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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
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Published April 16, 2024
How Blockchain Can Save Your Strawberries

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Recent Publications


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

Journal Article Operations Research · September 1, 2025 We consider an electric utility company that serves retail electricity customers over a discrete-time horizon. In each period, the company observes the customers’ consumption and high-dimensional features on customer characteristics and exogenous factors. ... Full text Cite

Markdown Policies for Demand Learning with Forward-Looking Customers

Journal Article Operations Research · September 1, 2025 We consider the markdown pricing problem of a firm that sells a product to a mixture of myopic and forward-looking customers. The firm faces uncertainty about the customers’ forward-looking behavior, arrival pattern, and valuations for the product, which w ... Full text Cite

The Blockchain Newsvendor: Value of Freshness Transparency and Smart Contracts

Journal Article Management Science · August 1, 2025 Motivated by blockchain applications in the fresh produce industry, we consider a newsvendor problem in which a retailer faces stochastic and freshness-dependent consumer demand. The retailer can adopt blockchain technology to have more transparent informa ... Full text Cite
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Education, Training & Certifications


Stanford University · 2012 Ph.D.