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基于专利和科技论文的技术机会识别研究——以金属3D打印技术为例 被引量:14

Research on Technology Opportunity Identification Based on Patent and Scientific Papers:An Case of Metal 3D Printing
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摘要 主要基于Web of Science科技论文和Derwent专利文献,利用SATI、SPSS等分析工具,提取文本关键词并构建相异共现矩阵,采用多维聚类方法识别研究热点主题。在继承和发展Naoki Shibata技术机会理论的基础上,通过对比科技论文和专利文献研究热点主题的差异来识别金属3D打印的技术机会。研究得出,科技论文和专利文献分别有4个研究热点主题,识别了两大类共4个技术机会。首次基于专利和科技论文研究金属3D打印的技术机会,开拓了金属3D打印的研究视野,对金属3D打印行业的企业战略决策具有指导作用。 Metal 3D printing is the crown of the modern manufacturing industry, the identification of metal 3D printing technology opportunities for rapidly improving the core competitiveness of China's manufacturing industry is of great significance. Mainly based on the Web of Science technology papers and Derwent patent documents, the use of SATI, SPSS and other analysis tools to extract text keywords and construct different co-occurrence matrix, multidimensional clustering method is used to identify the hot topics of research. On the basis of inheriting and developing the theory of the opportunity of Naoki Shibata technology, by comparing the technical papers and patent literature to study the differences in hot topics to identify the metal 3D printing technology opportunities. The research results show that there are 4 respectively research hot topics in scientific and technical papers and patent documents, and there are a total of 4 kinds of technical opportunities in the top 2 categories. This paper is the first time to study the technical opportunity of metal 3D printing based patent and scientific paper, which opens up the research field of vision, and it plays an important guiding role in the enterprise strategic decision making in the metal 3D printing industry.
作者 王坤 王京安 汤月 校姜文 Wang Kun;Wang Jing'an;Tang Yue;Xiao Jiangwen(School of Economics and Management, Nanjing Tech University, Nanjing 211800, China)
出处 《科技管理研究》 CSSCI 北大核心 2018年第7期73-79,共7页 Science and Technology Management Research
基金 国家自然科学基金面上项目"技术范式转换预警的理论与方法"(71473119)
关键词 金属3D打印 研究热点 多维聚类 技术机会 专利 科技论文 metal 3D printing research focus multidimensional clustering technology opportunity patent scientific paper
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