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Research on evaluation of knowledge interaction indicators in multi-team systems based on management entropy

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  • Xie, Hui
  • Li, Hao
  • Zhang, Kexin

Abstract

Efficient knowledge interaction among teams can enhance the collaborative performance of Multi-team Systems (MTSs). Identifying and addressing issues within MTS knowledge interaction is a current topic in knowledge-driven MTS collaboration. However, there is a lack of scientific and measurable evaluation indicators and methods for effectively evaluating MTS knowledge interactions to aid decision-making. This study, integrating a network perspective with complex systems thinking and the theoretical principles of management entropy, constructs a systematic evaluation system for MTS knowledge and a corresponding methodological framework. Validated and analyzed through two case studies in diverse contexts, this system and method enable managers to pinpoint crucial indicators affecting the effectiveness of MTS knowledge at various stages, especially critical junctures that may arise during the evolving development of the MTS. This provides a basis for decision-making to enable timely managerial interventions at crucial moments.

Suggested Citation

  • Xie, Hui & Li, Hao & Zhang, Kexin, 2025. "Research on evaluation of knowledge interaction indicators in multi-team systems based on management entropy," Technovation, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:techno:v:139:y:2025:i:c:s0166497224001755
    DOI: 10.1016/j.technovation.2024.103125
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    References listed on IDEAS

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