Online Course Guide of WHU –

Find all modules and courses of our degree programs.

Please use the filters below to select the term (spring or fall) as well as the respective program (BSc, MSc, MBA, Exchange, Doctoral) of your choice for an overview of all modules offered at WHU. The courses are listed under the modules. Please click on a module to see which courses are part of it. If you would like to find out more about a certain course, click on the name of the course to see detail information. The location of the lecture will be revealed after your course registration on myWHUstudies.

Spring term counts from January - August, fall term counts from September - December.

Important for Exchange Students: As the Full-Time and Part-Time MBA Programs utilize a modular course structure, the dates on which students begin and end the exchange are flexible. Please find here a chronological overview of the preliminary course offering for Fall and Spring.

Spring 2021  ›  Bachelor of Science  ›  Bachelor of Science - 4th Semester  ›  Data Science for Business and Pricing Analytics

Pricing Analytics

Course Code:
SCM462
Lecturers:
Prof. Dr. Arne Karsten Strauss
Course Type:
BSc Course
Week Hours:
2,0
Term:
Spring 2021
Language:
Englisch
Credits:
3,0
(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.

Date
Time
08:00 AM till 11:15 AM
Wednesday, 10/03/2021
08:00 AM till 11:15 AM
Tuesday, 23/03/2021
08:00 AM till 11:15 AM
Monday, 26/04/2021
02:00 PM till 05:00 PM
  • 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
90