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Longfei Li

Document Type

Research-Article

Author

Longfei Li, Junnan Zhang, Chao Liu, Yuyue Guan, Wan Kang

Journal Name

Journal of Innovation and Knowledge

Keywords

Dynamic resilience, Exponential random graph model, Innovation network, New energy vehicle industry, Static resilience

Abstract

It is essential to comprehend the feature and improvement path that supports the resilience of innovation networks under multiple crisis shocks. Studies have primarily examined the impact of network features on sustainable innovation outcomes yet overlooked the inter-organisational resilience feature of these networks. This study presents a measurement system to analyse resilience features in China's new energy vehicle industry (NEVI) cooperative innovation network. To evaluate the evolution of network structures and functionality, this system integrates the static–dynamic framework, capturing static and dynamic impacts. The exponential random graph model is used to investigate the improvement path of innovation network resilience in the NEVI. Findings reveal that, from the perspective of static network resilience, the transportability of the innovation network decreases, while the level of aggregation remains high. From the perspective of dynamic network resilience, nodes with high transitivity and diffusion abilities significantly enhance the efficiency and scale stability of the NEVI's innovation network. Improved network resilience is influenced by self-organisation, individual attribute, and exogenous network effects. This study enriches the literature on maintaining stability and sustainable development of innovation networks. It illustrates how to measure and improve the resilience of innovation networks to aid recovery from crises. © 2025 Elsevier B.V., All rights reserved.

https://doi.org/10.1016/j.jik.2025.100825

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