N. Bora Keskin

Professor of Business Administration
Duke University
Fuqua School of Business
100 Fuqua Drive
Durham, NC 27708-0120
Office: A311
Phone: 919-660-1913
Email / CV / Google Scholar / LinkedIn

Research Interests

Dynamic pricing, revenue management, statistical learning, machine learning, applied probability, service management, platform operations, supply chain information systems

Selected Honors and Awards

Publications

  1. Bayesian Dynamic Pricing Policies: Learning and Earning under a Binary Prior Distribution,
    Management Science, Vol. 58, No. 3, March 2012, pp. 570-586, with J.M. Harrison and A. Zeevi.
    [SSRN link]
  2. Dynamic Pricing with an Unknown Demand Model: Asymptotically Optimal Semi-myopic Policies,
    Operations Research, Vol. 62, No. 5, September-October 2014, pp. 1142-1167, with A. Zeevi.
    [SSRN link]
  3. Chasing Demand: Learning and Earning in a Changing Environment,
    Mathematics of Operations Research, Vol. 42, No. 2, May 2017, pp. 277-307, with A. Zeevi.
    — Lead Article.
    — Winner, Lanchester Prize, 2019.
    [SSRN link]
  4. On Incomplete Learning and Certainty-Equivalence Control,
    Operations Research, Vol. 66, No. 4, July-August 2018, pp. 1136-1167, with A. Zeevi.
    [SSRN link]
  5. Dynamic Selling Mechanisms for Product Differentiation and Learning,
    Operations Research, Vol. 67, No. 4, July-August 2019, pp. 1069-1089, with J.R. Birge.
    [SSRN link]
  6. Discontinuous Demand Functions: Estimation and Pricing,
    Management Science, Vol. 66, No. 10, October 2020, pp. 4516-4534, with A.V. den Boer.
    [SSRN link]
  7. Personalized Dynamic Pricing with Machine Learning: High-Dimensional Features and Heterogeneous Elasticity,
    Management Science, Vol. 67, No. 9, September 2021, pp. 5549-5568, with G.-Y. Ban.
    — Honorable Mention, INFORMS Junior Faculty Interest Group (JFIG) Paper Competition, 2018.
    — Finalist, INFORMS Data Mining Best Paper Competition, 2019.
    [SSRN link]
  8. Competition between Two-Sided Platforms under Demand and Supply Congestion Effects,
    M&SOM, Vol. 23, No. 5, September-October 2021, pp. 1043-1061, with F. Bernstein and G. DeCroix.
    [SSRN link]
  9. Dynamic Learning and Market Making in Spread Betting Markets with Informed Bettors,
    Operations Research, Vol. 69, No. 6, November-December 2021, pp. 1746-1766, with J.R. Birge, Y. Feng, and A. Schultz.
    — Preliminary Version in the Proceedings of the 2019 ACM Conference on Economics and Computation (EC '19).
    — Featured in Chicago Booth Review.
    [SSRN link]
  10. Data-driven Dynamic Pricing and Ordering with Perishable Inventory in a Changing Environment,
    Management Science, Vol. 68, No. 3, March 2022, pp. 1938-1958, with Y. Li and J. Song.
    [SSRN link]
  11. Impact of Information Asymmetry and Limited Production Capacity on Business Interruption Insurance,
    Management Science, Vol. 68, No. 4, April 2022, pp. 2824-2841, with Y.-M. Kao and K. Shang.
    [SSRN link]
  12. Dynamic Pricing with Demand Learning and Reference Effects,
    Management Science, Vol. 68, No. 10, October 2022, pp. 7112-7130, with A.V. den Boer.
    [SSRN link]
  13. Selling Quality-Differentiated Products in a Markovian Market with Unknown Transition Probabilities,
    Operations Research, Vol. 72, No. 3, May-June 2024, pp. 885-902, with M. Li.
    [SSRN link]
  14. To Interfere or Not to Interfere: Information Revelation and Price-Setting Incentives in Multiagent Learning Environments,
    Operations Research, Vol. 72, No. 6, November-December 2024, pp. 2391-2412, with J.R. Birge, H. Chen, and A. Ward.
    — Featured in Chicago Booth Review.
    — Featured in China Business Knowledge.
    — Featured in UNSW BusinessThink.
    [SSRN link]
  15. The Blockchain Newsvendor: Value of Freshness Transparency and Smart Contracts,
    Management Science, Vol. 71, No. 8, August 2025, pp. 6666-6682, with C. Li and J. Song.
    — Winner, Best Paper Award, Digital Supply Chain and Supplier Diversity Conference, 2022.
    — Winner, Fan Favorite Award, YinzOR Conference, 2022.
    — Second Place, POMS-HK Best Student Paper Competition, 2023.
    — Honorable Mention, OR/MS Tomorrow Mini Poster Competition, 2022.
    — Honorable Mention, INFORMS Minority Issues Forum Poster Competition, 2023.
    — Featured in Duke Fuqua Insights.
    — Featured in INFORMS News Releases.
    — Featured in The Duke Daily.
    [SSRN link]
  16. Markdown Policies for Demand Learning with Forward-looking Customers,
    Operations Research, Vol. 73, No. 5, September-October 2025, pp. 2550-2566, with J.R. Birge and H. Chen.
    — Featured in Chicago Booth Review.
    [SSRN link]
  17. Data-driven Clustering and Feature-based Retail Electricity Pricing with Smart Meters,
    Operations Research, Vol. 73, No. 5, September-October 2025, pp. 2636-2660, with Y. Li and N. Sunar.
    — Winner, INFORMS Data Mining Best Paper Competition, 2020.
    — Winner, INFORMS Service Science Best Paper Competition, 2022.
    — Invited to the 2022 Conference on AI, ML, & Business Analytics.
    — Featured in Duke Fuqua Insights.
    — Featured in Rethinc. Labs News.
    [SSRN link]
  18. Show-Up Profiles for Scheduled Services: Estimation and Applications,
    M&SOM (forthcoming), with F. Bernstein, A. Mersereau, M. Wood, and S. Ziya.
    — Winner, Triangle Impact Challenge, 2021 (originated from the winning proposal).
    — Featured in UNC Kenan-Flagler News & Stories.
    [SSRN link]
  19. The Nonstationary Newsvendor: Data-Driven Nonparametric Learning,
    Management Science (forthcoming), with X. Min and J. Song.
    [SSRN link]
  20. Data-driven Population Tracking in Service Systems,
    Management Science (forthcoming), with F. Bernstein, A. Mersereau, M. Wood, and S. Ziya.
    — Winner, Triangle Impact Challenge, 2021 (originated from the winning proposal).
    — Featured in Duke Fuqua Insights.
    — Featured in UNC Kenan-Flagler News & Stories.
    — Featured in The Well.
    [SSRN link]
  21. Dynamic Learning for Joint Pricing, Advertising and Inventory Management,
    M&SOM (forthcoming), with H. Gurkan and R. Parker.
    [SSRN link]

