创新科技2026，Vol.26Issue(3)：44-62,19.DOI:10.19345/j.cxkj.1671-0037.2026.3.4
制造企业绿色创新韧性提升的多元驱动路径研究:基于PLS—ANN—fsQCA的混合方法分析
Multiple Pathways to Enhancing Green Innovation Resilience in Manufacturing Enterprises:A PLS—ANN—fsQCA Hybrid Analysis
摘要
Abstract
Against the dual backdrop of China's"dual-carbon"goals and accelerating digi-tal transformation,green innovation resilience has emerged as a critical organizational capability enabling manufacturing enterprises to navigate environmental uncertainties and policy volatility.While existing research has predominantly examined green innovation through linear analytical lenses,this study breaks new ground by systematically investigating the configurational mecha-nisms that underpin green innovation resilience development.Leveraging the Technology-Organization-Environment(TOE)framework as our theoretical foundation,we analyze survey data from 319 Chinese manufacturing enterprises using an innovative multi-method approach that integrates partial least squares structural equation modeling(PLS-SEM),artificial neural networks(ANN),and fuzzy-set qualitative comparative analysis(fsQCA).This methodological triangulation allows us to comprehensively examine how digital technology accumulation and variation affordances,top management's environmental cognition,big data analytics capabilities,and both command-and-control and market-based environmental regulations interactively con-tribute to green innovation resilience.Our findings yield three key insights:①While all six ante-cedent conditions demonstrate statistically significant positive effects on green innovation resil-ience,their relative importance and operational mechanisms show substantial variation.②ANN analysis reveals significant nonlinearity in green innovation resilience,particularly highlighting the context-dependent roles of market-based environmental regulations and big data analytics capabilities,whose importance rankings fluctuate across different organizational and environ-mental conditions.③Through fsQCA,we identify four distinct yet equally effective configura-tions that lead to high green innovation resilience:the technology-cognition synergistic pathway,the cognition-data-regulation tripartite driven model,the digital accumulation with dual-regulation compensation approach,and the cognition-centered regulation-driven pattern.These findings robustly confirm the presence of both conjunctural causation and causal asymmetry in green innovation resilience.This study makes significant theoretical contributions by advancing a configurational perspective on green innovation resilience that complements and extends exist-ing linear paradigms.Practically,our findings provide manufacturing enterprises with actionable pathways to strategically align their resource endowments and build resilient green innovation ca-pabilities amidst complex,uncertain environments,while offering policymakers nuanced insights for designing more effective environmental governance frameworks.关键词
绿色创新韧性/TOE框架/组态分析/PLS-SEM/ANN/制造企业/数字技术可供性/数字化转型Key words
green innovation resilience/TOE framework/configuration analysis/PLS-SEM/ANN/manufacturing enterprises/affordance of digital technology/digital transformation分类
管理科学引用本文复制引用
郭敏,翟翯,王京北,刘慧..制造企业绿色创新韧性提升的多元驱动路径研究:基于PLS—ANN—fsQCA的混合方法分析[J].创新科技,2026,26(3):44-62,19.基金项目
国家自然科学基金青年项目"风险传播对竞合研发网络的脆弱性影响及控制方法研究"(72101274) （72101274）
陕西省社会科学基金项目"数字技术对陕西制造企业绿色创新韧性的影响机理研究"(2024R068) （2024R068）
陕西省教育厅重点科学研究计划项目"研发联盟网络中企业间竞合关系动态机制及其对网络稳定性的影响研究"(24JT020). （24JT020）
