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Nuri Bora Keskin

Associate Professor of Business Administration
Fuqua School of Business

Overview


Bora Keskin is an associate professor in the Operations Management area at the Fuqua School of Business at Duke University. Bora received his Ph.D. from the Graduate School of Business at Stanford University in 2012. Before joining the faculty at Duke University in 2015, he worked at McKinsey & Company as a consultant in banking and telecommunications industries, and at the University of Chicago as an Assistant Professor of Operations Management.

Bora’s main research studies management problems that involve decision making under uncertainty. In particular he is interested in stochastic models and their application to revenue management, dynamic pricing, statistical learning, machine learning, and product differentiation. Bora has published papers in leading research journals such as Management Science, Operations Research, Manufacturing and Service Operations Management, and Mathematics of Operations Research. In 2019, Bora was awarded the Lanchester Prize for the development of a novel paradigm for the modeling and analysis of online dynamic optimization problems that are subject to temporal uncertainty.

Bora has taught Value Chain Innovation in Business Processes as well as Supply Chain Management for the Daytime and Executive MBA programs, and Revenue Management for the PhD program at the Fuqua School of Business. Outside Duke, he served as a Board Member for the INFORMS Revenue Management and Pricing (RM&P) Section from 2014-2016, and as a Cluster Chair for the RM&P and M&SOM-Service tracks at INFORMS Annual Meetings (organizing 319 talks in total).

Current Appointments & Affiliations


Associate Professor of Business Administration · 2023 - Present Fuqua School of Business

In the News


Published January 14, 2025
How Accurate Are People-Counting Sensors?
Published April 16, 2024
How Blockchain Can Save Your Strawberries

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Recent Publications


To Interfere or Not To Interfere: Information Revelation and Price-Setting Incentives in a Multiagent Learning Environment

Journal Article Operations Research · November 1, 2024 We consider a platform in which multiple sellers offer their products for sale over a time horizon of T periods. Each seller sets its own price. The platform collects a fraction of the sales revenue and provides price-setting incentives to the sellers to m ... Full text Cite

Data-Driven Clustering and Feature-Based Retail Electricity Pricing with Smart Meters

Journal Article Operations Research · September 3, 2024 The adoption of smart meters and dynamic pricing programs is rapidly increasing among electric utility companies. In “Data-Driven Clustering and Feature-Based Retail Electricity Pricing with Smart Meters,” Keskin, Li, and Sunar analyze how utility ... Full text Cite

Selling Quality-Differentiated Products in a Markovian Market with Unknown Transition Probabilities

Journal Article Operations Research · May 1, 2024 In this paper, we study a firm’s dynamic pricing problem in the presence of unknown and time-varying heterogeneity in customers’ preferences for quality. The firm offers a standard product as well as a premium product to deal with this heterogeneity. First ... Full text Cite
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Education, Training & Certifications


Stanford University · 2012 Ph.D.