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Low-carbon energy innovation and implementation is essential to combat climate change, promote economic competitiveness, and achieve energy security. Our study of clean energy patenting in the United States is undertaken to elicit fundamental trends and implications that can inform public and private innovation investment, resulting in greater efficiency of research and development programs. Using U.S. patent data and additional patent-relevant data collected from the Internet, we map the landscape of low-carbon energy innovation in the United States since 1975. We isolate 10,603 renewable and 10,442 traditional energy patents and develop a database that characterizes proxy measures for technical and commercial impact, as measured by patent citations and Web presence, respectively. Regression models and multivariate simulations are used to compare the social, institutional, and geographic drivers of breakthrough clean energy innovation. Results indicate statistically significant effects of social, institutional, and geographic variables on technical and commercial impacts of patents and unique innovation trends between different energy technologies. We observe important differences between patent citations and Web presence of licensed and unlicensed patents indicating the potential utility of using screened Web hits as a measure of commercial importance. We offer hypotheses for these revealed differences and suggest a research agenda with which to test these hypotheses. These preliminary findings indicate that leveraging empirical insights to better target research expenditures could augment the speed and scale of innovation and deployment of clean energy technologies.
Claudia Rebeca Binder Signer, Selin Yilmaz, Matteo Barsanti