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How Does the Dual Credit Policy Affect the Green Innovation Performance of New Energy Vehicle Enterprises? ——A Dynamic Configuration Analysis Based on the TOE Framework

Hua Wu  *

Submitted:

15 January 2026

Posted:

20 January 2026

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Abstract
The development of new energy technologies is  crucial for the future competitiveness of the automotive industry. Green innovation is a key driver of industrial transformation and advancement. Companies in the new energy vehicle (NEV) sector play a critical role in the automotive supply chain and demonstrate their green innovation capabilities across the industry. The dual-credit policy, a major governmental regulatory incentive, has a significant impact on the innovation performance of NEVs. Therefore, it is important to examine its influence on green innovation outcomes. This study is grounded in institutional theory and the resource-based view, and informed by the TOE (Technology-Organization-Environment) analytical framework. It aims to develop a theoretical model to investigate the interplay among technological, organizational, and environmental factors in fostering green innovation. Using panel data from 21 NEV companies spanning the period 2014–2024, the research employs the dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA) method to identify causal configurations associated with high green innovation performance. The results show that no single factor is necessary for achieving superior outcomes. Configuration analysis reveals 3 dominant pathways: the “Technology-driven+Environment-pulled” pathway, the “Technology-driven+Organizational collaboration” pathway and the ”Technology-organization-environment tripartite linkage“ pathway. This study advances theoretical understanding by moving beyond unidimensional analyses and offering a holistic perspective on the multiple equifinal paths to high green innovation performance. It also provides practical insights for NEV firms to strategically align their technological, organizational, and environmental resources to enhance green innovation performance.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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