Research on Green Innovation Efficiency Measurement and Influencing Factors of Listed Power Generation Enterprises in China

Driven by the global transition to low-carbon energy and China's “dual carbon” goals, the power generation industry, as one of the main sources of resource consumption and carbon dioxide emissions, is facing an urgent need for green development. This paper takes A-share listed power generation enterprises from 2014 to 2023 as the research sample, measures green innovation efficiency based on the Data Envelopment Analysis (DEA) model, and identifies key influencing factors by combining a Tobit panel regression model. The study found that: (1) Green innovation efficiency (GIE) is generally low, with significant room for improvement, and shows a “W” pattern of decline followed by increase. Among these, pure technical efficiency (PTE) and scale efficiency (SE) are both at low levels, and there is significant heterogeneity among enterprises. (2) Among external factors, government subsidies have no significant impact, while market attention has a significant positive impact on green innovation efficiency through pure technical efficiency. Among internal factors, innovation level and capital intensity have a significant negative impact, while human resource level and enterprise scale have a significant positive impact, affecting green innovation efficiency through pure technical efficiency and scale efficiency, respectively.