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Quantitative Pricing & Revenue Analytics

Fall 2014 MBA Course

B8816-001: Quantitative Pricing & Revenue Analytics

TR - B Term, 10:45AM to 12:15PM
Location: WJW 310

Instructor: Costis Maglaras

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. A
familiar example comes from the airline industry, where tickets for the same
flight may be sold at many different fares, the availability of which is
changing as a function of purchase restrictions, the forecasted future demand,
and the number of unsold seats. The adoption of such systems has transformed
the transportation and hospitality industries, and is increasingly important in
retail, telecommunications, entertainment, financial services, health care, manufacturing,
as well as on-line advertising, online retailing, and online markets. In
parallel, pricing and revenue optimization has become a rapidly expanding
practice in consulting services, and a growing area of software and IT

Through a combination of case studies, lectures and guest speakers, the course
will review the main methodologies that are used in each of these areas, 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 ensuing 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, and in many cases
some ability to segment the market and differentiate its pricing and product
offering across market segments and market conditions. 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.


The recommended textbook for the course is by Robert Phillips titled
“Pricing and Revenue Optimization.” In additional to the “classic” material
reviewed in class and in the book, we will go through 2-3 cases that highlight
recent applications of these ideas, e.g., in keyword advertising, online
retailing, etc..

/ Connections to the Core

 I will assume that students are familiar with the content covered in
the managerial statistics, decision models, managerial economics and marketing
core courses. In more detail, the course assumes knowledge in the following

Managerial statistics: basic understanding of probability; probability distributions; expected value calculations; knowledge of regression and how to run a regression in excel

  • Business
    Analytics: some knowledge of spreadsheet modeling; linear & nonlinear
    optimization; how to formulate these problems in excel; how to use solver to
    get a solution; how to interpret the solution; how to interpret the shadow
    price variables (we will use this type of knowledge quite a bit). We will also
    use logistic regression as well as the tool used in the BA course (I will make
    it available anew).

  • Marketing /
    Economics: basic understanding of demand functions; what they mean; some
    examples; some basic understanding of consumer choice.