首页|Improving sustainable development performance of new energy industry through green innovation network evolution empowered by digitalization: Based on temporal exponential random graph model

Improving sustainable development performance of new energy industry through green innovation network evolution empowered by digitalization: Based on temporal exponential random graph model

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  • NETL
  • NSTL
  • Elsevier
© 2024 Elsevier LtdThe sustainable development of the new energy industry is crucial for addressing climate change and facing various challenges, which requires the support of green innovation network effected by digitalization. Nonetheless, the influence of each dimension of digitalization in driving network development to enhance sustainable development performance has yet to be adequately explored. Therefore, this study aims to explore how multi-dimensional digitization dynamically empowers green innovation networks and identifies key digitalization elements, thus effectively improving sustainable development performance. Green innovation networks of new energy enterprises in China are constructed using green patents. First, the impact of network structure on sustainable development performance is analyzed from the perspective of structural embeddedness with multiple regression analysis. Further, the dynamic evolutionary characteristics of network structure at macroscopic and mesoscopic levels are investigated through social network analysis and network motif. Then, a multi-dimensional digitalization framework is established, and the temporal exponential random graph model is employed to uncover the evolutionary mechanism of green innovation network, considering five types of digitalization elements. The findings indicate the following: (1) Green innovation network structure affects sustainable development performance and enterprises with high closeness centrality and betweenness centrality exhibit superior sustainable development performance. (2) The evolutionary characteristics of green innovation networks reveal the networks lacks resilience, necessitating the optimization of network structure through promoting formation of innovation collaboration relationships. (3) The impacts of multi-dimensional digitalization elements on green innovation network are heterogeneous and dynamic. Digital technology, digital investment, digital strategy, and digital policy empower the positive development of networks and facilitate network formation, while digital economy exerts a negative effect. Similar digital strategies among enterprises facilitate the formation of green innovation networks. This study offers valuable insights for local governments in formulating industrial policies and for new energy enterprises in optimizing digitalization elements and improving sustainable development performance.

DigitalizationInnovation networkNew energy industrySustainable developmentTemporal exponential random graph model

Liu Q.、Chen R.、Yue W.、Gao Q.

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School of Entrepreneurship Wuhan University of Technology||School of Management Wuhan University of Technology

School of Entrepreneurship Wuhan University of Technology

School of Management Wuhan University of Technology

2025

10.1016/j.enconman.2024.119253

Energy conversion & management

Energy conversion & management

ISSN：0196-8904
年,卷(期)：2025.324(Jan.)
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