Author Identifier (ORCID)
Steven D'Alessandro: https://orcid.org/0000-0001-7480-232X
Fons Wijnhoven: https://orcid.org/0000-0001-8231-7535
Abstract
This book offers a practical, model-driven pathway for reasoning about uncertain futures in business and public policy using system dynamics with Insight Maker. It begins by motivating why historical data alone often fail to predict social change, and it introduces the core language of system dynamics—stocks, flows, feedbacks, delays, and auxiliary variables—alongside the complementary use of agent-based modeling. Through business-relevant cases (e.g., park management trade-offs, epidemic–economy interactions, and industry competition), the book demonstrates how non-linear structure generates counter-intuitive dynamics, why scenario analysis is essential, and how to translate causal loop diagrams into stock-and-flow simulations. Readers are guided step-by-step to build, parameterize, and run simulations in the free, browser-based Insight Maker environment, including the use of converters, sliders, and storytelling for collaborative exploration. Subsequent chapters catalogue common system archetypes, outline qualitative scenario techniques (2×2 and actor scenarios), and detail model assurance through triangulated validity checks, unit/constraint verification, and sensitivity analysis. The result is an accessible yet rigorous methodology that integrates empirical evidence with theory and expert judgment, enabling students, managers, and policymakers to map causal structure, test assumptions, and design policies under deep uncertainty—while laying foundations for digital-twin applications where simulations are continuously informed by live data.
Document Type
Book
Date of Publication
2025
Contributor's Note
Freely available to assist with teaching. All exercises are available online.
Type of File
Publisher
Edith Cowan University
School
School of Business and Law
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Wijnhoven, F. & D'Alessandro, S. (2025). System dynamics with Insight Maker. Edith Cowan University. https://doi.org/10.25958/g8d5-4e98