The consensus and dissent model in the graph model for conflict resolution with interval fuzzy preferences with application to doctor-patient disputes

Abstract

Strategic conflicts, such as doctor–patient disputes, have become a major societal concern, with increased media attention exacerbating tensions among stakeholders. A key challenge in such conflicts is information asymmetry, which leads to uncertainty in the expression of decision-maker (DM) preferences. Existing consensus models in conflict analysis typically assume clear and consistent DM preferences, limiting their applicability in real-world scenarios characterized by ambiguity and complexity. Thus, within the framework of the graph model for conflict resolution (GMCR), this paper first attempts to characterize DM’s uncertainty and resolve conflicts by considering interval fuzzy consensus and dissent preference between two DMs. The innovation of this work lies in promoting the research of consensus and dissent model in GMCR in uncertain fields. Specifically, the first work reflects the DM’s real judgments over states using interval fuzzy scales and then converts them into clear values, which can be applied to conflict analysis process. More importantly, the logical stability definitions and matrix stability definitions of the consensus and dissent model in the GMCR framework under interval fuzzy preference relations (IFPRs) for two DMs are determined. In addition, we introduce the specific solving and analysis steps for resolving real life conflicts by using proposed models. Compared to existing consensus models in conflict decision-making with crisp preferences, DM’s IFPRs in new proposed GMCR provides a new way to characterize DM’s uncertainty and constructs a set of stability definitions in uncertainty decision making situations. Finally, in order to illustrate the correctness and scientificity of the new proposed GMCR model, it is applied to real-life doctor-patient disputes in China. The model’s validity and applicability are demonstrated through a case study of doctor–patient disputes in China, with the stability analysis offering practical insights for conflict resolution in uncertain environments.