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The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer
To clarify the problems existing in the process of knowledge transfer of virtual teams, the team cooperation optimization model is combined with the technological innovation capability under the neural network (NN) model, and it is expected to provide a reference for the knowledge management and tec...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8942250/ https://www.ncbi.nlm.nih.gov/pubmed/35320279 http://dx.doi.org/10.1371/journal.pone.0264367 |
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author | Zhang, Anqi |
author_facet | Zhang, Anqi |
author_sort | Zhang, Anqi |
collection | PubMed |
description | To clarify the problems existing in the process of knowledge transfer of virtual teams, the team cooperation optimization model is combined with the technological innovation capability under the neural network (NN) model, and it is expected to provide a reference for the knowledge management and technological innovation of enterprises. This study first explores the organization, collaboration, and management of virtual teams from the perspective of knowledge transfer. In addition, based on NN, the research and development (R&D) and innovation capabilities of enterprises are studied, and an evaluation index system is constructed. In the stage of empirical analysis, this study selects Enterprise A for research and analyzes the status quo and existing problems of this company. Then, this study proposes a set of schemes conducive to virtual team collaboration and comprehensively uses management theory to evaluate the application effect. The team collaboration model based on knowledge transfer is applied to the operation and management of the enterprise, which significantly improves the collaboration between the various departments of the enterprise and the fluidity of resources. An enterprise R&D capability evaluation system based on a NN model can comprehensively evaluate various index data, thereby prompting its further strategic management and investment. The virtual team collaboration model combined with the R&D technological innovation under the NN model can objectively evaluate the capabilities of the enterprise, thereby improving the management efficiency and benefiting the long-term development of the enterprise. |
format | Online Article Text |
id | pubmed-8942250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-89422502022-03-24 The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer Zhang, Anqi PLoS One Research Article To clarify the problems existing in the process of knowledge transfer of virtual teams, the team cooperation optimization model is combined with the technological innovation capability under the neural network (NN) model, and it is expected to provide a reference for the knowledge management and technological innovation of enterprises. This study first explores the organization, collaboration, and management of virtual teams from the perspective of knowledge transfer. In addition, based on NN, the research and development (R&D) and innovation capabilities of enterprises are studied, and an evaluation index system is constructed. In the stage of empirical analysis, this study selects Enterprise A for research and analyzes the status quo and existing problems of this company. Then, this study proposes a set of schemes conducive to virtual team collaboration and comprehensively uses management theory to evaluate the application effect. The team collaboration model based on knowledge transfer is applied to the operation and management of the enterprise, which significantly improves the collaboration between the various departments of the enterprise and the fluidity of resources. An enterprise R&D capability evaluation system based on a NN model can comprehensively evaluate various index data, thereby prompting its further strategic management and investment. The virtual team collaboration model combined with the R&D technological innovation under the NN model can objectively evaluate the capabilities of the enterprise, thereby improving the management efficiency and benefiting the long-term development of the enterprise. Public Library of Science 2022-03-23 /pmc/articles/PMC8942250/ /pubmed/35320279 http://dx.doi.org/10.1371/journal.pone.0264367 Text en © 2022 Anqi Zhang https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zhang, Anqi The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer |
title | The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer |
title_full | The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer |
title_fullStr | The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer |
title_full_unstemmed | The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer |
title_short | The application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer |
title_sort | application of virtual teams in the improvement of enterprise management capability from the perspective of knowledge transfer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8942250/ https://www.ncbi.nlm.nih.gov/pubmed/35320279 http://dx.doi.org/10.1371/journal.pone.0264367 |
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