SYSTEM DYNAMICS

AIM

The objective of this course is to develop students’ ability to analyze complex systems from a holistic perspective, model system behavior over time, and evaluate alternative policy scenarios. The course focuses on building dynamic models of socio-economic, industrial, and managerial systems using feedback loops, stock-flow structures, delays, and nonlinear relationships. Students are expected to adopt a systems thinking approach, effectively utilize simulation-based decision support tools, and develop sustainable solutions for real-world problems.

CONTENT

This course contains; Course introduction, overview of systems approach, basic concepts of systems thinking,Structure and behavior of complex systems, defining system boundaries,Introduction to causal relationships and feedback concepts,Causal loop diagrams and basic analysis methods,Stock and flow concepts, modeling system structures,Development and interpretation of stock–flow diagrams,Modeling approaches and mid-term review,Midterm,Dynamic behavior patterns and time delays,Simulation fundamentals and model testing methods,Model verification, validation, and sensitivity analysis,Policy design and alternative scenario studies,Application examples and selected case studies,Student work, project presentations, or general review,Overall evaluation, final studies, and course closure.

1. 1

   1. Analyze complex socio-technical and managerial systems using a systems thinking perspective and interpret their fundamental structures and behavior patterns.

   Taught by: Discussion Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Project Task, Quiz

2. 2

   2. Identify causal relationships (causal links) among system variables, determine their direction and polarity; analyze positive and negative feedback loops, construct causal loop diagrams, and explain the effects of these structures on system behavior.

   Taught by: Discussion Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Project Task, Quiz

3. 3

   3. Translate real-world problems into mathematical and simulation-based models using stock-and-flow structures.

   Taught by: Discussion Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Project Task, Quiz

4. 4

   4. Analyze system models through simulation, interpret dynamic behavior patterns (growth, oscillation, collapse, etc.), and evaluate results.

   Taught by: Discussion Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task, Quiz

5. 5

   5. Develop alternative policy and decision scenarios and assess their impacts on system performance comparatively.

   Taught by: Discussion Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Project Task, Quiz

6. 6

   6. Apply system dynamics methodologies to holistically model, analyze, and propose justified solutions for complex interdisciplinary problems.

   Taught by: Discussion Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Project Task, Quiz

WEEKLY PLAN

1. WEEK 1

   Course introduction, overview of systems approach, basic concepts of systems thinking

2. WEEK 2

   Structure and behavior of complex systems, defining system boundaries

3. WEEK 3

   Introduction to causal relationships and feedback concepts

4. WEEK 4

   Causal loop diagrams and basic analysis methods

5. WEEK 5

   Stock and flow concepts, modeling system structures

6. WEEK 6

   Development and interpretation of stock–flow diagrams

7. WEEK 7

   Modeling approaches and mid-term review

8. WEEK 8

   Midterm

9. WEEK 9

   Dynamic behavior patterns and time delays

10. WEEK 10

    Simulation fundamentals and model testing methods

11. WEEK 11

    Model verification, validation, and sensitivity analysis

12. WEEK 12

    Policy design and alternative scenario studies

13. WEEK 13

    Application examples and selected case studies

14. WEEK 14

    Student work, project presentations, or general review

15. WEEK 15

    Overall evaluation, final studies, and course closure

ASSESSMENT

• Rate of Midterm Exam to Success30%
• Rate of Final Exam to Success70%

WORKLOAD

READING

• Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin/McGraw-Hill.
• Lecture Notes

TEACHING STAFF

• Assist.Prof. Engin SANSARCICOORDINATOR
• Assist.Prof. Engin SANSARCI