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

Hui Xie, Hao Li and Kexin Zhang

Technovation, 2025, vol. 139, issue C

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.

Keywords: Multi-team systems; Management entropy; Knowledge interaction; Evaluation indicators (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166497224001755
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:139:y:2025:i:c:s0166497224001755

DOI: 10.1016/j.technovation.2024.103125

Access Statistics for this article

Technovation is currently edited by Jonathan Linton

More articles in Technovation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().