Dang Yanzhong
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Team Knowledge Formation and Evolution Based on Computational Experiment
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Indexed by:会议论文

Date of Publication:2016-11-04

Included Journals:EI、CPCI-S

Volume:660

Page Number:1-14

Key Words:Team knowledge; Formation and evolution; Knowledge intensive team; Computational experiment

Abstract: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.

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Gender:Male

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:系统工程研究所

Discipline:Management Science and Engineering. Systems Engineering

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