen) [Online Appendix].
      8. --- Honorable Mention award in the INFORMS Service Science 2017 Best Cluster Paper Award.

  8. Dynamic Pricing and Inventory Management in the Presence of Online Reviews, Production and Operations Management, 31(8), 2022, 3180-3197 (with Nan Yang) [Online Appendix].

  9. Cold Start to Improve Market Thickness on Online Advertising Platforms: Data-Driven Algorithms and Field Experiments, Management Science, 69(7), 2023, 3838-3860 (with Zikun Ye, Dennis J. Zhang, Heng Zhang, Xin Chen, and Zhiwei Xu) [Online Appendix].

  10. Data Aggregation and Demand Prediction, Operations Research, 70(5), 2022, 2597-2618 (with Maxime Cohen and Kevin J. Jiao) [Online Appendix].
      11. --- Finalist award in the INFORMS Data Mining Section 2019 Best Paper Award.

      --- [GitHub Repo]

  11. The Impact of Social Nudges on User-Generated Content for Social Network Platforms, Management Science, 69(9), 2023, 5189-5208 (with Zhiyu Zeng, Hengchen Dai, Dennis J. Zhang, Heng Zhang, Max Shen, and Zhiwei Xu) [Online Appendix].

  12. Inventory Commitment and Monetary Compensation under Competition, Manufacturing & Service Operations Management, 25(6), 2023, 2142-2159 (with Junfei Lei, Fuqiang Zhang, and Yugang Yu) [Online Appendix].

  13. Online Advertisement Allocation under Customer Choices and Algorithmic Fairness, Management Science, forthcoming, 2023 (with Xiaolong Li, Ying Rong, and Huan Zheng) [Online Appendix].

  14. Content Promotion for Online Content Platforms with Network Diffusion Effect, Manufacturing & Service Operations Management, forthcoming, 2024 (with Yunduan Lin, Mengxin Wang, Max Shen, and Heng Zhang) [Online Appendix].
      15. --- Winner of the INFORMS Social Media Analytics 2022 Best Student Paper Award Competition (Primary Awardee: Yunduan Lin).

      --- [GitHub Repo]

Working Papers

  1. Dynamic Competition in Online Retailing: Implications of Network Effects (with Zheyu Jiang and Nan Yang).

  2. Nonprogressive Diffusion on Social Networks: Approximation and Applications (with Yunduan Lin, Heng Zhang, and Max Shen).
      3. --- Winner of the POMS-HK 2023 Best Student Paper Award Competition (Primary Awardee: Yunduan Lin).

      --- Finalist of the INFORMS Data Mining and Decision Analytics Workshop 2023 Best Paper Competition (Primary Awardee: Yunduan Lin).

  3. Deep Learning Based Causal Inference for Large-Scale Combinatorial Experiments: Theory and Empirical Evidence (with Zikun Ye, Zhiqi Zhang, Dennis J. Zhang, and Heng Zhang).

  4. Optimal Growth of a Two-Sided Platform with Heterogeneous Agents (with Yixin Zhu, Hongfan Chen, and Sean X. Zhou).

Books

  1. Demand Prediction in Retail - A Practical Guide to Leverage Data and Predictive Analytics, Springer Series in Supply Chain Management, ISBN 978-3-030-85855-1, 2022 (with Maxime Cohen, Paul-Emile Gras, and Arthur Pentecoste).

Research Awards and Grants

  1. Finalist of the INFORMS Data Mining and Decision Analytics Workshop 2023 Best Paper Competition (Primary Awardee: Yunduan Lin), October 2023.

  2. Finalist of the MSOM Student Paper Competition 2023 (Primary Awardee: Zhiyu Zeng), October 2023.

  3. Winner of the INFORMS Social Media Analytics 2023 Best Student Paper Award Competition (Primary Awardee: Zikun Ye), October 2023.

  4. Second Prize of the CSAMSE 2023 Best Paper Award, July 2023.

  5. Hong Kong Research Grants Council, General Research Fund 14504123, PI, HKD 444,066, January 2024-December 2025.

  6. Tencent Collaboration with University Fund, PI, RMB 332,310, December 2022.

  7. Winner of the POMS-HK 2023 Best Student Paper Award (Primary Awardee: Yunduan Lin), January 2023.

  8. Winner of the INFORMS Social Media Analytics 2022 Best Student Paper Award (Primary Awardee: Yunduan Lin), October 2022.

  9. CUHK 'Improvement on Competitiveness in Hiring New Faculties' Funding Scheme, PI, HKD 1,500,000, July 2022.

  10. Hong Kong Research Grants Council, General Research Fund 14502722, PI, HKD 629,325, September 2022-August 2025.

  11. Finalist award in the INFORMS Revenue Management & Pricing 2020 Student Paper Competition (Primary Awardee: Zikun Ye), October 2020.

