This book explores the latest theories, methods, and applications of consensus modeling. It proposes a variety of consensus modeling methods for different decision-making contexts, including conflict risk mitigation in group decision-making, integration with the failure mode and effects analysis technique, consideration of over-adjustment and flexible consensus, social network large-group decision-making environments involving multiple consensus costs, and multi-agent collaborative decision-making with consideration of trade-offs between revenue and reputation. In addition, this book discusses the application and implementation process of the proposed consensus modeling techniques in real-world decision-making, including collecting decision data, organizing decision-making groups, controlling the decision-making process, and evaluating the results.

We encourage researchers, academics, students, business managers, and policy makers engaged in a variety of real-world decisions characterized by group decision-making (e.g., emergency decisions, public affairs decisions, and major corporate decisions) to pay attention to the proposals presented in the book. This book systematically describes the latest theories, methods, and applications of consensus modeling with a view to providing practical methodological support for corporate decision-making, governmental decision-making, and so on. Special emphasis is placed on the fact that this book can provide students, especially graduate students, with a comprehensive perspective on the study of consensus modeling. For businesses and governments, this book provides methodological support for how to merge inputs from multiple parties to obtain a majority-approved consensus solution (at minimal group cost) and ultimately develop group wisdom.

Analyzes the mechanism of consensus modeling for promoting group wisdom Explores the integration of consensus modeling and the performance in multiple decision-making scenarios Discusses the practical applications of consensus modeling and provides rich experimental scenarios

Auteur

Sumin Yu is an Associate Professor, Master Supervisor, and Vice Dean of the College of Management, Shenzhen University, Shenzhen, China. Yu received her Ph.D degree in Management from Central South University in 2018. Her research areas include electronic commerce, information management, decision theory and methods, large-scale decision-making and consensus, innovation in healthcare delivery models, tourism management, etc. She chaired a project of National Natural Science Foundation. She has now published more than 30 international journal papers in top journals and conference proceedings, including IEEE Transactions on Fuzzy Systems, IEEE Transactions on Computational Social Systems, Information Fusion, Information Sciences, Knowledge-Based Systems, Applied Soft Computing, Computers & Industrial Engineering, Group Decision and Negotiation, International Transactions in Operational Research, among others. She co-authored two books published in Springer Nature. Her h-index is 18 with more than 1300 citations received in Google Scholar. A total of 5 articles were selected into ESI Global High Citation Paper Database, among which 3 articles were selected as hot papers. She serves as a reviewer in many top-tier international journals in related areas to decision analysis, soft computing, consensus modeling, and large-scale decision-making.

Zhijiao Du is a Faculty-Appointed Assistant Professor at the Business School, Sun Yat-Sen University, Shenzhen, China. Dr. Du received his Ph.D degree in Management from Sun Yat-Sen University in 2022. He chaired a project of the National Natural Science Foundation of China, a project funded by China Postdoctoral Science Foundation and a project of Guangdong Provincial Philosophy and Social Science Planning. His research interests include social network big data analysis, intelligent group decision-making, large-scale decision-making and consensus, digital supply chain finance, corporate venture capital, etc. He has now published more than 25 academic articles in top journals and conference proceedings, including Decision Support Systems, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Computational Social Systems, Information Fusion, Information Sciences, Knowledge-Based Systems, Computers & Industrial Engineering, Group Decision and Negotiation, among others. Two of the articles was selected into ESI Global Database of Highly Cited Papers in Computer Science. He co-authored two books published in Springer Nature. His h-index is 13 with more than 1000 citations received in Google Scholar. He serves as a reviewer in many top-tier international journals in related areas to decision analysis, supply chain management.

Xuanhua Xu is a Professor and Doctoral Supervisor at School of Business, Central South University. He was a visiting scholar on official assignment at the Department of Information Systems, School of Computer Science, National University of Singapore for one year. He is the Director of the Research Center for Big Data and Intelligent Decision Making. His research interests include complex large group decision-making theory and methodology, big data intelligent decision-making methodology, financial risk regulation theory and methodology, information system and decision support system, emergency management, risk analysis and management, complex engineering decision-making methodology and risk analysis. He presided over one major project of National Natural Science Foundation of China (NSFC), one national key R&D program, one key project of National Social Science Foundation of China, and four general projects of NSFC. He has published more than 180 academic papers in leading academic journals at home and abroad, such as Decision Support Systems, Information Fusion, Information Sciences, IEEE Transactions on Fuzzy Systems, Expert Systems with Applications, Knowledge-Based Systems, Group Decision and Negotiation, Reliability Engineering and Syste

Contenu

Introduction.- Literature Review and Preliminary Knowledge.- Consensus Modeling to Manage Conflict Risk Mitigation.- Consensus Modeling with Failure Mode and Effects Analysis.- Enhanced Minimum-Cost Consensus Modeling.- Multi-Stage Multi-Cost Consensus Modeling in SNLSDM.- Comprehensive Loss Analysis-Based Consensus Modeling.- Practical Applications.- Conclusions and Future Research Directions.