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Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks
In the era of digital economy, the impact of innovation resources on high-quality economic growth has become increasingly prominent. There are many researches on the influencing factors of innovation performance. The purpose of this study is to explore the factors that affect the innovation performa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552817/ https://www.ncbi.nlm.nih.gov/pubmed/36237674 http://dx.doi.org/10.3389/fpsyg.2022.1012228 |
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author | Zhang, Liping Xiong, Kaiqi Gao, Xinzhi Yang, Yi |
author_facet | Zhang, Liping Xiong, Kaiqi Gao, Xinzhi Yang, Yi |
author_sort | Zhang, Liping |
collection | PubMed |
description | In the era of digital economy, the impact of innovation resources on high-quality economic growth has become increasingly prominent. There are many researches on the influencing factors of innovation performance. The purpose of this study is to explore the factors that affect the innovation performance of high-end manufacturing clusters in China based on the dual perspectives of digital economy and innovation network. A total of 194 valid questionnaires were collected. And structural equation modeling has been used to test the proposed research models and hypotheses. The results indicated that, the higher the centrality of the innovation network, the more the cluster enterprises can play the centrality advantage, which has a significant positive impact on the innovation performance of the cluster. Similarly, both the strength and density of innovation networks also impacted on cluster innovation performance, but to a lesser extent. We also found that the digital empowerment derived from the digital economy can get rid of the limitations caused by spatial distance and lead to the improvement of resource utilization, which plays a positive moderating role between innovation network and innovation capacity. Implications for digital economy and innovation networks to improve the quality of innovation performance are provided. |
format | Online Article Text |
id | pubmed-9552817 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95528172022-10-12 Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks Zhang, Liping Xiong, Kaiqi Gao, Xinzhi Yang, Yi Front Psychol Psychology In the era of digital economy, the impact of innovation resources on high-quality economic growth has become increasingly prominent. There are many researches on the influencing factors of innovation performance. The purpose of this study is to explore the factors that affect the innovation performance of high-end manufacturing clusters in China based on the dual perspectives of digital economy and innovation network. A total of 194 valid questionnaires were collected. And structural equation modeling has been used to test the proposed research models and hypotheses. The results indicated that, the higher the centrality of the innovation network, the more the cluster enterprises can play the centrality advantage, which has a significant positive impact on the innovation performance of the cluster. Similarly, both the strength and density of innovation networks also impacted on cluster innovation performance, but to a lesser extent. We also found that the digital empowerment derived from the digital economy can get rid of the limitations caused by spatial distance and lead to the improvement of resource utilization, which plays a positive moderating role between innovation network and innovation capacity. Implications for digital economy and innovation networks to improve the quality of innovation performance are provided. Frontiers Media S.A. 2022-09-27 /pmc/articles/PMC9552817/ /pubmed/36237674 http://dx.doi.org/10.3389/fpsyg.2022.1012228 Text en Copyright © 2022 Zhang, Xiong, Gao and Yang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Zhang, Liping Xiong, Kaiqi Gao, Xinzhi Yang, Yi Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks |
title | Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks |
title_full | Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks |
title_fullStr | Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks |
title_full_unstemmed | Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks |
title_short | Factors influencing innovation performance of China’s high-end manufacturing clusters: Dual-perspective from the digital economy and the innovation networks |
title_sort | factors influencing innovation performance of china’s high-end manufacturing clusters: dual-perspective from the digital economy and the innovation networks |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552817/ https://www.ncbi.nlm.nih.gov/pubmed/36237674 http://dx.doi.org/10.3389/fpsyg.2022.1012228 |
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