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Research paper | Open Access

Research on collaborative governance mechanism of academic ecological environment under the background of crowd intellectual thinking

Yi He, Linlin Ma( ), Yanan Wang
Central University of Finance and Economics, Beijing, China
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Abstract

Purpose

This paper aims to use intellectual thinking to solve the problem of how to carry out collaborative governance of the academic ecological environment.

Design/methodology/approach

This paper selected academic ecosystem, academic ecological environment and academic ecological governance as three keywords to collect literature data. The hot issues on the academic ecological environment and its governance system in China are analyzed, with visualization software such as Citespace, China National Knowledge Infrastructure (CNKI) and other literature metrology tools.

Findings

The previous research literature cannot fully explain the governance mechanism of the academic ecological environment. In this paper, the authors use the way of group cooperation thinking in the crowd science category, to build a collaborative governance framework of the academic ecological environment from the national level, the institutional level and the individual level, taking full advantage of the in-depth analysis on crowd intellectual thinking.

Originality/value

The authors use the way of group cooperation thinking in the crowd science category, to build a collaborative governance framework of academic.

Keywords

Collaborative governanceAcademic ecological environmentCrowd intellectual thinking

References

 

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International Journal of Crowd Science
Volume 5 Issue 3,
November 2021
Pages 271-280
DOI: 10.1108/IJCS-07-2021-0020
Cite this article:
He Y, Ma L, Wang Y. Research on collaborative governance mechanism of academic ecological environment under the background of crowd intellectual thinking. International Journal of Crowd Science, 2021, 5(3): 271-280. https://doi.org/10.1108/IJCS-07-2021-0020

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Received: 30 July 2021
Revised: 16 August 2021
Accepted: 26 August 2021
Published: 13 September 2021
© The author(s)

Yi He, Linlin Ma and Yanan Wang. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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