Mingshuo Cao , Qi Sun , Francisco Chiclana , Yujia Liu , Tiantian Gai , Yiling Yang , Jian Wu
{"title":"Trust driven group decision making: Research progress and prospects from the perspective of consensus","authors":"Mingshuo Cao , Qi Sun , Francisco Chiclana , Yujia Liu , Tiantian Gai , Yiling Yang , Jian Wu","doi":"10.1016/j.cie.2025.111101","DOIUrl":null,"url":null,"abstract":"<div><div>Trust driven Group Decision Making (TGDM) is a new type of decision making process conducted through trust relationships and information exchange between individuals in the social network environment. By systematically organizing the research progress of TGDM and exploring its future research directions, the GDM research for consensus will be promoted. Firstly, this article combs the development status and research trends in recent years based on bibliometrics methods, and then summarizes and discusses the important literature related to TGDM. Secondly, it defines the scientific research category and basic framework of GDM and TGDM. Thirdly, the basic related concepts of TGDM problems are summarized, and then its characteristics and function are analyzed. Finally, it analyzes the problems and challenges faced by TGDM research and explores future research directions. It finds that many scholars have constructed multi-dimensional TGDM models from different perspectives, which have shown wonderful application performance in fields such as product design, failure mode and effects analysis, meta universe virtual communities, and Water–Energy–Food. In addition, it will be a very promising research direction to in-depth investigate TGDM driven by scene, behavior and decision maker’s personality characteristics.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111101"},"PeriodicalIF":6.7000,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360835225002475","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Trust driven Group Decision Making (TGDM) is a new type of decision making process conducted through trust relationships and information exchange between individuals in the social network environment. By systematically organizing the research progress of TGDM and exploring its future research directions, the GDM research for consensus will be promoted. Firstly, this article combs the development status and research trends in recent years based on bibliometrics methods, and then summarizes and discusses the important literature related to TGDM. Secondly, it defines the scientific research category and basic framework of GDM and TGDM. Thirdly, the basic related concepts of TGDM problems are summarized, and then its characteristics and function are analyzed. Finally, it analyzes the problems and challenges faced by TGDM research and explores future research directions. It finds that many scholars have constructed multi-dimensional TGDM models from different perspectives, which have shown wonderful application performance in fields such as product design, failure mode and effects analysis, meta universe virtual communities, and Water–Energy–Food. In addition, it will be a very promising research direction to in-depth investigate TGDM driven by scene, behavior and decision maker’s personality characteristics.
期刊介绍:
Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.