LAUSR

Abstract Green innovation is the main force to drive China’s intensive pollution industries (IPIs) into sustainable development. Improving green innovation efficiency (GIE) is an effective way to reach this goal. The correct approach to measuring IPIs’ GIE and its influencing factors is a hot issue. Based on the panel data of China’s 21 subdivided industries of IPIs over the period from 2011 to 2015, this paper applies the Super-Slack-Based Measurement (Super-SBM) and Tobit model to analyse IPIs’ GIE and its influencing factors, respectively. The results show that IPIs’ overall efficiency fluctuates around 0.67 in the first 4 years and increases to 0.776 in 2015, failing to be DEA-efficient; there are obvious gaps in GIE between the 21 industries, and the ferrous metal smelting and calendering industry has the weakest GIE. The regression results show that, government R&D support and environmental regulation have inverted U-shaped and U-shaped relationship with IPIs’ GIE, respectively. Foreign market demand and market competition have significant positive and negative impacts on GIE, respectively, but the impact of market openness is not significant. The results suggest that (1) Chinese government should increase R&D support for IPIs, especially for those with low GIE, and strengthen supervision of the use of government R&D funds to avoid the crowding-out effect, (2) strengthen the intensity of environmental supervision and enforcement of environmental regulation policies, (3) improve environmental protection standards and preferential policies for exportation at the same time, (4) promote industrial restructuring and improve the mechanism of resource and benefit sharing to promote the flow of innovative resources and diffusion of innovative achievements.