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How to facilitate knowledge diffusion in complex networks: The roles of network structure, knowledge role distribution and selection rule

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  • Qiao, Tong
  • Shan, Wei
  • Zhang, Mingli
  • Liu, Chen

Abstract

The diffusion of knowledge within organizations provides opportunities for interpersonal co-operation, improves creative ability and therefore leads to competitive advantage. Focus of prior literature on knowledge diffusion has been on identifying factors that influence individuals' behavioral intentions to seek and share knowledge. However, knowledge diffusion as an enigmatic, emergent and organizational-level process is more than the simple aggregation of individual attributes and needs to be further investigated. Accordingly, this study focuses on three distinct system-level factors, i.e., architectures of connections among individuals, distributions of knowledge roles and designs of selection mechanisms and analyses their effects on knowledge diffusion. To be more specific, we examine three distinct knowledge roles: seekers, contributors and brokers. We also distinguish between three types of selection mechanisms: objective selection mechanisms, feedback-based selection mechanisms and random selection mechanisms. By conducting agent-based simulations on four representative networks, i.e., regular networks, random networks, small-world networks and scale-free networks, our results show that the optimal knowledge diffusion performance can be achieved on scale-free networks where all agents implement objective mechanisms and show characteristics of brokers. Moreover, our results (a) highlight the significance of brokers, (b) illustrate the superiority of objective selection rules and (c) demonstrate that scale-free networks provide an optimal framework for knowledge diffusion. Furthermore, we also find the interdependent relevance of these three factors to knowledge diffusion and propose a qualitative explanation of these findings.

Suggested Citation

  • Qiao, Tong & Shan, Wei & Zhang, Mingli & Liu, Chen, 2019. "How to facilitate knowledge diffusion in complex networks: The roles of network structure, knowledge role distribution and selection rule," International Journal of Information Management, Elsevier, vol. 47(C), pages 152-167.
  • Handle: RePEc:eee:ininma:v:47:y:2019:i:c:p:152-167
    DOI: 10.1016/j.ijinfomgt.2019.01.016
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    Citations

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    Cited by:

    1. Lei Xu & Ronggui Ding & Lei Wang, 2022. "How to facilitate knowledge diffusion in collaborative innovation projects by adjusting network density and project roles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1353-1379, March.
    2. Mai-Lun Chiu & Tsung-Sheng Cheng & Chun-Nan Lin, 2024. "Driving Open Innovation Capability Through New Knowledge Diffusion of Integrating Intrinsic and Extrinsic Motivations in Organizations: Moderator of Individual Absorptive Capacity," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3685-3717, March.
    3. Shixun Wang & Lihong Yang, 2022. "The Network Structure of Innovation Networks," Networks and Spatial Economics, Springer, vol. 22(1), pages 65-96, March.
    4. Mei, Jun & Wang, Sixin & Xia, Dan & Hu, Junhao, 2022. "Global stability and optimal control analysis of a knowledge transmission model in multilayer networks," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    5. Zhu, Hongmiao & Jin, Zhen, 2023. "A dynamics model of knowledge dissemination in a WeChat Group from perspective of duplex networks," Applied Mathematics and Computation, Elsevier, vol. 454(C).

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