Revenue Management and Pricing

Description from DukeHub

This course focuses on the application of stochastic modeling and optimization to two fundamental and closely related problems: dynamic pricing, and dynamic allocation of limited resources. We will cover fundamental methods and models in dynamic pricing and revenue management, and explore related literature in operations research, statistics, and economics. The course consists of three modules: (a) dynamic capacity control, (b) dynamic pricing, and (c) demand estimation and the tradeoff between learning and earning. Open only to PhD students; MBA students require instructor consent. A background in stochastic processes, microeconomics, optimization, and dynamic programming is helpful. Instructor consent required.

Skills

• data and statisticsdescription: "modeling" and 1 more
• financedescription: "pricing" and 2 more

AI-resilient: 0 of 5 0/5

• No: Physical, lab or field work
• No: Live work with people
• No: Judgment someone is accountable for
• No: A craft you practice with your hands or body
• No: Small, in-person format

The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works

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