BUS429 Pricing Analytics and Revenue Management
Spring 2019Autumn 2019
The content of this course has two main parts:
The goal of part 1 is to discuss the main principles of pricing and revenue management:
- Understand it as a corporate process.
- Review the economic principles of pricing.
- Understand the key role of price differentiation (segmentation).
- Learn to price when supply is constrained.
Part 2 focuses on the techniques of three of the major applications of pricing and revenue management:
- Revenue Management: this is one of the major applications of PRO. This section focuses on the strategies and tactics that some industries use to manage allocation of their capacity over time to maximize revenue.
- Markdown management: this section focuses on the schedule of price discounts to maximize the return from the inventory.
- Customize pricing: this section focuses on determining the discount levels to provide to each costumer in order to maximize the expected profitability of a deal.
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 in complex and dynamic environments.
After completing this course, students:
- Understand the tactic role of pricing and revenue optimization within a strategic pricing plan in relevant business contexts.
- Understand the economics foundation of pricing theory.
- Understand the conditions for the application of revenue management.
- Have an overview of the industries where pricing and revenue optimization has provided competitive advantages.
- Are able to identify potential applications of pricing and revenue optimization in new industries.
- Are able to use analytical tools to model real-world pricing decision-making processes.
- Are able to implement pricing solutions.
- Are capable to write reports to communicate their findings clearly and concisely, and in a rigorous form to provide business insights to diverse audiences
Lectures, computer workshops, team project.
Elementary Statistics, Probability, and Optimization.
Final written project (50%) - in groups of two students (or one student).
Four written home works, in groups of two students (or one student), where the students will solve specific questions related to the course content (50%).
A - F.
MS Excel, Matlab, R.
Phillips, R. (2005) Pricing and Revenue Optimization. Stanford University Press.
Tudor, B. and Ferguson, M. (2013) Segmentation, Revenue Management and Pricing Analytics, Routledge.
- ECTS Credits
- Teaching language
Autumn. Offered Autumn 2018
Assistant Professor Julio C. Goez, Department of Business and Management Science