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SYSTEM DYNAMICS MODELLING AND SIMULATION FOR INTELLIGENT ORGANIZATIONS

Syllabus

Updated A.Y. 2024-2025

Learning Objectives

The course aims to provide students with the theoretical and practical notions necessary for the interpretation and management of complex dynamic systems, while also equipping graduating students with advanced expertise in the following areas:

  1. Grasp the core principles of Systems Thinking and its progression into the discipline of System Dynamics.
  1. Master techniques for modeling and simulating dynamic systems using professional tools.
  2. Critically evaluate classic models in sustainable development (SDGs), including the classic models related to sustainability, such as Limits to Growth (Meadows).
  3. Apply dynamic modeling to complex and sustainable business scenarios.
  4. Prepare participants to develop customized models for real-world problems.

Upon completing this course, students will achieve the following outcomes:

  • Knowledge:
    • Demonstrate a solid understanding of the core principles of Systems Thinking and dynamic modeling.
    • Explain the historical evolution and diverse applications of the System Dynamics (SD) approach across different fields.
  • Comprehension:
    • Employ a systemic perspective to analyze complex real-world problems.
    • Assess existing static and dynamic models, focusing on their assumptions and limitations.
  • Application:
    • Construct static models (systems thinking diagrams) and dynamic models using specialized tools such as Vensim PLE.
    • Design and conduct simulations to predict system behaviors and assess policy outcomes in dynamic environments.
  • Cross-disciplinary Competencies:
    • Integrate systems thinking into organizational decision-making processes.
    • Develop advanced problem-solving skills applicable to complex, multi-faceted contexts.

Program

The course is structured into four main sections, each addressing a key thematic area of System Dynamics and its applications:

Section 1: Introduction and Context Analysis

  • Overview of the course objectives, structure, and project work methodology.
  • Socio-economic context analysis to identify relevant themes or needs related to Sustainable Development Goals (SDGs).
  • Tools and methods for identifying gaps and framing problems.

Section 2: Systems Thinking

  • Theoretical foundations of Systems Thinking.
  • Exploration of key models and frameworks.
  • Practical exercises: constructing systems thinking diagrams (causal loop diagrams) to capture feedback loops.
  • Application of Systems Thinking to real-world scenarios with a focus on sustainability and strategic decision-making.

Section 3: System Dynamics

  • Comprehensive study of System Dynamics methodology, including stock and flow diagrams.
  • Hands-on exercises: using Vensim PLE to build and simulate dynamic models.
  • Simulating complex systems to analyze behavior over time and assess policy impacts.

Section 4: Project Work

  • Individual or group-based project focused on a systemic solution addressing a gap related to SDGs.
  • Guidance on model construction, validation, and presentation.
  • Final project presentation with peer and instructor feedback.

Book

  • Senge, P. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization. Doubleday. (Selected chapters)
  • Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill. (Selected chapters)
  • Meadows, D. H., Meadows, D. L., & Randers, J. (1990). Beyond the Limits: Confronting Global Collapse, Envisioning a Sustainable Future. Chelsea Green Publishing. (Selected chapters)
  • Meadows, D. H., Randers, J., & Meadows, D. L. (2004). Limits to Growth: The 30-Year Update. Chelsea Green Publishing. (Selected chapters)
  • La Bara, L., & Fiorani, G. (2023). Sustainable development, stakeholders’ partnership, state-owned assets in a system thinking model (pp. 356-366). https://doi.org/10.25019/STR/2023.026
  • All slides, videos, and additional articles (including the project work format) are available on the course Team platform.

Teaching Methods

The course adopts a structured pedagogical approach aimed at fostering both theoretical comprehension and practical proficiency:

  1. Theoretical Lectures

These sessions integrate slide presentations with traditional blackboard teaching to deliver a thorough exposition of fundamental concepts, ensuring students grasp the theoretical underpinnings of the subject matter.

  1. PC-Based Simulations

Utilizing Vensim PLE software, students engage in interactive simulations designed to apply theoretical insights to real-world scenarios, thereby enhancing their analytical and problem-solving skills.

  1. Short Assignments and Practical Exercises
  • For attending students: These tasks are performed and analyzed during classroom sessions to encourage active participation and collaborative learning.
  • For non-attending students: Exercises must be independently completed and subsequently reviewed during the final examination to assess understanding and methodological rigor.
  1. Final Project Work

This capstone component is intended to synthesize the knowledge and skills acquired throughout the course. It includes:

  • Comprehensive Written Report: A detailed documentation of the project’s objectives, methodology, findings, and conclusions.
  • Development of Simulation Models: Creation of both a System Thinking (ST) model and a System Dynamics (SD) model, demonstrating the ability to design and implement complex system representations.
  • Oral Presentation: A formal defense of the project, adhering to the established Project Work Format, aimed at evaluating the student’s communication and presentation skills.

This multifaceted teaching methodology is designed to provide an optimal balance between conceptual understanding, practical application, and the development of critical thinking and professional competencies.

Exam Rules

The exam evaluates the student’s mastery of the subject, problem-solving skills, independent judgment, and use of System Thinking (ST) and System Dynamics (SD) methodologies, focusing on real-world applications and achieving Sustainable Development Goals (SDGs).

Presentation clarity and language proficiency are evaluated according to these criteria:

  1. Knowledge and understanding;
  2. Applying knowledge and understanding;
  3. Making judgments;
  4. Learning skills;
  5. Communication skills. 

Exam Components

The exam involves preparing and evaluating a Project Work, including a detailed written report and an oral presentation.

  • Written Report (70% of the final grade): This report must provide a thorough analysis of a real-world phenomenon, incorporating both qualitative and quantitative data. It should include original ST and SD models, completed exercises (conducted during the course or independently for non-attending students), and a clear identification of the SDGs addressed. The report should highlight how the research and models contribute to sustainable development.
  • Oral Presentation (30% of the final grade): Students are required to present their Project Work orally, following the guidelines outlined in the Project Work Format. This presentation aims to assess their communication skills, ability to articulate complex ideas, and depth of understanding of the subject.

Students may opt to reject the grade awarded and retake the exam at a later session. In this case, the new grade will supersede the previous one.

Grading Criteria

  • Not suitable: Major deficiencies or inaccuracies in knowledge and understanding; weak analytical and synthesis skills; excessive generalizations; poor critical thinking and judgment; incoherent presentation and inappropriate language.
  • 18-20: Basic but sufficient knowledge and understanding, with possible errors and generalizations; limited analytical and synthesis skills; arguments may lack coherence and precision in language.
  • 21-23: Adequate knowledge and understanding; reasonable analytical and synthesis skills; generally coherent reasoning with acceptable technical language.
  • 24-26: Good knowledge and understanding; solid analytical and synthesis skills; well-structured arguments, though occasional imprecision in technical language may occur.
  • 27-29: Strong knowledge and understanding; excellent analytical and synthesis skills; good independent judgment; arguments are well-presented with appropriate technical language.
  • 30-30L: Exceptional and in-depth understanding of the subject; outstanding analytical, synthesis, and critical thinking skills; original and well-articulated arguments presented with precise technical language.