[1] BOWER J L, CHRISTENSEN C M. Disruptive technologies: catching the wave[J]. Harvard business review, 1995, 73(1): 75-76.
[2] CHRISTENSEN C M. The innovators dilemma: when new technologies cause great firms to fail[M]. Boston: Harvard Business School Press, 1997.
[3] 李平. 颠覆性创新的机理性研究[M]. 北京: 经济管理出版社, 2018: 10-11. (LI P. Research on the mechanism of disruptive innovation[M]. Beijing: Economic Management Press, 2018: 10-11.)
[4] NAGY D, SCHUESSLER J, DUBINSKY A. Defining and identifying disruptive innovations[J]. Industrial marketing management, 2016, 57: 119-126.
[5] 苏成, 赵志耘, 赵筱媛, 等. 颠覆性技术新阐释：概念、内涵及特征[J]. 情报学报, 2021, 40(12): 1253-1262. (SU C, ZHAO Z Y, ZHAO X Y, et al. New explanation on disruptive technology: concept, connotation and features [J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(12): 1253-1262.)
[6] 梁镇涛, 毛进, 李纲. 融合“科学-技术”知识关联的高颠覆性专利预测方法[J]. 情报学报, 2023, 42(6): 649-662. (LIANG Z T, MAO J, LI G. A highly disruptive patent prediction method integrating “science-technology” knowledge association [J]. Journal of the China Society for Scientific and Technical Information, 2023, 42(6): 649-662.)
[7] 李晓龙, 鲁平, 李存斌. 基于Delphi和DEMATEL法影响国网的颠覆性创新技术影响因素综合排序分析[J]. 科技管理研究, 2017, 37(6): 127-133. (LI X L, LU P, LI C B. A comprehensive ranking analysis of the influencing factors of disruptive innovation technology on State Grid based on Delphi and DEMATEL methods[J]. Science and technology management research, 2017, 37(6): 127-133.)
[8] 张欣. 颠覆性技术识别方法述评[J]. 图书情报工作, 2020, 64(17): 145-152. (ZHANG X. Review of disruptive technology identification methods[J]. Library and information service, 2020, 64(17): 145-152.)
[9] DIXON T, EAMES M, BRITNELL J, et al. Urban retrofitting: identifying disruptive and sustaining technologies using performative and foresight techniques[J]. Technological forecasting and social change, 2014, 89(11): 131-144.
[10] VOJAK B A, CHAMBERS F A. Road mapping disruptive technical threats and opportunities in complex, technology based subsystems: the SAILS methodology[J]. Technological forecasting and social change, 2004, 71(1-2): 121-139.
[11] 王知津, 周鹏, 韩正彪. 基于情景分析法的技术预测研究[J]. 图书情报知识, 2013(5): 115-122. (WANG Z J, ZHOU P, HAN Z B. Research on technology forecast based on scenario analysis[J]. Documentation, information & knowledge, 2013(5): 116-122.)
[12] 侯广辉, 廖桂铭, 王刚. 基于突变级数的颠覆性技术识别模型构建及实证研究[J]. 情报杂志, 2021, 40(10): 7-14. (HOU G H, LIAO G M, WANG G. Construction and empirical study of disruptive technology identification model based on mutation series [J]. Journal of intelligence, 2021, 40(10): 7-14.)
[13] 黄鲁成, 成雨, 吴菲菲, 等. 关于颠覆性技术识别框架的探索[J]. 科学学研究, 2015, 33(5): 654-664. (HUANG L C, CHENG Y, WU F F, et al. Exploration of a framework for identifying disruptive technologies[J]. Studies in science of science, 2015, 33(5): 654-664.)
[14] CHENG Y, HUANG L, LI X, et al. Forecasting of potential impacts of disruptive technology in promising technological areas: elaborating the SIRS epidemic model in RFID technology[J]. Technological forecasting and social change, 2017, 117(4): 170-183.
[15] CHEN C, ZHANG J, GUO R S. The D-Day, V-Day, and bleak days of a disruptive technology: a new model for ex-ante evaluation of the timing of technology disruption[J]. European journal of operational research, 2016, 251(2): 562-574.
[16] GUO J, PAN J F, GUO J X, et al. Measurement framework for assessing disruptive innovations[J]. Technological forecasting and social change, 2019, 139(2): 250-265.
