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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This work is partly supported by the National Natural Science Foundation of China under Grant No. 71471028.
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Li, Y., Dang, Y. (2016). Team Knowledge Formation and Evolution Based on Computational Experiment. In: Chen, J., Nakamori, Y., Yue, W., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2016. Communications in Computer and Information Science, vol 660. Springer, Singapore. https://doi.org/10.1007/978-981-10-2857-1_1
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DOI: https://doi.org/10.1007/978-981-10-2857-1_1
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