<![CDATA[The evolution of digital technology has transformed workforce training through gamification and interactive simulation. This study introduces SIMBA, a novel simulation-based logistics operations training platform built in Unity, distinguished by its integration of multimetric behavioral analytics for real-time user performance evaluation. Unlike conventional gamified systems that predominantly assess user perceptions or learning outcomes qualitatively, SIMBA combines task-oriented behavioral metrics task duration, error rate, and score progression within a sequential four-level simulation representing authentic logistics operations: order entry, package classification, route planning, and delivery execution. Each level incorporates adaptive game mechanics, forward-chaining inference logic, and systematic behavior tracking to capture granular user interaction data. A cohort of 30 participants was assessed using non-parametric statistical methods (Friedman and Wilcoxon Signed-Rank tests), with correlation analyses (Pearson and Spearman) employed to examine inter-variable relationships. Results revealed statistically significant performance variation across levels and a strong inverse correlation between error rates and final scores, affirming the scoring model’s behavioral sensitivity. Through the use of heatmaps and line graphs, distinct learning trajectories growth, stagnation, and fluctuation were identified, highlighting SIMBA’s capacity for personalized training insights. This research advances the field by offering an integrated evaluation framework that operationalizes behavioral metrics within gamified simulations, enabling quantifiable, adaptive, and contextually valid assessment of user learning in logistics training. Future studies should expand the participant base, disaggregate the impact of specific game mechanics, and incorporate biometric or psychophysiological indicators to deepen understanding of user engagement and cognitive load.]]>
