Exploring the Multidimensional Drivers of Sustainable Green Innovation in Chinese Manufacturing Listed Companies: An XGBoost-SHAP Machine Learning Model Approach

ith the growing emphasis on global sustainable development goals, green transformation has become a key focus in global economic development. In this context, green technological innovation, particularly sustainable green innovation in Chinese manufacturing listed companies (SGIM), is recognized as a critical pathway for driving industrial upgrading and achieving carbon neutrality. This study explores the multidimensional drivers of SGIM in Chinese manufacturing listed companies, employing an XGBoost (Extreme Gradient Boosting)machine learning model combined with SHAP (Shapley Additive Explanations) for interpretability analysis. As China’s manufacturing sector transitions towards a greener, low-carbon, and circular economy, understanding the key factors that drive SGIM is essential for both corporate strategy and national environmental objectives. The study identifies key drivers across five dimensions: company-level resources, management team characteristics, financial performance, R&D investment, and external environmental factors. Using advanced machine learning techniques, the study reveals significant nonlinear relationships between SGIM and factors such as R&D personnel (Nrdp), company size (Size), and capital intensity (Cap). The findings indicate that human capital, organizational capabilities, and financial resources play central roles in enhancing SGIM, with diminishing returns observed beyond certain thresholds. The SHAP analysis further emphasizes the complex interplay between these variables, providing insights into the underlying mechanisms of SGIM. This study contributes to the literature by providing a multidimensional framework for assessing SGIM and offers practical implications for policy formulation, corporate strategy, and the optimization of green innovation practices. The research highlights the importance of balancing resource allocation and dynamically integrating knowledge, organizational, and capital elements to foster sustainable innovation in manufacturing enterprises.