How industrial convergence affects regional green development efficiency: A spatial conditional process analysis

Industrial convergence is a key means to transform the economic mode. Taking the convergence of manufacturing and producer services in China as the research object, this study explored how industrial convergence affects regional green development efficiency (GDE). First, a coupling evaluation system was established to measure industrial convergence degree, and the directional distance function-based slacks-based measure was combined with the global Malmquist-Luenberger index to measure GDE. Second, we employed spatial econometric models to analyze the relationship between industrial convergence and GDE. Then, using the spatial conditional process analysis, a unified framework of green innovation, investment structure, and energy intensity was constructed to investigate the transmission mechanism involved. The results showed that: (1) Regional GDE and green innovation had a spatial dependence. (2) Considering the spatial correlation, industrial convergence is conductive to regional GDE. (3) Green innovation is an effective path by which industrial convergence improves regional GDE. (4) In this mediating process, the investment structure and energy intensity play a moderating role. The investment bias in high-tech industries increases the role of industrial convergence in promoting regional GDE and green innovation, while the moderating direction of energy intensity is opposite. In addition, there is a crowding-out effect in energy dependence, which hinders the effectiveness of green innovation.

Automated summary

The study found that industrial convergence has a positive impact on regional green development efficiency, especially through promoting green innovation. Investment structure and energy intensity play a moderating role in the mediating process.