Group Decision

Group decision-making (GDM) research focuses on developing methods to effectively aggregate diverse individual preferences into a collective choice, addressing inherent complexities like uncertainty and conflicting opinions. Current research emphasizes advancements in handling various data types (e.g., linguistic terms, fuzzy sets, probabilistic information) and incorporating factors like sentiment analysis, psychological biases, and privacy concerns into GDM models, often employing techniques like fuzzy logic, granular computing, and multi-criteria decision analysis. These improvements aim to enhance the accuracy, efficiency, and fairness of group decisions across diverse applications, from resource allocation to collaborative problem-solving.