针对大群体应急决策中专家有效信息提取不准确、共识达成难的问题，提出一种新的基于多维多层次商空间结构的大群体应急决策方法。通过引入模糊商空间理论，将复杂决策问题进行解耦，构建多维多层次商空间结构，并基于统计检验确定最优聚类层次，实现细粒度维度下专家有效信息的精准提取与大群体专家的高效聚类；结合应急决策问题的时效性，构建共识反馈调整模型以达到群体共识阈值；合成不同偏好的商空间结构得到最终偏好信息矩阵，计算各方案得分并进行排序择优。将该方法应用到森林火灾应急决策案例中，验证了方法的有效性和可行性。

To address the problems of inaccurate extraction of valid information from experts and difficulty in consensus reaching in large-group emergency decision-making, a novel large-group emergency decision-making method based on a multi-dimensional and multi-level quotient space structure is proposed. By introducing fuzzy quotient space theory, complex decision-making problems are decoupled to construct the multi-dimensional and multi-level quotient space structure. The optimal clustering level is determined via statistical tests, realizing precise extraction of valid information from experts at fine-grained dimensions and efficient clustering of large-group experts. Considering the timeliness of emergency decision-making, a consensus feedback adjustment model is constructed to achieve the group consensus threshold. Quotient space structures with different preferences are then synthesized to obtain the final preference information matrix, and the scores of each alternative are calculated for ranking and selection. The proposed method is applied to a forest fire emergency decision-making case to verify its effectiveness and feasibility.