[17] GANGULY A, NILCHIANI R, FARR J V. Defining a set of metrics to evaluate the potential disruptiveness of a technology[J]. Engineering management journal, 2010, 22(1): 34-44.
[18] DOTSIKA F, WATKINS A. Identifying potentially disruptive trends by means of keyword network analysis[J]. Technological forecasting and social change, 2017, 119: 114-127.
[19] MOMENI A, ROST K. Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling[J]. Technological forecasting and social change, 2016, 104: 16-29.
[20] 于光辉, 宁钟, 李昊夫. 基于专利和Bass模型的颠覆性技术识别方法研究[J]. 科学学研究, 2020(9): 1-12. (YU G H, NING Z, LI H F. Research on disruptive technology identification methods based on patents and bass models[J]. Studies in science of science, 2020(9): 1-12.)
[21] FLEMING L. Recombinant uncertainty in technological search[J]. Management science, 2001, 47(1): 117-132.
[22] KARVONEN M, KÄSSI T. Patent citations as a tool for analysing the early stages of convergence[J]. Technological forecasting and social change, 2013, 80(6): 1094-1107.
[23] 赵玉桐, 杨建林. 基于跨领域专利的颠覆性技术识别研究——以人工智能领域为例[J]. 情报理论与实践, 2023, 46(3): 174-182. (ZHAO Y T, YANG J L. Research on disruptive technology identification based on cross domain patents: taking the field of artificial intelligence as an example[J]. Information studies: theory & application, 2023, 46(3): 174-182.)
[24] TORTORIELLO M, MCEVILY B, KRACKHARDT D. Being a catalyst of innovation: the role of knowledge diversity and network closure[J]. Organization science, 2015, 26(2): 423-438.
[25] 李乾瑞, 郭俊芳, 黄颖, 等. 基于专利计量的颠覆性技术识别方法研究[J]. 科学学研究, 2021, 39(7): 1166-1175. (LI Q R, GUO J F, HUANG Y, et al. Research on disruptive technology identification methods based on patent metrology[J]. Studies in science of science, 2021, 39(7): 1166-1175.)
[26] 李乾瑞, 郭俊芳, 黄颖, 等. 基于突变-融合视角的颠覆性技术主题演化研究[J]. 科学学研究, 2021, 39(12): 2129-2139. (LI Q R, GUO J F, HUANG Y, et al. Research on the evolution of disruptive technology themes from the perspective of mutation fusion[J]. Studies in science of science, 2021, 39(12): 2129-2139.)
[27] 黄鲁成, 蒋林杉, 吴菲菲. 萌芽期颠覆性技术识别研究[J]. 科技进步与对策, 2019, 36(1): 10-17. (HUANG L C, JIANG L S, WU F F. Research on the identification of disruptive technologies during the embryonic stage[J]. Science & technology progress and policy, 2019, 36(1): 10-17.)
[28] 苗红, 王晓宇, 黄鲁成, 等. 基于专利的跨领域技术特征测度与分析[J]. 情报学报, 2015, 34(5): 484-492. (MIAO H, WANG X Y, HUANG L C, et al. Measurement and analysis of cross domain technical features based on patents[J]. Journal of the China Society for Scientific and Technical Information, 2015, 34(5): 484-492.)
[29] 王康, 陈悦. 技术融合视角下基于专利的颠覆性技术识别研究[J]. 情报杂志, 2022, 41(4): 29-36, 134. (WANG K, CHEN Y. Research on patent based disruptive technology identification from the perspective of technology fusion[J]. Journal of intelligence, 2022, 41(4): 29-36, 134.)
[30] 曹晓阳, 白光祖. 以颠覆性技术创新培育发展新质生产力[N]. 科技日报, 2024-02-22(8). (CAO X Y, BAI G Z. Cultivate and develop new quality productive forces through disruptive technological innovation[N]. Science and technology daily, 2024-02-22(8).)
[31] 李丫丫, 赵玉林. 基于专利的技术融合分析方法及其应用[J]. 科学学研究, 2016, 34(2): 203-211. (LI Y Y, ZHAO Y L. Patent based technology fusion analysis method and application[J]. Studies in science of science, 2016, 34(2): 203-211.)
