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Team Knowledge Formation and Evolution Based on Computational Experiment

  • Yutong LiEmail author
  • Yanzhong DangEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 660)

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.

Keywords

Team knowledge Formation and evolution Knowledge intensive team Computational experiment 

Notes

Acknowledgments

This work is partly supported by the National Natural Science Foundation of China under Grant No. 71471028.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2016

Authors and Affiliations

  1. 1.School of PsychologyLiaoning Normal UniversityDalianChina
  2. 2.Institute of System EngineeringDalian University of TechnologyDalianChina

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