Grounded theory modeling based on evidence fusion with group consensus reaching

Abstract Grounded theory, a qualitative research method, typically relies on collaborative, subjective analysis among researchers. However, such subjective collaborative processes often raise concerns regarding transparency, consistency, and reliability of the results. In this study, we introduce a novel quantitative approach, Grounded Theory Modeling based on Evidence Fusion and Group Consensus Reaching (GCR-GT), to provide a clear and systematic procedural guideline for the collaborative process. GCR-GT quantitatively captures researchers’ judgments through evidence-based functions and employs a structured consensus-reaching mechanism, transforming the qualitatively ambiguous theory-building and collaborative processes into clear, quantitative computational steps. Specifically, researchers construct initial relationships between concepts based on evidence extracted from data, which are represented as belief distribution functions. These functions undergo multi-round consensus evaluation and iterative feedback adjustments until group consensus is achieved. During this process, uncertainty and similarity are used to quantitatively measure the weight and reliability of each researcher’s opinion, and the analytical generalized combination (AGC) rule is used to fuse group opinions and integrate relationships across coding hierarchies. After reaching a consensus, the opinions are further integrated to determine the strength of the relationship between concepts and categories, forming the theoretical framework. Finally, this study validates the practicality and effectiveness of the method through a case study on the driving mechanisms of artificial intelligence-enabled mass personalization. This method not only enhances the scientific rigor and effectiveness of collaborative grounded theory processes but also provides a generalizable methodological perspective for collaborative qualitative research in the social sciences and related fields.