The Core Enterprise Network Competence, Network Characteristics and the Innovation Network Governance Performance – From Chinese Microcosmic Evidence
Tao Guo 1 2 * , Jing Dong 1, Xuejiao Ren 1, Yao Huang 1
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1 School of Economics and Management, Harbin Engineering University, Harbin Heilongjiang 150001, CHINA2 Enterprise Institute for Innovation, Harbin Engineering University, Harbin Heilongjiang 150001, CHINA* Corresponding Author

This article belongs to the special issue "Problems of Application Analysis in Knowledge Management and Science-Mathematics-Education".

Abstract

To investigate the impact of the core enterprise network competence on innovation network governance performance, this paper introduces network characteristics as an intermediary variable and constructs a conceptual model according to the core enterprise network competence, the network characteristics and the governance performance of the innovation network. This paper also conducts empirical research using 543 survey data. The results show that network vision, network development, network relationship management and network combination management competences as well as network characteristics all have a positive impact on governance performance. Network characteristics have a partial mediating effect on the relationship among network development, network relationship management, and network combination management competences and governance performance; however, network characteristics have no significant mediating effect on the relationship between network vision competence and governance performance. This research will help Chinese enterprises better cultivate network competence and can provide a reference for the improvement of innovation network governance performance.

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 13, Issue 12, December 2017, 7823-7833

https://doi.org/10.12973/ejmste/77924

Publication date: 21 Nov 2017

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Article Downloads: 990

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