Green technology innovation is essential to promoting not only the construction of ecological civilization but also the fundamental means of achieving sustainable development. Taking research and development (R&D) investment, CO2 emissions, and other related factors into account, this study constructed an extended logarithmic mean Divisia index (LMDI) decomposition model for the change in the number of green technology patent applications to quantify the contribution of each driving factor based on green patent applications data in China from 2000 to 2017. The results indicated that economic scale, R&D efficiency, R&D reaction, and green patent share play positive roles in promoting green patent applications in China, among which R&D efficiency is the most significant contributor. By contrast, carbon intensity plays a dampening role. The conclusions of this study could provide a theoretical foundation for China to formulate targeted green technology innovation management policies, promotion measures, and related R&D strategies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.