B8899-002: Pricing & Revenue Optimization
R Full Term,
02:15PM to 05:30PM
Location: URI 307
Instructor: costis maglaras
View course evaluation
Pricing and revenue optimization — or revenue management, as it is also called — focuses on how a firm should set and update pricing and product availability decisions across its various selling channels in order to maximize its profitability. The most familiar example probably comes from the airline industry, where tickets for the same flight may be sold at many different fares throughout the booking horizon depending on product restrictions as well as the remaining time until departure and the number of unsold seats. The use of such strategies has transformed the transportation and hospitality industries, and they are increasingly important in retail, telecommunications, entertainment, financial services, health care and manufacturing. In parallel, pricing and revenue optimization has become a rapidly expanding practice in consulting services and a growing area of software and IT development.
Through a combination of case studies, lectures and guest speakers, the course reviews the main methodologies that are used in each of these areas, discuss legal issues associated with different pricing strategies and survey current practices in different industries. The ultimate goal is for students to learn to identify and exploit opportunities for revenue optimization in different business contexts. As the course outline reveals, most of the topics covered in the course are either directly or indirectly related to pricing issues faced by firms that operate in environments where they enjoy some degree of market power. Within the broader area of pricing theory, the course places particular emphasis on tactical optimization of pricing and capacity allocation decisions, tackled using quantitative models of consumer behavior (e.g., captured via appropriate price-response relations), demand forecasts and market uncertainty, and the tools of constrained optimization — the two main building blocks of revenue optimization systems.
More information will be made available at www.gsb.columbia.edu/faculty/cmaglaras/maglaras.htm.