Using Patent Data to Evaluate the Knowledge Dissemination of the Offshore Wind Power Industry

Abstract

Many countries use the offshore wind power technology as renewable energy for sustainable development. In this study, we will focus on the knowledge dissemination of the offshore wind power technology. Not every country has the ability to develop their own offshore wind power technologies. The knowledge dissemination on sustainable technology could bridge the technology gap among the developer and promote the development of sustainable clean energy technology. Some objective evaluation indicators of knowledge dissemination will be carried out in this research and help to find appropriate companies to assist the local industry on offshore wind power industry. The public patent information is used to build a model to bring evaluation indicators about knowledge dissemination. These evaluation indicators include the revealed symmetric technological advantage index (RSTA), the knowledge density index ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D_c,m,t</i> ), and the relatedness knowledge base index ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R_c,r,t</i> ). For RSTA, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> indicators, Siemens Aktiengesellschaft, Vestas Wind Systems, Siemens Gamesa Renewable Energy, and Aloys Wobben have higher values, which can be evaluated to have the higher degree of knowledge dissemination in the field of offshore wind power technology. Unlike previous studies that only using patent bibliographic data alone, employ evaluation indicators can extract more information about the knowledge dissemination. This study presents a promising method to evaluate the degree of knowledge dissemination in offshore wind power technology by using patent data.