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Communication Policies in Knowledge Networks

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  • Ioannidis, Evangelos
  • Varsakelis, Nikos
  • Antoniou, Ioannis

Abstract

Faster knowledge attainment within organizations leads to improved innovation, and therefore competitive advantage. Interventions on the organizational network may be risky or costly or time-demanding. We investigate several communication policies in knowledge networks, which reduce the knowledge attainment time without interventions. We examine the resulting knowledge dynamics for real organizational networks, as well as for artificial networks. More specifically, we investigate the dependence of knowledge dynamics on: (1) the Selection Rule of agents for knowledge acquisition, and (2) the Order of implementation of “Selection” and “Filtering”. Significant decrease of the knowledge attainment time (up to −74%) can be achieved by: (1) selecting agents of both high knowledge level and high knowledge transfer efficiency, and (2) implementing “Selection” after “Filtering” in contrast to the converse, implicitly assumed, conventional prioritization. The Non-Commutativity of “Selection” and “Filtering”, reveals a Non-Boolean Logic of the Network Operations. The results demonstrate that significant improvement of knowledge dynamics can be achieved by implementing “fruitful” communication policies, by raising the awareness of agents, without any intervention on the network structure.

Suggested Citation

  • Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2018. "Communication Policies in Knowledge Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 360-374.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:360-374
    DOI: 10.1016/j.physa.2017.09.078
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    Citations

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    Cited by:

    1. Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2021. "Intelligent Agents in Co-Evolving Knowledge Networks," Mathematics, MDPI, vol. 9(1), pages 1-17, January.
    2. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2018. "Experts in Knowledge Networks: Central Positioning and Intelligent Selections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 890-905.
    3. Liming Zhao & Haihong Zhang & Wenqing Wu, 2019. "Cooperative knowledge creation in an uncertain network environment based on a dynamic knowledge supernetwork," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 657-685, May.
    4. Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2020. "Promoters versus Adversaries of Change: Agent-Based Modeling of Organizational Conflict in Co-Evolving Networks," Mathematics, MDPI, vol. 8(12), pages 1-25, December.
    5. Dimitris Tsintsaris & Milan Tsompanoglou & Evangelos Ioannidis, 2024. "Dynamics of Social Influence and Knowledge in Networks: Sociophysics Models and Applications in Social Trading, Behavioral Finance and Business," Mathematics, MDPI, vol. 12(8), pages 1-27, April.
    6. Mehdi Mazloumi & Edwin van Hassel, 2021. "Improvement of Container Terminal Productivity with Knowledge about Future Transport Modes: A Theoretical Agent-Based Modelling Approach," Sustainability, MDPI, vol. 13(17), pages 1-17, August.

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