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Complex Network Analysis for Knowledge Management and Organizational Intelligence

Author

Listed:
  • Josef Daňa

    (Masaryk University)

  • Francesco Caputo

    (University of Salerno)

  • Jaroslav Ráček

    (Masaryk University)

Abstract

The scope and focus of knowledge management has changed multiple times over the last decades, each shift revealing new challenges to management science. Recent change of perspective drawing from systems thinking is suggesting that knowledge is created through interaction between people. Complex network analysis is a rigorous method that can be used for evaluation of interaction patterns between employees. The literature suggests that specific interaction patterns are related to increased knowledge flow, innovativeness, and performance. Aim of this paper is to provide an overview of various approaches utilizing the complex network analysis in organizations and present suggestions that might support managerial decision-making processes related to knowledge management and organizational intelligence.

Suggested Citation

  • Josef Daňa & Francesco Caputo & Jaroslav Ráček, 2020. "Complex Network Analysis for Knowledge Management and Organizational Intelligence," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(2), pages 405-424, June.
    • Handle: RePEc:spr:jknowl:v:11:y:2020:i:2:d:10.1007_s13132-018-0553-x
    DOI: 10.1007/s13132-018-0553-x
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    References listed on IDEAS

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    1. Cowan, Robin & Jonard, Nicolas, 2004. "Network structure and the diffusion of knowledge," Journal of Economic Dynamics and Control, Elsevier, vol. 28(8), pages 1557-1575, June.
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    3. Stephen P. Borgatti & Rob Cross, 2003. "A Relational View of Information Seeking and Learning in Social Networks," Management Science, INFORMS, vol. 49(4), pages 432-445, April.
    4. Tröster, Christian & Mehra, Ajay & van Knippenberg, Daan, 2014. "Structuring for team success: The interactive effects of network structure and cultural diversity on team potency and performance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 124(2), pages 245-255.
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    Cited by:

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    2. Fawwaz Awamleh & Ahmet Ertugan, 2021. "The Relationship Between Information Technology Capabilities, Organizational Intelligence, and Competitive Advantage," SAGE Open, , vol. 11(2), pages 21582440211, May.
    3. Singh, Sanjay Kumar & Mazzucchelli, Alice & Vessal, Saeedeh Rezaee & Solidoro, Adriano, 2021. "Knowledge-based HRM practices and innovation performance: Role of social capital and knowledge sharing," Journal of International Management, Elsevier, vol. 27(1).
    4. Scuotto, Veronica & Magni, Domitilla & Palladino, Rosa & Nicotra, Melita, 2022. "Triggering disruptive technology absorptive capacity by CIOs. Explorative research on a micro-foundation lens," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    5. Caputo, Francesco & Magni, Domitilla & Papa, Armando & Corsi, Christian, 2021. "Knowledge hiding in socioeconomic settings: Matching organizational and environmental antecedents," Journal of Business Research, Elsevier, vol. 135(C), pages 19-27.
    6. Tachia Chin & Francesco Caputo & Yi Shi & Mario Calabrese & Chiraz Aouina‐Mejri & Armando Papa, 2022. "Depicting the role of cross‐cultural legitimacy for responsible innovation in Asian‐Pacific business models: A dialectical systems view of Yin‐Yang harmony," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(6), pages 2083-2093, November.
    7. Caputo, Francesco & Cillo, Valentina & Fiano, Fabio & Pironti, Marco & Romano, Marco, 2023. "Building T-shaped professionals for mastering digital transformation," Journal of Business Research, Elsevier, vol. 154(C).
    8. Oleg Sergeevich Sukharev, 2023. "Intellectual Firm: Key Features and Development Models," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(2), pages 1091-1119, June.

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