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个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:系统工程研究所
学科:管理科学与工程. 系统工程
电子邮箱:yzhdang@dlut.edu.cn
Team Knowledge Formation and Evolution Based on Computational Experiment
点击次数:0000133844
论文类型:会议论文
发表时间:2016-11-04
收录刊物:EI、CPCI-S
卷号:660
页面范围:1-14
关键字:Team knowledge; Formation and evolution; Knowledge intensive team; Computational experiment
摘要:In knowledge intensive team, team knowledge referred to team-level knowledge emerged from knowledge interaction among members, is vital resources for enterprise innovation. So how the team knowledge forms and evolves is what this paper concerns. Firstly knowledge interaction process is described according to member's psychological and behavioral activities, then team knowledge emerging process in knowledge interaction is depicted based on members' memories, after that a task driven-artificial knowledge intensive team is established with computational experiment method by simulating knowledge interactions to achieve team knowledge formation and evolution. According to the experiments, the influences of team scale, team knowledge space, member's knowledge learning ability, knowledge interaction willingness and initial knowledge state on team knowledge formation and evolution are analyzed. The experiments results can provide reliable decision supports for managers to use team knowledge to improve enterprise innovation.