• DocumentCode
    3038789
  • Title

    Multi-agent Simulation Research on Knowledge Management Strategies of R&D Enterprises

  • Author

    Kou Xiao-dong ; Wang Zhi-yu ; Yang Lin

  • Author_Institution
    Sch. of Humanities, Econ. & Law, Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    1109
  • Lastpage
    1114
  • Abstract
    In the background of transformation and upgrading of China´s economy, this article builds a kind of model for R&D Enterprises based on multi-agent modeling technique, and by simulating the effects of different project group sizes on achievement of enterprise mission and capital cost control, the knowledge management strategies for the model enterprise are suggested. The main findings include that a R&D enterprise should pay more attention to its capital position at its early stage, and viable strategies include enlarging the size of each project group to a reasonable extent, facilitating project progress while accumulating tacit knowledge; when the enterprise enters into its development stage, it should concentrate on knowledge sharing activities among employees, and viable strategies include building a culture where knowledge sharing is encouraged, and reducing the size of project groups.
  • Keywords
    costing; knowledge management; multi-agent systems; research and development; Chinese economy; R&D enterprises; capital cost control; enterprise mission; knowledge management strategies; knowledge sharing; multiagent modeling technique; multiagent simulation research; project group sizes; project progress; tacit knowledge; Analytical models; Educational institutions; Gaussian distribution; Knowledge management; Load modeling; Remuneration; Technological innovation; NetLogo simulation; R&D Enterprises; knowledge management strategy; multi-agent modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.193
  • Filename
    6721946