Gah‐Yi Ban

Robert H. Smith School of Business, University of Maryland

Associate Professor

College Park, MD 20742-1815

United States

  • Robert H. Smith School of Business, University of Maryland

SCHOLARLY PAPERS

5

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7,521

SSRN CITATIONS
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SSRN RANKINGS

Top 16,351

in Total Papers Citations

50

CROSSREF CITATIONS

17

Ideas:
“  Data-driven optimization, machine learning for operations management & analytics for sustainable operations  ”

  • Robert H. Smith School of Business, University of Maryland

Scholarly Papers (5)

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1.

Personalized Dynamic Pricing with Machine Learning: High Dimensional Features and Heterogeneous Elasticity

Management Science, Vol. 67, No. 9, September 2021, pp. 5549-5568
Number of pages: 53 Posted: 25 May 2017 Last Revised: 16 Sep 2021
Gah‐Yi Ban and N. Bora Keskin
Robert H. Smith School of Business, University of Maryland and Duke University - Fuqua School of Business
Downloads 3,044 (5,675)
Citation 23

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dynamic pricing, demand learning, demand uncertainty, regret analysis, lasso, machine learning

2.

The Big Data Newsvendor: Practical Insights from Machine Learning

Published in Operations Research 67(1):90-108. https://doi.org/10.1287/opre.2018.1757
Number of pages: 55 Posted: 03 Feb 2015 Last Revised: 22 Aug 2019
Gah‐Yi Ban, Cynthia Rudin and Cynthia Rudin
Robert H. Smith School of Business, University of Maryland and Duke UniversityDuke University - Pratt School of Engineering
Downloads 2,703 (6,867)
Citation 35

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big data, newsvendor, machine learning, Sample Average Approximation, statistical learning theory, quantile regression

3.

Confidence Intervals for Data-Driven Inventory Policies with Demand Censoring

Published in Operations Research 68(2):309-326
Number of pages: 47 Posted: 04 Sep 2015 Last Revised: 14 May 2020
Gah‐Yi Ban
Robert H. Smith School of Business, University of Maryland
Downloads 830 (41,274)
Citation 6

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demand censoring, inventory management, estimation, nonparametric, dynamic programming

4.

Dynamic Procurement of New Products with Covariate Information: The Residual Tree Method

Manufacturing & Service Operations Management, Fall 2019, 21(4):798-815, Kenan Institute of Private Enterprise Research Paper No. 18-8
Number of pages: 40 Posted: 02 Mar 2017 Last Revised: 05 May 2020
Gah‐Yi Ban, Jérémie Gallien and Adam Mersereau
Robert H. Smith School of Business, University of Maryland, London Business School and University of North Carolina Kenan-Flagler Business School
Downloads 617 (60,955)
Citation 13

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new product, inventory management, data-driven operations, scenario tree method, residual tree method, demand uncertainty

5.

Model Mis-Specification in Newsvendor Decisions: A Comparison of Frequentist Parametric, Bayesian Parametric and Nonparametric Approaches

Number of pages: 32 Posted: 01 Jan 2020 Last Revised: 22 Jun 2020
Gah‐Yi Ban, Zhenyu Gao and Fabian Taigel
Robert H. Smith School of Business, University of Maryland, Tsinghua University and University of Wuerzburg, Chair of Logistics and Quantitative Methods
Downloads 327 (128,966)

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data-driven decision-making, newsvendor, inventory, model mis-specification, asymptotic statistics