Zusammenfassung:
Industry is the main source of carbon emissions, and reducing emissions is closely linked to advancing carbon neutrality. Moreover, technological innovation is crucial for industrial low-carbon development. This study uses provincial panel data from China covering 2010 to 2023 and employs the Stochastic Non-smooth Envelopment of Data model to measure industrial carbon emissions efficiency. Combining listed companies' green patent text data, we calculate related and unrelated green technological diversification to investigate the impact of related and unrelated green technological diversification on industrial carbon emissions efficiency using a panel quantile model. The study also explores the moderating role of technological specialisation, revealing that related and unrelated green technological diversification promote industrial carbon emissions efficiency at different quantile levels; however, the positive effect diminishes as quantile levels rise. Furthermore, related green technological diversification has a stronger impact than unrelated green technological diversification, and related and unrelated green technological diversification have a greater effect on accelerating industrial carbon emissions efficiency in non-coastal, low-income and low market share regions. Finally, technological specialisation has a stronger complementary impact on related green technological diversification than on unrelated green technological diversification in enhancing industrial carbon emissions efficiency. The conclusions of this study provide novel insights into advancing industrial green transformation.