Digital innovation network embedding and firm innovation resilience from the perspective of knowledge-based dynamic capability
Year: 2026
Type: article
Abstract: The volatile, uncertain, complex, and ambiguous (VUCA) era has brought unprecedented impacts on the innovation development of enterprises. Amidst the transformative opportunities presented by digital technological advancements, whether firms can enhance their innovation resilience by embedding themselves within emerging digital innovation network has raised much attention and discussion. Therefore, this study constructs the theoretical analysis framework of “network embedding - dynamic-based knowledge capability - innovation resilience” to explore the relationship between digital innovation network and firm innovation resilience, and to analyze how the knowledge-based dynamic capability plays the role of pathway. Utilizing firms’ cooperative digital invention patents application data to construct digital innovation network and drawing on the panel data of A-listed firms over the period of 2012–2023, this study empirically investigates how embedding in digital innovation network affects firm innovation resilience. The key findings are as follows: (1) Both digital innovation network structural and relational embedding have significant positive effect on firm innovation resilience; (2) Knowledge-based dynamic capability which comprises of knowledge acquisition, integration, and reconfiguration plays a mechanism role in the relationship between digital innovation network embedding and innovation resilience; (3) Embedding in digital innovation network has a more pronounced effect in firms which executives with digital background, which are classified into non-high-tech industries, and which are insensitive to uncertainty. This study provides empirical evidence and practical insights for fostering innovation resilience in the context of digitization and openness, thereby enhancing the security and controllability of Chinese industrial and supply chains.
Source: Discover Sustainability
Institutions: Guangdong University of Technology, Xiangtan University
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,390
Awards: G1976921702, G2494512467
OpenAlex ID: W7212182658
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