Linking Psychological Safety Climate to Dual Innovation Through AI-Enabled Dynamic Capabilities
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Objective: This study develops and empirically validates an integrated model that explains how the psychological safety climate influences dual innovation through AI-enabled dynamic capabilities in Chinese design organizations. Methods: A cross-sectional survey was conducted among 281 designers from industry design firms and departments. Data analysis employed partial least squares-structural equation modeling, including mediation bootstrapping analysis, importance-performance map analysis, necessary condition analysis, and quadratic effect analysis. Findings: All hypotheses received strong empirical support. The psychological safety climate has a significant influence on AI-enabled dynamic capabilities, with a path coefficient of 0.452 at p <0.001, and on dual innovation, with a coefficient of 0.383 at p < 0.001. AI-enabled dynamic capabilities have a positive impact on dual innovation, with a coefficient of 0.384 at p < 0.001, and significant mediation effects, indicating an indirect effect of 0.174 at p < 0.001. The model explains 42.7% of the variance in dual innovation. Importance-performance analysis reveals a psychological safety climate as highly important but moderately performing, indicating strategic opportunities for improvement for organizations. Necessary condition analysis confirms both constructs as essential requirements for innovation outcomes. The findings demonstrate that psychological safety climate, as a higher-order cultural resource, enables lower-order AI-enabled dynamic capabilities, supporting socio-technical systems structure for dual innovation. Organizations should prioritize investments in psychological safety while maintaining their AI capabilities. Novelty: This research introduces AI-enabled dynamic capabilities as a second-order formative construct and establishes the meta-capability role of psychological safety climate in AI-enabled dynamic capabilities and dual innovation, thereby extending the resource-based view and dynamic capabilities theories through micro-foundational perspectives.
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