A sustainable mechanism for digitization to promote green technological innovation in enterprises

Abstract

This study delves into the spatial-temporal dynamics of urban digital advancement and its green economic efficacy through methods like kernel density analysis, exploratory spatial data analysis, Gini coefficient, and coefficient of variation. Utilizing entropy weighting and regression analysis, it investigates the influence of digital development on green economic efficiency. Sustainable development performance (EWS), the volume of green patent applications (Lngrd), and other pivotal control variables are incorporated into a regression framework to elucidate the mechanisms by which digital evolution impacts green economic efficiency. Empirical findings reveal a consistent annual growth rate exceeding 5% across six regions, showcasing the steady progress and substantial achievements in digitalization. However, a wide disparity exists within enterprise digitalization levels, with the maximum digital transformation index at 4.996, a minimum of 0.002, and a median of 0.696, indicating an ongoing uneven development. Digital transformation significantly enhances corporate green technological innovation, evidenced by a coefficient of 0.014. Its effect on sustainability performance is notably more substantial in enterprises with higher equity concentrations (0.004) and greater pollution levels (0.005).

Keywords

• kernel density analysis
• spatiotemporal evolution characteristics
• entropy weight method
• regression model
• green technology
• 97m50