摘要
[目的/意义]“卡脖子”技术是现阶段制约我国战略性新兴产业高质量发展的关键瓶颈,为实现产业链自主安全可控,高效准确识别“卡脖子”技术十分必要。[方法/过程]以专利文献作为数据来源,首先根据技术共现网络测度并遴选关键核心技术,其次基于技术差距及技术依赖的视角,综合考虑后发优势与自主创新能力的关系,从技术价值优势、技术竞争优势、技术垄断地位和自主创新能力这4个维度设计“卡脖子”技术识别指标体系,然后运用CRITIC-TOPSIS方法构建一套系统的“卡脖子”技术识别模型,最后在数控机床领域进行实证研究。[结果/结论]应用所提出方法的识别结果是,我国在数控机床领域存在34项潜在“卡脖子”技术,主要集中在数控机床控制或调节系统、数控机床关键功能部件、车削或镗削数控机床、电数字数据处理等领域,将此结果与美国商业出口管制清单进行对比,具有较好的一致性,由此验证本方法的可行性和可靠性。
[Purpose/Significance]“Neck Stuck”technologies is the key point that restricts the high-quality development of China’s strategic emerging industries at the present stage.To ensure the independent security control of the industrial chain,it is necessary to identify the“Neck Stuck”technologies efficiently and accurately.[Method/Process]This study utilized patent literature as the main data source.Firstly,key core technologies were selected based on technical co-occurrence network measurements.Secondly,the relationship between latecomer advantages and independent innovation capabilities was comprehensively considered from the perspective of technical gap and technical dependence.A“Neck Stuck”technologies identification index system was designed across four dimensions:technical value advantage,technical competition advantage,technical monopoly status,and independent innovation ability.Then,a systematic“Neck Stuck”technologies identification model was constructed using the CRITIC-TOPSIS method.Finally,empirical research was conducted in the field of CNC machine tools.[Result/Conclusion]The results of the identification process using the proposed method in this study reveal the existence of 34 potential“Neck Stuck”technologies in the field of CNC machine tools in China.These technologies are primarily concentrated in the control or adjustment system,key functional components,turning or boring CNC machine tools,and digital data processing.A comparison of these findings with the U.S.Commerce Control List confirms the high degree of consistency,thus validating the feasibility and reliability of the proposed method.
作者
曹琨
吴新年
白光祖
郑玉荣
靳军宝
李莉
Cao Kun;Wu Xinnian;Bai Guangzu;Zheng Yurong;Jin Junbao;Li Li(Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000;Department of Information Resources Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100049;Chinese Academy of Engineering Innovation Strategy,Beijing 100088)
出处
《图书情报工作》
北大核心
2023年第19期80-91,共12页
Library and Information Service
基金
国家社会科学基金项目“演化视角下新兴技术形成机制与识别方法研究”(项目编号:20BTQ094)
中国工程院紧急重点咨询项目“技术贸易安全管理前沿研究”(项目编号:2021-JZ-10)研究成果之一。