Papers Under Review or Revision

  1. Order Stacking in On-Demand Delivery Platforms,
    with J. Scott and R. Swinney.
    [SSRN link]
  2. Bayesian Dynamic Pricing and Subscription Period Selection with Unknown Customer Utility,
    with Y.-M. Kao and K. Shang.
    [SSRN link]
  3. Green Ride-Hailing: Impact on Environment and Consumers,
    with Y. Li and N. Sunar.
    — Featured in Johns Hopkins Carey News.
    [SSRN link]
  4. Feature-based Scheduling and Dynamic Learning with a Large Backlog,
    with C. Zhang.
    — Featured in Duke Fuqua Insights.
    [SSRN link]
  5. Innovator's Edge in Supply Chain Transparency and Food Waste Reduction,
    with C. Li and J. Song.
    [SSRN link]
  6. A Model-Free Geotemporal Clustering Approach for Pandemic Projection and Medical Resource Planning: Insights from COVID-19,
    with X. Min and J. Song.
    [SSRN link]
  7. Optimal Dynamic Pricing with Demand Model Uncertainty: A Squared-Coefficient-of-Variation Rule for Learning and Earning,
    [SSRN link]
  8. Deep Learning for Visual Advertising on Digital Platforms,
    with Y. Li and J. Song.
  9. Feature Selection for Promotion: Learning to Avoid Information Overload,
    with C. Li and M. Li.
    — Winner, Best Student Paper Award, INFORMS Workshop on Data Science, 2024.

Works in Progress

  1. Endogenous State Transitions in Transfer Learning and Dynamic Pricing,
    with J. Song and S. Wang.
  2. Learning and Earning for Congestion-Prone Service Systems,
    with P. Afèche.