Abstract for: From Static Analysis to Dynamic Insight: Improving Freight Management Learning through System Dynamics Simulation

Traditional freight management instruction often relies on static and linear representations that fail to capture the dynamic complexity of real-world logistics systems. This study examines whether System Dynamics (SD) modeling and simulation can enhance students’ ability to reason about stocks, flows, delays, and feedback mechanisms in freight distribution. A quasi-experimental pretest–posttest design was implemented with 32 graduate-level students, grouped according to existing tutorial sections. Two groups received instruction incorporating SD simulation, while a control group engaged in traditional case-based analysis using an identical freight scenario. Learning outcomes were evaluated using an ANCOVA framework to control for prior knowledge. Results (R² = 0.784) indicate that pre-test performance is a strong predictor of post-test outcomes (p < 0.001). Students exposed to SD simulation achieved higher post-test scores, with an estimated mean difference of approximately eight points relative to the control group. This effect, while only marginally significant (p = 0.060), suggests a consistent positive trend associated with the intervention. SD simulation appears to function as an effective epistemic tool for helping students connect abstract concepts to the behavior of complex freight systems. While the results are constrained by sample size and study design, the study contributes to System Dynamics education by offering empirical insights into the role of simulation in fostering systems thinking within a domain-specific context Grammar check and improve readability