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Driving the Sustainability Transition in Energy Storage: System Analyses of Innovation Networks in China’s Electric Vehicle Battery Industry

Dengjuan Liu, Li Li () and Wei Liu ()
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Dengjuan Liu: College of Management Science, Chengdu University of Technology, Chengdu 610059, China
Li Li: College of Management Science, Chengdu University of Technology, Chengdu 610059, China
Wei Liu: School of Environment, Tsinghua University, Beijing 100084, China

Sustainability, 2025, vol. 17, issue 11, 1-24

Abstract: Amid the accelerating global transition toward a low-carbon economy, collaborative innovation within the new energy vehicle industry has emerged as a critical mechanism for advancing green technology diffusion and fostering industrial ecosystem sustainability. This study explores the evolutionary features of the cooperative network and the ways in which network embedding influences innovation performance by analyzing 2808 patents pertaining to battery technologies for new energy vehicles (NEVs) in China, which adopted the network embedding theory. The results show that (l) the innovation performance within China’s NEV battery technology innovation cooperation network exhibits significant variation, the industry is undergoing accelerated stratification, and a trend towards head concentration is evident; (2) network size amplifies the beneficial influence of structural holes and centrality on innovation performance; and (3) the mediating role of external knowledge search between network embeddedness and innovation performance is negatively moderated by relationship intensity. By extending the social network theory to the field of new energy vehicle batteries, this study reveals the special law of network embedding in the technology-intensive industry, elucidates the mediating mechanism of external knowledge search, and innovatively proposes the “innovation paradox” of relationship strength, confirming the innovation advantage of weak relationship cross-border reorganization in this field.

Keywords: cooperative networks; network embedding; evolutionary characteristics; external knowledge search; innovation performance; new energy vehicle battery technology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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