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 Syllabus

Course Information

• Lectures: TR 11.40pm-12.55pm, Thurston 205, map

• Instructor: Sid Banerjee, 229 Rhodes Hall, email

• Teaching Assistants:

  • Alberto Vera
  • James Dong

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.

• For revenue management:
  • The Theory and Practice of Revenue Management by Kalyan Talluri and Garrett van Ryzin.
    
• For market design:
  • Twenty Lectures on Algorithmic Game Theory by Tim Roughgarden: We will cover the first 8 lectures; however this is an excellent book for game theory in general. You can also refer to Tim’s original lecture notes.
  • Mechanism Design and Approximation by Jason Hartline: Covers same material, but in much greater detail.
• For a less technical overview of the history, organizing principles, and applications of pricing and revenue management:
  • Pricing and Revenue Optimization by Robert Phillips
  • Principles of Pricing by Vohra and Krishnamurthi
    

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

• Homework 1 (Due by 11.59pm on Friday, 10th February)
  [Solutions]
  
• Homework 2 (Due by 11.59pm on Friday, 28th February)
  [Solutions]
• Homework 3 (Due by 11.59pm on Wednesday, 15th March)
  [Solutions]
• Homework 4 (Due by 11.59pm on Sunday, 26th March
  [Solutions] (iPython notebook)
• Homework 5 (Due by 11.59pm on Wednesday, 5th May)
  [Solutions]