System Dynamics

Course manual 2018/2019

Course content

The course elaborates on the quantitative and qualitative analysis techniques that the students have learned in their bachelor and investigated in the Fundamentals of Information Studies course. In the System Dynamics course, students will learn how to model and analyse the dynamics of large-scale economic, social or technological systems and processes. System dynamics is grounded in the modern theory of nonlinear dynamics and control theory. Students will learn how to describe the structures of complex systems and build simulations of real-world problems. Students will discover the basic concepts of system dynamics: stocks and flows, feedback loops, control strategies, state oscillation and instability, S-shaped growth, overshoot and collapse, path dependency and other nonlinear dynamics. In the course, students will explore different problem domains, build up their skills by practicing on small assignments, and finally demonstrate their knowledge and skills in a project, using a system dynamics modelling environment.

Study materials

Literature

• Sterman, J. (2000). Business dynamics: Systems thinking and modeling for a complex world. Boston: Irwin/McGraw-Hill.

Practical training material

• Practical training material will be made available via the Canvas system.

Software

• Vensim or Netlogo, will be announced during the course.

Objectives

After completing the course, the student is able to:

1. explain the added value of modelling to science and society;
2. describe the properties of several classes of modelling approaches and advantages of systems dynamics approach;
3. formulate models of complex economic, social or technological systems;
4. identify the structure of the system, describe the stocks and flows, and suggest feedback loops;
5. explain the features of nonlinear dynamics, such as state oscillation and instability, S-shaped growth, overshoot and collapse, path dependency;
6. implement the models in a system dynamics software and analyse the process dynamics;
7. formulate ordinary differential equations (ODEs) behind the system dynamics model, analyse and solve ODEs analytically and numerically;
8. explain and analyse how discretisation and numerical algorithms affect the accuracy of simulation results;
9. calibrate model parameters and validate the model against experimental data;
10. perform model sensitivity analysis;
11. explain how system dynamics modelling can be used in decision making and business optimization;
12. discuss the strategies for controlling complex dynamical systems.

Teaching methods

• Lecture
• Working independently on e.g. a project or thesis
• Self-study
• Presentation/symposium
• Seminar
• Supervision/feedback meeting

Course structure:

• Weekly lectures on the theoretical and practical aspects of System Dynamics (4 hours per week)
• Weekly seminars linking the topics of the week to the practical implementations and studies (4 hours per week)

Students will work on the themes addressed in this course individually and in groups. In the first 4 weeks you will build up practical skills individually; and in the last 4 weeks you will work in teams of 3-4 students, where you will study a complex system and integrate the results in a group project.

Learning from each other and benefiting from the wide variety of backgrounds and experiences is stimulating the learning process. During the seminars and working group sessions, you will receive feedback on your individual work from your teaching assistants and from fellow students, and you will give feedback to their work.

Attendance

In OER-B of the programme no requirements regarding attendance are mentioned.

Assessment

Inspection of assessed work

All the comments to the assessed assignment reports will be provided via the Canvas. 

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

• dr. Valeria Krzhizhanovskaya