Improving sustainable performance of China's new energy industry through collaborative innovation network resilience

The sustainable development of the new energy industry is crucial and needs support from collaborative innovation networks (CINs). However, CINs may face hindrances or interruptions under multiple risk shocks, impeding their effectiveness in promoting sustainable performance (SP). Enhancing CIN resi...

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Published inRenewable & sustainable energy reviews Vol. 201; p. 114625
Main Authors Liu, Qin, Chen, Ruming, Yu, Qian
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.09.2024
Subjects
Complex network
Innovation ecosystem
Innovation network
Network resilience
New energy industry
Sustainable performance
Temporal exponential random graph model
Sustainable performance
New energy industry
Network resilience
Complex network
Innovation ecosystem
Innovation network
Temporal exponential random graph model
Online AccessGet full text
ISSN1364-0321
1879-0690
DOI10.1016/j.rser.2024.114625

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Abstract The sustainable development of the new energy industry is crucial and needs support from collaborative innovation networks (CINs). However, CINs may face hindrances or interruptions under multiple risk shocks, impeding their effectiveness in promoting sustainable performance (SP). Enhancing CIN resilience is essential for the normal operation of CINs and requires support from the innovation ecosystem. This study aims to improve CIN resilience by optimizing innovation ecological factors, thereby improving the SP of new energy industry. The study selects China's new energy industry as the empirical object. Firstly, the impacts of CIN resilience on SP are explored through regression analysis. Secondly, the impacts of nine driving factors proposed based on innovation ecosystem on CIN resilience were uncovered by the temporal exponential random graph model. Lastly, network simulation was utilized to study how to optimize CIN resilience through network edge addition strategies and identify key regional cooperations for enhancing CIN resilience more effectively. The results indicate that: (1) CIN resilience can improve SP, with adaptive capacity exerting the most promotional effect. (2) Innovation ecological factors dynamically and heterogeneously drive CIN resilience. Innovative market subjects and technical environments exhibit substantial positive impacts on CIN resilience. (3) Promoting innovation cooperations of intermediary bridge regions can optimize CIN resilience. This study offers practical strategies for Chinese local governments and other countries or regions to formulate effective industrial policies and provides valuable insights for new energy enterprises. [Display omitted] •Collaborative innovation network resilience can improve sustainable performance.•Innovation ecological factors positively and dynamically drive network resilience.•Promoting key regional cooperations can effectively optimize network resilience.•Studying network resilience drivers and optimization by complex network methods.
AbstractList The sustainable development of the new energy industry is crucial and needs support from collaborative innovation networks (CINs). However, CINs may face hindrances or interruptions under multiple risk shocks, impeding their effectiveness in promoting sustainable performance (SP). Enhancing CIN resilience is essential for the normal operation of CINs and requires support from the innovation ecosystem. This study aims to improve CIN resilience by optimizing innovation ecological factors, thereby improving the SP of new energy industry. The study selects China's new energy industry as the empirical object. Firstly, the impacts of CIN resilience on SP are explored through regression analysis. Secondly, the impacts of nine driving factors proposed based on innovation ecosystem on CIN resilience were uncovered by the temporal exponential random graph model. Lastly, network simulation was utilized to study how to optimize CIN resilience through network edge addition strategies and identify key regional cooperations for enhancing CIN resilience more effectively. The results indicate that: (1) CIN resilience can improve SP, with adaptive capacity exerting the most promotional effect. (2) Innovation ecological factors dynamically and heterogeneously drive CIN resilience. Innovative market subjects and technical environments exhibit substantial positive impacts on CIN resilience. (3) Promoting innovation cooperations of intermediary bridge regions can optimize CIN resilience. This study offers practical strategies for Chinese local governments and other countries or regions to formulate effective industrial policies and provides valuable insights for new energy enterprises. [Display omitted] •Collaborative innovation network resilience can improve sustainable performance.•Innovation ecological factors positively and dynamically drive network resilience.•Promoting key regional cooperations can effectively optimize network resilience.•Studying network resilience drivers and optimization by complex network methods.
ArticleNumber 114625
Author Liu, Qin
Yu, Qian
Chen, Ruming
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  surname: Liu
  fullname: Liu, Qin
  email: Liu.qin@whut.edu.cn
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  givenname: Ruming
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  givenname: Qian
  surname: Yu
  fullname: Yu, Qian
  email: yuqian@whut.edu.cn
  organization: School of Economics, Wuhan University of Technology, Wuhan, Hubei, 430070, China
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Keywords Sustainable performance
New energy industry
Network resilience
Complex network
Innovation ecosystem
Innovation network
Temporal exponential random graph model
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Snippet The sustainable development of the new energy industry is crucial and needs support from collaborative innovation networks (CINs). However, CINs may face...
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SubjectTerms Complex network
Innovation ecosystem
Innovation network
Network resilience
New energy industry
Sustainable performance
Temporal exponential random graph model
Title Improving sustainable performance of China's new energy industry through collaborative innovation network resilience
URI https://dx.doi.org/10.1016/j.rser.2024.114625
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