BUS429 Pricing Analytics and Revenue Management

• Topics

  The course will try to answer the question: "At what price should firms sell their output to maximize their profits?"

  To answer this question students will use micro-level data to:

  • Estimate consumer demand
  • Estimate production, cost, and profit functions
  • Estimate the nature of competition among firms

  A specific focus will be given to the role of price differentiation (segmentation) and on the pricing theory when supply is constrained.

• Learning outcome

  This course provides students with the tools to understand the tactical function of pricing and revenue optimization. Specifically, in this course the students will learn how to use management science analytical techniques to set prices.

  After completing this course, students can:

  Knowledge

  • Understand demand systems in product and in characteristics space.
  • Understand the role of marginal costs in homogeneous vs differentiated product spaces.
  • Understand the economics foundation of pricing theory.

  Skills

  • Identify potential applications of pricing and revenue management in new industries.
  • Use analytical tools to model real-world pricing decision-making processes.
  • Implement pricing solutions.

  General competences

  • Write reports to communicate their findings clearly and concisely, and in a rigorous form to provide business insights to diverse audiences.

• Teaching

  Lectures, computer workshops, team project.

• Recommended prerequisites

  Elementary Statistics, Probability, and Optimization.

• Required prerequisites

  Elementary statistics, probability, and microeconomics.

• Credit reduction due to overlap

  None.

• Compulsory Activity

  None.

• Assessment

  Final written project (100%) - in groups of two students (or one student) - where the student(s) will solve specific questions related to the course content.

• Grading Scale

  A - F.

• Computer tools

  MS Excel and R.

• Literature

  Arne Henningsen (2020) Introduction to Econometric Production Analysis with R

  Victor Aguirregabiria (2021) Empirical Industrial Organization: Models, Methods, and Applications

  Jean Tirole (1988) The theory of industrial organization