ArticleiScience2026
Multilayer innovation network resilience: A framework for digital economy vulnerability assessment.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
Innovation networks drive technological progress, yet their multilayer structures remain poorly understood in digital economy vulnerability contexts. This study develops a comprehensive framework for assessing multilayer innovation network resilience, analyzing interdependencies and disruption scenarios using China's digital economy as a representative empirical context. We construct coupled multilayer networks implementing four integrated attack strategies to identify cascading vulnerability mechanisms. Results reveal asymmetric patterns: collaboration networks show significant fragility to targeted attacks, while knowledge networks demonstrate higher resilience, especially during mature stages. Cascade failure analysis establishes that knowledge network disruptions propagate severe ecosystem-wide effects, whereas collaboration network perturbations generate limited cross-layer impacts. This asymmetry advances multilayer innovation network theory and provides practical insights for vulnerability assessment. The framework indicates that protecting critical technological knowledge should prioritize over maintaining collaborative arrangements when resources are limited, as knowledge networks constitute the essential integrative mechanism within innovation systems.
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