颠覆性技术的科学-技术-产业互动模式识别与分析  

Recognition and Analysis of Science-Technology-Industry Interaction Patterns of Disruptive Technologies

作　　者：许海云 王超[1] 陈亮[2] 徐硕 杨冠灿 朱礼军[2] Xu Haiyun;Wang Chao;Chen Liang;Xu Shuo;Yang Guancan;Zhu Lijun(Business School,Shandong University of Technology,Zibo 255000;Institute of Scientific and Technical Information of China,Beijing 100038;School of Economics and Management,Beijing University of Technology,Beijing 100124;School of Information Resource Management,Renmin University of China,Beijing 100872)

机构地区：[1]山东理工大学管理学院,淄博255000 [2]中国科学技术信息研究所,北京100038 [3]北京工业大学经济与管理学院,北京100124 [4]中国人民大学信息资源管理学院,北京100872

出　　处：《情报学报》2023年第7期816-831,共16页Journal of the China Society for Scientific and Technical Information

基　　金：国家自然科学基金项目“基于弱信号时效网络演化分析的变革性科技创新主题早期识别方法研究”(72274113);山东省自然科学基金“基于弱信号分析的变革性创新主题早期识别方法研究”(ZR2022MG052);山东省“泰山学者”人才工程项目(tsqn202103069)。

摘　　要：颠覆性技术是“从0到1”的技术研发,可对主流技术和现有产业产生变革性效果,形成阶跃式创新轨迹,推动经济社会发展产生突变式进步。探索颠覆性技术的科学-技术-产业之间的互动模式,对探索颠覆性技术内在的产生与发展规律、前瞻识别潜在颠覆性技术具有指导作用。本文以公认度高的颠覆性技术领域为研究对象,选取领域相近的渐进性技术领域作为对比对象,以知识网络结构作为分析视角,分别构建颠覆性技术的科学、技术、产业三层知识网络;利用整体网络属性关联和网络社区相似度算法来实现知识子网间的关联测度,以此实现科学-技术-产业互动模式的识别。实证分析发现,颠覆性技术与渐进性技术在科学、技术、产业三者的关联与互动模式中存在共性特征,也存在诸多显著的差异特征。最后,提出互动模式识别对颠覆性技术识别方法和科技-产业管理的启示。Disruptive technology is a“from 0 to 1”technology innovation,which can have a disruptive effect on mainstream and existing industries,form a discontinuous innovation trajectory,and ultimately promote economic and social development to produce sudden progress.Exploring the science-technology-industry interaction model of disruptive technologies has guiding significance for exploring their inherent innovation mechanisms and identifying potential disruptive technologies.First,this study adopts well-recognized disruptive technologies as the research object,and selects progressive technologies in similar fields as comparison objects.The knowledge network structure is taken as the research perspective,and we construct a three-layer network of disruptive technologies:science,technology,and industry.Finally,the overall network attribute correlation and community similarity algorithm are used to realize the correlation measurement between knowledge subnets for the identification of science-technology-industry interaction mode.Empirical analysis reveals that disruptive and incremental technology have both commonalities and differences in the correlation and interaction mode of science,technology,and industry.Finally,we present the implications of interactive pattern recognition for disruptive technology identification methods and technology-industry management.

关 键 词：颠覆性技术 科学-技术-产业 创新生态 知识流动 知识网络 

分 类 号：G353.1[文化科学—情报学]