IE 559

Course ID:

Course Code & Number

IE 559

Course Title

Revenue Management

Level

MS

Credit Hours/ ECTS Credits

(3+0+0) 3 TEDU Credits, 7.5 ECTS Credits

Year of Study:

Master

Semester:

Fall

Type of Course:

Elective

Mode of Delivery:

Face-to-face

Language of Instruction:

English

Pre-requisite / Co-requisite::

Catalog Description

Pricing. Price optimization, Price Differentiation, Revenue Management, Capacity Determination and Assignment, Overbooking Strategies, Discount Management.

Course Objectives

Pricing Fundamentals: Price Theory, Demand Models, Game Theoretic Models, Consumer Behaviour. Pricing in different industries: advertising, airlines, cruise lines, utilities, dining, entertainment,  healthcare, hospitality. Quantity based revenue management: single resource capacity control, network capacity control, overbooking. Price based revenue management: dynamic pricing, markdowns and discounting, auctions. Customer behaviour and market response models. Estimation and forecasting. Assortment planning and optimization.

Software Usage

Course Learning Outcomes

(Tentative - yet to be approved by the Senate)

Upon succesful completion of this course, a student will be able to
1. Gain an understanding of pricing fundamentals.
2. Compare pricing approaches in different industries.
3. Apply quantity based revenue management methodologies.
4. Apply price based revenue management methodologies.
5. Choose the appropriate demand model for the industrial sector and market.
6. Choose and apply the demand estimation methodologies using market response models
8. Apply assortment planning and optimization methodologies.

Learning Activities and Teaching Methods:

Telling/Explaining Discussion/Debate Reading Demonstrating Problem Solving Case Study/Scenarion Analysis

Assessment Methods and Criteria:

Test / Exam Quiz Case Studies / Homework

Assessment Methods and Criteria Others:

Design Content

Recommended Reading

1. Makridakis, S., Wheelwright, S., Hyndman, R.J. (1998), Forecasting Models and Applications, Wiley 2. Hanke, J.E., Wichern, D. (2008), Business Forecasting, Prentice Hall

Required Reading

1. Bowerman, B.L., O’Connell, R., Koehler A. (2004), Forecasting, Time Series and Regression, Thomson Brooks

Grading

Learning Activities and Teaching Methods Others:

Course Coordinator:

Student Workload:

Workload	Hrs
Course Readings	52
Hands-on Work	50
Exams/Quizzes	40

Course & Program Learning Outcome Matching: