• DocumentCode
    1862141
  • Title

    Research on Knowledge Sharing Behavior in Hub-and-spoke Industrial Cluster Based on Evolutionary Game Theory

  • Author

    Lan, Wang

  • Author_Institution
    Sch. of Econ. & Trade, Zhengzhou Inst. of Aeronaut. Ind. Manage., Zhengzhou, China
  • fYear
    2010
  • fDate
    9-10 Jan. 2010
  • Firstpage
    420
  • Lastpage
    423
  • Abstract
    Hub-and-spoke industrial cluster refers to the collaborative enterprises network consisted of leader firms and small and medium enterprises based on specialization division. Owing to strong ties and vertical division, hub-and-spoke clusters have advantage on cooperative innovation, knowledge creation and knowledge sharing. Our aim is to propose an analytical framework on the knowledge sharing behavior in hub-and-spoke industrial clusters based on evolutionary game theory. Firstly, this paper establishes an evolutionary game model of knowledge sharing behavior of clustering firms. Secondly, it analyzes how the evolution and the evolutionary stable strategy (ESS) are influenced by the characteristics and the network structure of hub-and-spoke industrial clusters. Finally, this paper focuses on factors affecting the choice of knowledge sharing strategy in hub-and-spoke industrial clusters, such as: absorptive capabilities, knowledge gaps, organizational distance, uncertainly, trust and so on.
  • Keywords
    game theory; groupware; innovation management; knowledge based systems; collaborative enterprises network; cooperative innovation; evolutionary game theory; evolutionary stable strategy; hub-and-spoke industrial cluster; knowledge creation; knowledge sharing; Aerospace industry; Conference management; Data mining; Electronic switching systems; Evolution (biology); Game theory; Industrial economics; Mining industry; Technological innovation; Toy industry; evolutionary game; hub-and-spoke network; industrial cluster; knowledge sharing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
  • Conference_Location
    Phuket
  • Print_ISBN
    978-1-4244-5397-9
  • Electronic_ISBN
    978-1-4244-5398-6
  • Type

    conf

  • DOI
    10.1109/WKDD.2010.57
  • Filename
    5432561