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2020/2021  KAN-CDSCV1002U  Game Theory for Business and Data-driven Decision Making

English Title
Game Theory for Business and Data-driven Decision Making

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 60
Study board
Master of Science (MSc) in Business Administration and Data Science
Course coordinator
  • Raghava Rao Mukkamala - Department of Digitalisation
Main academic disciplines
  • Information technology
  • Statistics and quantitative methods
  • Economics
Teaching methods
  • Online teaching
Last updated on 10-06-2020

Relevant links
Learning objectives
  • Summarize different fundamental concepts, techniques and methods of game theoretic approach.
  • Critically assess the applicability of various game-theoretic approaches for business strategies and real-world competitive situations.
  • Demonstrate the understanding of various strategies for different types of games and their suitability to wide variety of business scenarios or societal phenomena.
  • Exhibit deeper knowledge and understanding of the topics as part of the project and the report should reflect on critical awareness of the methodological choices with written skills to accepted academic standards.
Course prerequisites
The course has no prerequisites. But the course requires an interest in and commitment to learn and acquire necessary skills to understand the concepts of Game Theory and hands-on exercises. However, no prior coding experience or knowledge about Game Theory is required.
Prerequisites for registering for the exam (activities during the teaching period)
Number of compulsory activities which must be approved (see s. 13 of the Programme Regulations): 3
Compulsory home assignments
There will be 3 multiple choice quizzes that will be conducted at diffident stages of the course to test to student understanding of core concepts of the course. In order to qualify for the final exam, the students have to participate in the quizzes and pass 2 quizzes out of 3.

There will not be any extra attempts provided to the students before the ordinary exam. If a student cannot participate in the activities due to documented illness, or if a student does not get the activity approved in spite of making a real attempt, then the student cannot participate the ordinary exam.
Before the re exam the student will be given one extra attempt: one home assignment (10 pages) to make up for two mandatory activities.
Examination
Game Theory for Business and Data-driven Decision Making:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Individual or group exam Individual oral exam based on written group product
Number of people in the group 2-4
Size of written product Max. 15 pages
Assignment type Project
Duration
Written product to be submitted on specified date and time.
20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and also the individual oral performance, covering the topics of the course.
Course content, structure and pedagogical approach

Game theory has applications in numerous fields, such as Computer Science, Economics, Social Science and political science. Game theory is also now finding its applications in data-driven decision making as well. Many business decisions can be modelled and analyzed using game theory. Data-driven decision making has embraced a wide variety of business functions: accounting, finance, operations, strategy and organizational design.

 

This course aims to provide basic understanding of various game-theoretic concepts and its application in different application areas. In this course, basic tools of game theoretic analysis will be introduced and we will outline some of the applications of game theory, primarily in economics and business domains, such as market competition, bargaining, auctions and competitive bidding.

 

The course will cover different types of games as listed below:

 

  • Bi-matrix games,
  • Zero-Sum vs. Non-Zero-Sum games,
  • Extensive vs. Normal forms games,
  • Perfect vs. Imperfect Information games,
  • Symmetric vs. Asymmetric game,
  • Cooperative vs. Non-Cooperative game,
  • Simultaneous vs. Sequential games
  • Static vs. Dynamic games.

 

All the games will be covered with some practical examples and their applicability to different scenarios.

 
Description of the teaching methods
This is a fully online course. The lectures and exercises will be delivered in 10 sessions, where each session contains 2-hour of lecture followed by a 2-hour exercise session later. All lectures sessions will be prerecorded and will be uploaded to the canvas well in advance. Exercises sessions will be online interactive sessions.

The lectures will be combined with some pragmatic hands-on exercises using various software tools for game theory.

Teaching Materials:
Lecture slides
Readings
Scientific articles
Handouts
Feedback during the teaching period
As part of the mandatory assignments, the students will have to take 3 multiple choice quizzes. In addition to that there will be hands-on exercise as part of exercises session in the classroom. The students will receive feedback on both the activities. For the quizzes, feedback on quizzes about which questions are correct or wrong will be provided to the students. Moreover, feedback on the hands-on exercises will be also provided in the classroom.
Student workload
Lectures 20 hours
Exercises 20 hours
Prepare to class 80 hours
Project work and report 76 hours
Exam and prepare 10 hours
Total 206 hours
Expected literature

Books and Scientific Articles
Lecture slides
Readings
Hand-on exercises

 

Some suggested text books for reference:

 

  • Papayoanou, Paul A., Dave Charlesworth, and Debbie Charlesworth. Game theory for business: A primer in strategic gaming. Probabilistic Pub., 2010.
  • Rubinstein, Ariel, and Martin J. Osborne. "A course in game theory." The MIT Press, (2000).
  • Binmore, Ken. "Fun and Games: A Text on Game Theory (Lexington, MA, DC Heath)." (1992).

 
Last updated on 10-06-2020