Achieving sustainable development and carbon neutrality requires continuous technological upgrading in the new energy sector. Improvement of innovation quality in new energy firms therefore plays a significant role in sustainability transitions. However, whether and how the business environment supports the innovation quality in the new energy sector remains unclear. Using machine learning, our study assesses the predictive ability of the business environment for innovation quality in new energy firms, distinguishes the importance of different elements, and then portrays predictive patterns of critical elements. The results show that the business environment provides substantial predictive ability for innovation quality, increasing out-of-sample R2 from 0.6200 to 0.7001, which represents an improvement of 0.0801. Among the focal explanatory variables, human resources, financial environment, and public services emerge as relatively important elements. Furthermore, we find that human resources and innovation quality exhibit an overall upward trend, whereas public services and financial environment have a complex relationship with innovation quality. Heterogeneity analysis reveals that the predictive ability of the business environment for innovation quality varies significantly across firms with different ownership and locations. Our study provides evidence for policy design and business environment optimization to strengthen the institutional foundations of sustainable development.
Liu et al. (Thu,) studied this question.