[32] 黄颖, 张琳, 孙蓓蓓, 等. 跨学科的三维测度——外部知识融合、内在知识会聚与科学合作模式[J]. 科学学研究, 2019, 37(1): 25-35. (HUANG Y, ZHANG L, SUN B B, et al. Cross disciplinary three-dimensional measurement: external knowledge fusion, internal knowledge convergence, and scientific cooperation models[J]. Studies in science of science, 2019, 37(1): 25-35.)
[33] 韩正琪, 刘小平, 寇晶晶. 基于Rao-Stirling指数和LDA模型的领域学科交叉主题识别——以纳米科技为例[J]. 情报科学, 2020, 38(2): 116-124. (HAN Z Q, LIU X P, KOU J J. Domain disciplinary cross topic recognition based on Rao Stirling index and LDA model: taking nanotechnology as an example[J]. Information science, 2020, 38(2): 116-124.)
[34] LEYDESDORFF L, RAFOLS I. Indicators of the interdisciplinarity of journals: diversity, centrality, and citations[J]. Journal of informetrics, 2011, 5(1): 87-100.
[35] LEYDESDORFF L, KUSHNIR D, RAFOLS I. Interactive overlay maps for US patent (USPTO) data based on international patent classification (IPC) [J]. Scientometrics, 2014, 98(3): 1583-1599.
[36] 陈育新, 卢俊, 韩毅. 基于专利文献的颠覆性技术识别研究——以人工智能为例[J]. 情报学报, 2022, 41(11): 1124-1133. (CHEN Y X, LU J, HAN Y. Research on disruptive technology identification based on patent literature: taking artificial intelligence as an example[J]. Journal of the China Society for Scientific and Technical Information, 2022, 41(11): 1124-1133.)
[37] 柯建坤, 许忠好. Louvain算法与K均值聚类算法的比较研究[J]. 应用概率统计, 2022, 38(5): 780-790. (KE J K, XU Z H. Comparative study of Louvain algorithm and K-means clustering algorithm [J]. Chinese journal of applied probability and statistics, 2022, 38(5): 780-790.)
[38] LANCICHINETTI A, FORTUNATO S. Community detection algorithms: a comparative analysis[J]. Physical Review E, 2009, 80(5): 11-21.
[39] DONNA J K, ABDUL A, SHAKER A Z. Where do breakthroughs come from? Characteristics of high-potential inventions[J]. Journal of product innovation management, 2013, 30(6): 1212–1226.
[40] MALVA D, KELCHTERMANS A, LETEN B, et al. Basic science as a prescription for breakthrough inventions in the pharmaceutical industry[J]. The journal of technology transfer, 2015, 40(4): 670-695.
[41] SCHOENMAKERS W, DUYSTERS G. The technological origins of radical inventions[J]. Research policy, 2010, 39(8): 1051-1059.
[42] DAHLIN K B, BEHRENS D M. When is an invention really radical? Defining and measuring technological radicalness[J]. Research policy, 2005, 34(5): 717-737.
[43] CARLO J L, LYYTINEN K, ROSE G M. A knowledge-based model of radical innovation in small software firms[J]. MIS quarterly, 2012, 36(3): 865-895.
[44] AN X, LI J, XU S, et al. An improved patent similarity measurement based on entities and semantic relations[J]. Journal of informetrics, 2021, 15(2): 1-16.
[45] GIORDANO V, CHIARELLO F, MELLUSO N, et al. Text and dynamic network analysis for measuring technological convergence: A case study on defense patent data[J]. IEEE transactions on engineering management, 2023, 70(4): 1490-1503.
[46] YUN J, GEUM Y. Analysing the dynamics of technological convergence using a co-classification approach: a case of healthcare services[J]. Technology analysis and strategic management, 2019, 31(12): 1412-1429.
[47] 张齐. 基于熵的复杂网络结构特性研究[D]. 重庆: 西南大学, 2017.(ZHANG Q. Research on the characteristics of complex network structures based on entropy[D]. Chongqing: Southwest University, 2017.)
[48] 谭跃进, 吴俊. 网络结构熵及其在非标度网络中的应用[J].系统工程理论与实践, 2004, 24(6): 1-3. (TAN Y J, WU J. Network structure entropy and its application to scale-free networks[J]. Systems engineering-theory & practice, 2004, 24(6): 1-3.)
