{"title":"Multi-agent simulation of team stability evolution: A complexity science perspective","authors":"Liang Yaqi, Hou Guisheng, Jiang Xiujuan","doi":"10.1016/j.joi.2025.101655","DOIUrl":null,"url":null,"abstract":"<div><div>Drawing on the theory of complex adaptive systems, this study develops a multi-agent model of a research innovation team through the NetLogo simulation platform. The operational mechanisms of the research innovation team are delineated into three distinct processes: demand-driven collaborative mechanism, objectives-driven knowledge sharing mechanism, and outcome-driven dynamic trust mechanism. These processes describe the individual decision-making of team members and the complex interactions among them. By analyzing the evolutionary patterns of research innovation team stability under various influencing factors, this study shows that: (1) While the effects on team stability vary across different parameter settings, the underlying evolutionary patterns remain largely consistent. (2) The influences of different factors on team stability exhibit nonlinear characteristics. These findings offer theoretical insights and decision-making support for fostering stable development within research innovation teams.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101655"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Informetrics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751157725000197","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Drawing on the theory of complex adaptive systems, this study develops a multi-agent model of a research innovation team through the NetLogo simulation platform. The operational mechanisms of the research innovation team are delineated into three distinct processes: demand-driven collaborative mechanism, objectives-driven knowledge sharing mechanism, and outcome-driven dynamic trust mechanism. These processes describe the individual decision-making of team members and the complex interactions among them. By analyzing the evolutionary patterns of research innovation team stability under various influencing factors, this study shows that: (1) While the effects on team stability vary across different parameter settings, the underlying evolutionary patterns remain largely consistent. (2) The influences of different factors on team stability exhibit nonlinear characteristics. These findings offer theoretical insights and decision-making support for fostering stable development within research innovation teams.
期刊介绍:
Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.