With the advancement of society and information technology, the connections between people, organizations, and countries have become increasingly close, leading to the emergence of various conflicts. These conflicts span multiple fields such as economy, trade, healthcare, and the environment. Notable examples include trade frictions between China and the United States, the price war between JD.com and GOME, cross-border water rights issues, compensation disputes related to demolitions, and medical malpractice cases. Without effective intervention and management, conflicts can result in significant property losses and casualties. These issues have impacted people's lives at different levels and to varying degrees, becoming a focal point for individuals, managers, decision-makers, academics, and government departments.
Dual conflicts are prevalent in our lives. On one hand, internal members of a decision-making body often experience preference conflicts due to differences in cognitive levels and knowledge backgrounds. On the other hand, decision-making bodies encounter game conflicts because of incompatible goals. Helping stakeholders reach consensus in such dual conflict environments is a critical issue for academia and management practice.
Professor Zhang Hengjie and his research team have studied this dual conflict problem and applied for the 2021 National Natural Science Foundation of China (General Program) with their project titled Consensus-based Group Decision Making within the Graph Model and its Application. This project addresses the practical needs of conflict management by exploring consensus decision-making in dual conflict environments through the intersection of graph models and group consensus decision-making. The project aims to assist stakeholders in achieving consensus in such settings. The theories and methods involved include group decision-making, consensus-reaching processes, graph models for conflict resolution, optimization theory and methods, social network analysis, game theory, and machine learning. The research results will enhance the existing group consensus decision-making system, providing decision-making support for resolving conflicts, such as transboundary water pollution disputes in river basins.
National Natural Science Foundation of China (General Program): 72171075
