GIBSU-DEMATEL: Enhancing group decision-making by integrating expert satisfaction and uncertainty in interval judgments

In complex decision-making environments, expert judgments are often uncertain and divergent, making aggregation into a single numerical value problematic. The classical Decision-Making Trial and Evaluation Laboratory (DEMATEL) addresses interdependencies among criteria but aggregates expert inputs using simple averaging, which neglects opinion diversity and creates an artificial sense of certainty. To address these limitations, we propose Group Interval-Based DEMATEL method Balancing Satisfaction and Uncertainty (GIBSU-DEMATEL), a novel framework that represents group judgments as intervals and optimizes their construction to simultaneously maximize expert satisfaction and minimize judgmental uncertainty. This dual-objective approach ensures that aggregated results better reflect the diversity of expert perspectives while maintaining analytical rigor. Unlike existing interval or fuzzy DEMATEL variants, which focus primarily on uncertainty, GIBSU-DEMATEL formalizes the trade-off between expert satisfaction and uncertainty through an optimization function, producing causal maps that are both interpretable and socially acceptable. The framework is validated through a case study on learning management system selection in higher education, demonstrating improved robustness, higher satisfaction, and transparent representation of divergent opinions compared with classical, interval and fuzzy DEMATEL. Sensitivity analysis further confirms the adaptability and reliability of the method across decision scenarios.