GRA 4135 Decision Theory and System Dynamics

GRA 4135 Decision Theory and System Dynamics

Course code:
GRA 4135
Department:
Credits:
6
Course coordinator:
Kim van Oorschot
Course name in Norwegian:
Decision Theory and System Dynamics
Product category:
Master
Portfolio:
Semester:
2018 Autumn
Active status:
Active
Level of study:
Master
Teaching language:
English
Course type:
One semester
Introduction

Accelerating economic, technological, social, and environmental change challenge managers and policy makers to learn at increasing rates, while at the same time the complexity of the systems they need to manage is growing. Many of the problems they face now arise as unanticipated side effects of their own past decisions. All too often the decisions or policies implemented to solve important problems fail, make the problem worse, or create new problems. Effective decision making and learning in a world of growing dynamic complexity requires systems thinking, expanding the boundaries of mental models, and developing tools to understand how the structure of complex systems creates their behavior.

This course introduces students to system dynamics as a tool for analyzing and modeling complex business problems and strategies. As such, system dynamics enables understanding the structure and dynamics of complex systems. System dynamics is also a rigorous modeling method for developing formal computer simulations of complex systems and use these simulations to design more effective policies and make better decisions. These simulation models can be used to create management flight simulators: microworlds where space and time can be compressed and slowed so decision makers can experience the long-term side effects of decisions, speed learning, develop our understanding of complex systems, and design structures and strategies for greater success (Sterman, 2000, pp. vii).

Learning outcomes - Knowledge

After taking the course students should:

• Be able to explain how the structure of business systems creates their behavior and performance
• Understand how well-meant policies often inadvertently create business performance issues, rather than solve them
Learning outcomes - Skills

After taking the course students should be able to:

• Develop simulation models of business systems;
• Simulate what-if scenarios, and use these scenarios to develop better policies.
• Translate a problem description into a conceptual or qualitative model
• Translate the conceptual model into mathematical equations
• Develop a simulation model, learning to use new software
• Translate quantitative, simulation results into “best practices” for management, solving the case
Learning Outcome - Reflection

After completing the course, students will be able to reflect on their “old way of thinking” and how it differs from the new way of thinking. Students will be able to recognize when a problem is dynamic, and when they should apply the “new way of thinking”. Students will learn to look at business or social problems from a broader perspective.

Course content
• Learning in and about complex systems
• The modeling process
• Causal loop diagramming
• Structure and behavior of dynamic systems
• Stocks and flows and their dynamics
• Dynamics of simple structures, like S-shaped growth
• Delays
• Modeling decision making and human behavior
• Supply chains and the origin of oscillations
Learning process and requirements to students

Different learning methods will be used in this course, for instance lectures, individual exercises, group work, and presentations about existing models. Firstly, studying the course material (lecture slides and compulsory literature) is required to get a grasp of basic concepts. Secondly, different kinds of exercises will be given to practice the new way of thinking and to practice with the new software and to learn how to develop simulation models. Finally, students have to deliver a group assignment based on a case study in a given topic. The assignment can be executed in groups of up to 4 persons.

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class that is not included on itslearning or text book.

Software tools
No specified computer-based tools are required.

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Qualifications

All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Required prerequisite knowledge

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Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA 41351
ECTS
Internal and external examiner
Resit:
Examination when next scheduled course
100No 6 Week(s)Group/Individual ( 1 - 4 )Group assignment / term paper: students will have to build a simulation model from scratch about a certain business problem. This model then needs to be used to develop and simulate different decisions. Based on the outcome of the simulations, students have to choose the best decision and motivate their choice.
Exams:
 Exam category: Submission Form of assessment: Written submission Weight: 100 Invigilation: No Grouping (size): Group/Individual (1-4) Duration: 6 Week(s) Comment: Group assignment / term paper: students will have to build a simulation model from scratch about a certain business problem. This model then needs to be used to develop and simulate different decisions. Based on the outcome of the simulations, students have to choose the best decision and motivate their choice. Exam code: GRA 41351 Grading scale: ECTS Resit: Examination when next scheduled course
Exam organisation:
Ordinary examination
Total weight:
100