[49] 田雪姣, 鲍新中, 杨大飞, 等. 基于熵权-TOPSIS-德尔菲法的核心技术识别研究——以芯片产业技术为例[J]. 情报杂志, 2022, 41(8): 69-74, 86. (TIAN X J, BAO X Z, YANG D F, et al. Research on core technology identification based on entropy weight TOPSIS delphi method: taking chip industry technology as an example[J]. Journal of intelligence, 2022, 41(8): 69-74, 86.)
[50] 蒲慕明. 脑科学研究的三大发展方向[J]. 中国科学院院刊, 2019, 34(7): 807-813. (PU M M. The three major development directions of brain science research[J]. Journal of the Chinese Academy of Sciences, 2019, 34(7): 807-813.)
[51] 阮梅花, 袁天蔚, 王慧媛, 等.神经科学和类脑人工智能发展:未来路径与中国布局——基于业界百位专家调研访谈[J]. 生命科学, 2017, 29(2): 97-113. (RUAN M H, YUAN T W, WANG H Y, et al. Development of neuroscience and brain like artificial intelligence: future paths and China's layout: based on research interviews with 100 industry experts[J]. Chinese bulletin of life sciences, 2017, 29(2): 97-113.)
[52] 韩芳, 张生太, 冯凌子, 等. 基于专利文献技术融合测度的突破性创新主题识别——以太阳能光伏领域为例[J]. 数据分析与知识发现, 2021, 5(12): 137-147. (HAN F, ZHANG S T, FENG L Z, et al. Breakthrough innovation theme identification based on patent literature technology fusion measurement: taking the solar photovoltaic field as an example[J]. Data analysis and knowledge discovery, 2021, 5(12): 137-147.)
[53] 王学生, 王革. 中位数检验法在偏态分布资料中应用[J]. 中国公共卫生, 2001(5): 81-82. (WANG X S, WANG G. Application of median test method in skewed distribution data[J]. Chinese journal of public health, 2001(5): 81-82.)
[54] NORTON A P, KEELEY M. Optimal fixed-size windows and dynamic asset allocation[J]. Journal of portfolio management, 2009, 35(2): 58-68.
[55] 杨仲基, 王宏起, 王珊珊, 等. 基于动态网络方法的产业专利合作态势研究——以中国石墨烯产业为例[J]. 科技进步与对策, 2018, 35(9): 59-65. (YANG Z J, WANG H Q, WANG S S, et al. A Study on the situation of industrial patent cooperation based on dynamic network method - taking China's graphene industry as an example[J]. Science & technology progress and policy, 2018, 35(9): 59-65.)
[56] 王淑娜. 类脑用于脑卒中移植治疗及人源化模型构建的研究[D]. 上海:中国人民解放军海军军医大学, 2019. (WANG S N. A study on the application of brain analogues in stroke transplantation treatment and the construction of humanized models [D]. Shanghai: Naval Medical University, 2019.)
[57] SHIH J J, KRUSIENSKI D J, WOLPAW J R. Brain-computer interfaces in medicine[J]. Mayo clinic proceedings, 2012, 87(3): 268-279.
[58] 黄铁军, 施路平, 唐华锦, 等. 多媒体技术研究:2015——类脑计算的研究进展与发展趋势[J]. 中国图象图形学报, 2016, 21(11): 1411-1424. (HUANG T J, SHI L P, TANG H J, et al. Research on multimedia technology: 2015- research progress and development trends of brain like computing[J]. Journal of image and graphics, 2016, 21(11): 1411-1424.)
[59] 项水英, 宋紫薇, 高爽, 等. 光神经形态计算研究进展与展望（特邀）[J]. 光子学报, 2021, 50(10): 40-56. (XIANG S Y, SONG Z W, GAO S, et al. Progress and prospects of photoneural morphology calculation research (invited)[J]. Acta photonica sinica, 2021, 50(10): 40-56.)
[60] 赵地, 肖立. 基于神经形态计算的新一代感知系统研究进展[J]. 人工智能, 2020(1): 32-35. (ZHAO D, XIAO L. Research progress in the new generation perception system based on neuromorphic computing[J]. AI-View, 2020(1): 32-35.)
[61] 陈怡然, 李海, 陈逸中, 等. 神经形态计算发展现状与展望[J]. 人工智能, 2018(2): 46-58. (CHEN Y R, LI H, CHEN Y Z. Current status and prospects of neuromorphic computing development[J]. AI-View, 2018(2): 46-58.)