  12. Finalist award in the INFORMS Data Mining Section 2019 Best Paper Award, October 2019.

  13. Shanghai Eastern Scholar, Young Scholar Program QD2018053, PI, RMB 200,000/Year, January 2019-December 2021.

  14. National Natural Science Foundation of China, Young Scientist Program 71802133, PI, RMB 180,000, January 2019-December 2021.

  15. Honorable Mention award in the INFORMS Service Science 2017 Best Cluster Paper Award, October 2017.

  16. Shanghai Pujiang Talent Program 17PJC074, PI, RMB 100,000, September 2017-August 2019.

  17. Finalist award in the POMS College of Supply Chain Management 2015 Best Student Paper Competition, May 2015.

PhD Dissertation

Dynamic Pricing and Inventory Management: Theory and Applications (supervised by Nan Yang and Fuqiang Zhang) [Defense Slides].

Notes, Reviews and Tutorials

  1. On the Operations Job Market: Reflections and Insights.

  2. An Introduction to Joint Pricing and Inventory Management under Stochastic Demand.

  3. Pricing and Inventory Management under Fluctuating Costs.

  4. Recent Development in Health-care Operations (B.S. thesis, advised by Ke Liu).

Coauthors

Hongfan Chen, Xin Chen, Maxime Cohen, Hengchen Dai, Long Gao, Paul-Emile Gras, Zheyu Jiang, Kevin J. Jiao, Junfei Lei, Xiaolong Li, Yunduan Lin, Ting Luo, Arthur Pentecoste, Ying Rong, Max Shen, Mengxin Wang, Xuan Wang, Guang Xiao, Zhiwei Xu, Nan Yang, Zikun Ye, Yugang Yu, Zhiyu Zeng, Dennis J. Zhang, Fuqiang Zhang, Heng Zhang, Zhiqi Zhang, Huan Zheng, Sean X. Zhou, and Yixin Zhu.

PhD Student Advising

  1. Kevin J. Jiao (Dissertation Committee, New York University, Stern School of Business, PhD 2019, Initial Placement: FINRA).

  2. Xiaolong Li (Shanghai Jiaotong University, Antai College of Economics and Management, PhD 2019, Initial Placement: Post-Doctoral Fellow at NUS IORA).

  3. Zikun Ye (Uiniversity of Illinois at Urbana-Champaign, Department of Industrial and Enterprise Systems Engineering 2023, Initial Placement: Assistant Professor of Marketing, University of Washington, Foster School of Business).

  4. Zhiyu Zeng (Dissertation Committee, Tsinghua University, Department of Industrial Engineering 2023, Initial Placement: Post-Doctoral Fellow at Washington University in St. Louis, Olin Business School).

  5. Yunduan Lin (University of California, Berkeley, Department of Civil and Environmental Engineering 2024, Initial Placement: Assistant Professor, The Chinese University of Hong Kong, CUHK Business School).

  6. Junfei Lei (University of Washington, Foster School of Business 2023, Initial Placement: Post-Doctoral Fellow at INSEAD).

  7. Zhiqi Zhang (Washington University in St. Louis, Olin Business School, Current PhD).

  8. Zheyu Jiang (Dissertation Committee, University of Miami, Miami Herbert Business School 2023, Initial Placement: Nanjing University, School of Management and Engineering).

  9. Zihan Zhao (Washington University in St. Louis, Olin Business School, Current PhD).

  10. Yixin Zhu (The Chinese University of Hong Kong, CUHK Business School, Current PhD).

  11. Qinlu Hu (Advisor, The Chinese University of Hong Kong, CUHK Business School, Current PhD).

  12. Xinyu Xu (The Chinese University of Hong Kong, CUHK Business School, Current PhD).

  13. Shu Zhang (The Chinese University of Hong Kong, CUHK Business School, Current PhD).

  14. Xinyi Zhang (The National University of Singapore, School of Computing, Current PhD).

Undergraduate and Master Student Research Advising

  1. Qiansiqi Hu (CUHK Business School, MSBA 2024).

  2. Wenyi Wu (CUHK Statistics Department, Undergraduate 2024).

  3. Yuying Huang (CUHK Business School Research Assistant, New York University Shanghai, Undergraduate 2023).

  4. Yanwen Liu (Tsinghua University School of Economics and Management, Undergraduate 2024).

  5. Haoyu Xu (CUHK Business School Research Assistant, New York University Shanghai, Undergraduate 2017).

  6. Ziheng Wang (New York University Shanghai, Business Honors Thesis 2021).

  7. Yiyi Zhang (New York University Shanghai, Business Honors Thesis 2018).

  8. Yujia Ni (New York University Shanghai, Business Honors Thesis 2018).

Quotations

"Conferences and ArXiv are great places to find out what most clever and energetic people are working on, but where do you go to find out what clever and energetic people are not working on?"--- David Aldous

"Wir müssen wissen - wir werden wissen!" (We must know - we will know!)---the epitaph on the tomb of David Hilbert.