Pricing and Market Design

Course Description

This course will expose students to modeling and optimization techniques which can be used to design the firm-market interface. In particular, this interface can take two forms:

  • Revenue management: How to sell the right product to the right customer at the right time for the right price.
  • Marketplace design: Determining who gets what and why (and at what price) in two-sided platform marketplaces.

We will draw on a rich body of research spanning three disciplines - operations management, economics and computer science - and study a collection of related (yet diverse) mathematical models and techniques. The models we cover have proved successful in practice across various industries; however, given the transformations brought about by the advent of online commerce and increased use of smartphones, our aim is to provide students with tools that generalize to new domains.

Course Information

References

There is no required textbook for the course; we will cover materials from a variety of sources, and relevant notes and references will be uploaded here and on Piazza. For interested students, here are some recommended books.

Lectures

  • Lecture 1: Introduction [slides]
  • Lecture 2: Single fare-class capacity allocation (Littlewood’s Law) [slides]
  • Lecture 3: Intro to dynamic programming [slides]
  • Lecture 4-7: Multiple fare-class capacity allocation [slides]
    • [Notes]: Optimality of protection-levels
    • [Notes]: Computing protection levels
  • Lecture 8: Intro to network revenue management [slides]
  • Lecture 9: The Network RM Dynamic Program [slides]
  • Lecture 10: LP approximation for single-resource settings [Notes]
  • Lecture 11: Convexity and LP-based Approximations [Notes]
  • Lecture 12: LP-duality and bid prices for network RM [Notes]
  • Lecture 12.5: Snow day…
  • Lecture 13: Model mismatch and the spiral-down effect [Notes]
  • Lecture 14: Choice Models
  • Lecture 15: Assortment Optimization under the MNL model [Notes]
  • Lecture 16,17: Constrained assortment optimization under MNL [Notes]
  • Lecture 18: Strategic models and mechanism design [Notes]
  • Lecture 19,20: Single-parameter settings and Myerson’s Lemma [Notes]
  • Lecture 21,22: Optimal revenue mechanisms [notes]
  • Lecture 23,24: Pricing in two-sided marketplaces [Notes]
  • Lecture 25: Course summary, and beyond… [Notes]

Assignments

Siddhartha Banerjee
Siddhartha Banerjee
Assistant Professor

Sid Banerjee is an assistant professor in the School of Operations Research at Cornell, working on topics at the intersection of data-driven decision-making, market design, and algorithms for large-scale networks.