Opinions-integrated consensus models for large-scale group decision-making in emergency medical capability evaluation

Emergency medical capability is critical for community resilience and emergency response. However, existing evaluation methods mainly rely on expert insights while ignoring public perspectives. To bridge this gap, two opinions-integrated consensus models for large-scale group decision-making (LSGDM) are proposed. First, public opinions are analyzed using fuzzy-set Qualitative Comparative Analysis to determine criteria weights. An importance slider and programming model are introduced to quantify the relative importance of public opinions. A backtracking identification method is introduced to adjust expert insights and facilitate consensus. Based on these, a comprehensive consensus model and a professional consensus model are developed. Simulation and sensitivity analysis demonstrate the effectiveness of both models in consensus reaching. Overall, the professional consensus model performs better due to its stricter judgment mechanism. Additionally, the performance of both models is sensitive to parameter settings. Accordingly, the adaptability of both models is further discussed in terms of public participation and acceptance, evaluation timeliness, and expert heterogeneity. This study provides a systematic approach to integrating public opinions and expert insights in LSGDM, enhancing the credibility and applicability of evaluation results.