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Pricing Analytics

Course code
Course type
BSc Course
Weekly Hours
FS 2022
Prof. Dr. Arne Karsten Strauss
Please note that exchange students obtain a higher number of credits in the BSc-program at WHU than listed here. For further information please contact directly the International Relations Office.

Pricing analytics and revenue management focuses on how a firm should model demand, set and update pricing and product availability decisions across its various selling channels in order to maximize its profitability. 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.

Within the broader area of pricing theory, the course places emphasis on tactical optimization of pricing and capacity allocation decisions, tackled using demand modeling and constrained optimization – the two main building blocks of revenue management systems.

Case studies provide hands-on experience of the subject. Students are using R for most of the exercises within the RStudio environment, involving training on both demand modeling and optimization problems.

  • Ability to explain, apply and implement fundamental price optimization approaches to business problems
  • Ability to recognize the business conditions conductive to application of pricing analytics
  • Ability to model demand (using a limited range of methods) and to estimate price elasticities
T. Bodea and M. Ferguson: Segmentation, Revenue Management and Pricing Analytics. Routledge 2014.
Lectures and seminars discussing weekly homework assignments (mostly case-study-based).
Group assignment: 40%

Exam: 60%

The group assignment is formative, whereas the exam is summative

Students unfamiliar with R programming should learn about the basics of R in advance of the module; optional preparation materials will be provided.
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