Gah‐Yi Ban

1.2k total citations · 1 hit paper
9 papers, 693 citations indexed

About

Gah‐Yi Ban is a scholar working on Management Information Systems, Management Science and Operations Research and Marketing. According to data from OpenAlex, Gah‐Yi Ban has authored 9 papers receiving a total of 693 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Management Information Systems, 7 papers in Management Science and Operations Research and 4 papers in Marketing. Recurrent topics in Gah‐Yi Ban's work include Supply Chain and Inventory Management (7 papers), Forecasting Techniques and Applications (5 papers) and Consumer Market Behavior and Pricing (4 papers). Gah‐Yi Ban is often cited by papers focused on Supply Chain and Inventory Management (7 papers), Forecasting Techniques and Applications (5 papers) and Consumer Market Behavior and Pricing (4 papers). Gah‐Yi Ban collaborates with scholars based in United Kingdom, United States and Singapore. Gah‐Yi Ban's co-authors include Cynthia Rudin, N. Bora Keskin, Noureddine El Karoui, Andrew E. B. Lim, Jérémie Gallien, Adam J. Mersereau and Zhenyu Gao and has published in prestigious journals such as Management Science, Operations Research and Manufacturing & Service Operations Management.

In The Last Decade

Gah‐Yi Ban

9 papers receiving 666 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Big Data Newsvendor: Practical Insights from Machine Learning

2018 301 citations Gah‐Yi Ban, Cynthia Rudin Operations Research profile →

Peers

Gah‐Yi Ban

MSOR

MIS

MARKE

FINAN

EE

Karthik Natarajan Singapore

Joline Uichanco United States

Dan A. Iancu United States

Arnab Bisi United States

Wai-Ki Ching Hong Kong

Adam J. Mersereau United States

Nalân Gülpınar United Kingdom

John W. Mamer United States

Süleyman Özekıcı Türkiye

David C. Heath United States

Karthik Natarajan Singapore

Gah‐Yi Ban

727 ×1.7

MSOR

266 ×0.9

MIS

85 ×0.7

MARKE

167 ×1.6

FINAN

216 ×2.6

EE

Citations per year, relative to Gah‐Yi Ban Gah‐Yi Ban (= 1×) peers Karthik Natarajan

Countries citing papers authored by Gah‐Yi Ban

Since Specialization

Citations

This map shows the geographic impact of Gah‐Yi Ban's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gah‐Yi Ban with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gah‐Yi Ban more than expected).

Fields of papers citing papers by Gah‐Yi Ban

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gah‐Yi Ban. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gah‐Yi Ban. The network helps show where Gah‐Yi Ban may publish in the future.

Co-authorship network of co-authors of Gah‐Yi Ban

This figure shows the co-authorship network connecting the top 25 collaborators of Gah‐Yi Ban. A scholar is included among the top collaborators of Gah‐Yi Ban based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gah‐Yi Ban. Gah‐Yi Ban is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Ban, Gah‐Yi & N. Bora Keskin. (2021). Personalized Dynamic Pricing with Machine Learning: High-Dimensional Features and Heterogeneous Elasticity. Management Science. 67(9). 5549–5568. 100 indexed citations

2.

Ban, Gah‐Yi. (2020). Confidence Intervals for Data-Driven Inventory Policies with Demand Censoring. Operations Research. 30 indexed citations

3.

Ban, Gah‐Yi, et al.. (2019). Model Mis-Specification in Newsvendor Decisions: A Comparison of Frequentist Parametric, Bayesian Parametric and Nonparametric Approaches. SSRN Electronic Journal. 1 indexed citations

4.

Ban, Gah‐Yi & Cynthia Rudin. (2018). The Big Data Newsvendor: Practical Insights from Machine Learning. Operations Research. 67(1). 90–108. 301 indexed citations breakdown →

5.

Ban, Gah‐Yi, Jérémie Gallien, & Adam J. Mersereau. (2018). Dynamic Procurement of New Products with Covariate Information: The Residual Tree Method. Manufacturing & Service Operations Management. 21(4). 798–815. 61 indexed citations

6.

Ban, Gah‐Yi & N. Bora Keskin. (2017). Personalized Dynamic Pricing with Machine Learning. SSRN Electronic Journal. 25 indexed citations

7.

Ban, Gah‐Yi & Jérémie Gallien. (2017). Dynamic Procurement of New Products with Covariate Information: The Residual Tree Method. SSRN Electronic Journal. 3 indexed citations

8.

Ban, Gah‐Yi, Noureddine El Karoui, & Andrew E. B. Lim. (2016). Machine Learning and Portfolio Optimization. Management Science. 64(3). 1136–1154. 168 indexed citations

9.

Ban, Gah‐Yi. (2015). The Data-Driven (s, S) Policy: Why You Can Have Confidence in Censored Demand Data. SSRN Electronic Journal. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact