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Demonstrates pathways that improve green innovation quality in the automotive industry, suggesting significant implications for sustainability.
The automotive manufacturing industry, a key pillar sector, is increasingly guided toward enhancing green innovation quality through low carbon economy principles under ESG frameworks. This study employs a mixed-method approach combining Necessary Condition Analysis (NCA) and fuzzy set Qualitative Comparative Analysis (fsQCA), utilizing a sample of 301 Chinese automotive manufacturing firms to establish an environmental, social, and governance (ESG) framework. It examines how environmental regulations, social dynamics, and internal governance conditions jointly influence green innovation quality. Results demonstrate that the Environmental Management System serves as a central condition for improving green innovation quality. Green innovation quality manifests through multiple pathways converging to identical outcomes, with three distinct mechanisms driving high performance: environmental regulation-driven pathways, anti-corruption and centralized decision-making pathways, and management constraint and governance efficiency pathways. These findings provide robust theoretical foundations for advancing sustainable green innovation in the automotive industry.
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Wang et al. (2026) studied this question.
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