[1] CHRISTENSEN C M. The innovator’s dilemma: when new technologies cause great firm to fail[M]. Cambridge: Harvard Business Review Press, 1997.
[2] 王康, 陈悦, 宋超, 等. 颠覆性技术：概念辨析与特征分析[J]. 科学学研究, 2022, 40(11): 1937-1946. (WANG K, CHEN Y, SONG C, et al. Disruptive technology: concept discrimination and characteristics analysis[J]. Studies in science of science, 2022, 40(11): 1937-1946.)
[3] 张金柱, 王秋月, 仇蒙蒙. 颠覆性技术识别研究进展综述[J]. 数据分析与知识发现, 2022, 6(7): 12-31. (ZHANG J Z, WANG Q Y, QIU M M. Review of studies identifying disruptive technologies[J]. Data analysis and knowledge discovery, 2022, 6(7): 12-31.)
[4] 刘小慧, 沈哲思, 廖宇, 等. 科研论文颠覆性指数的改进及其影响因素研究[J]. 图书情报工作, 2020, 64(24): 84-91. (LIU X H, SHEN Z S, LIAO Y, et al. The research about the improved disruption index and its influencing factors[J]. Library and information service, 2020, 64(24): 84-91.)
[5] 张硕, 汪雪锋, 乔亚丽, 等. 从技术预测研究现状、趋势及未来思考:数据分析视角[J]. 图书情报工作, 2022, 66(10): 4-18. (ZHANG S, WANG X F, QIAO Y L, et al. Research status, trends and future thinking of technology forecasting: from the perspective of data analytics[J]. Library and information service, 2022, 66(10): 4-18.)
[6] 乔亚丽, 黄颖, 张硕, 等. 多维视角下颠覆性技术识别：研究进展与未来思考[J]. 情报杂志, 2022, 41(8): 45-52. (QIAO Y L, HUANG Y, ZHANG S, et al. The identification of disruptive technology from a multi-dimensional perspective: research progress and future prospects[J]. Journal of intelligence, 2022, 41(8): 45-52.)
[7] CHRISTENSEN C M, RAYNOR M, MCDONALD R. What is disruptive innovation?[J]. Harvard business review, 2015, 93(12): 44-53.
[8] DANNEELS E. Disruptive technology reconsidered: a critique and research agenda[J]. Journal of product innovation management, 2004, 21(4): 246-258.
[9] SCHMIDT G M, DRUEHL C T. When is a disruptive innovation disruptive?[J]. Journal of product innovation management, 2008, 25(4): 347-369.
[10] 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. Study on identification framework of disruptive technology[J]. Studies in science of science, 2015, 33(5): 654-664.)
[11] 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, 2021, 39(8): 1467-1473, 1536. (YU G H, NING Z, LI H F. Research on identification method of disruptive technology based on patent and Bass Model[J]. Studies in science of science, 2021, 39(8): 1467-1473, 1536.)
[12] CHENG Y, HUANG L C, RAMLOGAN R, 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: 170-183.
[13] JIA W F, XIE Y P, ZHAO Y N, et al. Research on disruptive technology recognition of China’s electronic information and communication industry based on patent influence[J]. Journal of global information management, 2021, 29(2): 148-165.
[14] 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 model[J]. Journal of intelligence, 2021, 40(10): 7-14.)
[15] 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. Topic evolution research of disruptive technology based on mutation and fusion perspective[J]. Studies in science of science, 2021, 39(12): 2129-2139.)
[16] 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 disruptive technology identification based on patent from the perspective of technology convergence[J]. Journal of intelligence, 2022, 41(4): 29-36, 134.
[17] 王康, 陈悦, 王玉奇, 等. 基于专利引用变化的颠覆性技术识别研究[J]. 情报杂志, 2022, 41(1): 74-80, 169. (WANG K, CHEN Y, WANG Y Q, et al. Research on disruptive technology identification based on patent citation changes[J]. Journal of intelligence, 2022, 41(1): 74-80, 169.)
[18] 吴可凡, 王伟, 张世玉, 等. 技术不连续性视角下颠覆性技术识别方法研究[J]. 情报理论与实践, 2022, 45(10): 125-131. (WU K F, WANG W, ZHANG S Y, et al. Research on disruptive technology identification methods from the perspective of technology discontinuities[J]. Information studies: theory & application, 2022, 45(10): 125-131.)
[19] 单晓红, 韩晟熙, 刘晓燕. 基于技术主题演化的颠覆性技术识别研究[J]. 情报理论与实践, 2023, 46(8): 113-123. (SHAN X H, HAN S X, LIAO X Y. Research on disruptive technology identification based on the evolution of technology themes[J]. Information studies: theory & application, 2023, 46(8): 113-123.)
[20] 许佳琪, 汪雪锋, 雷鸣, 等. 从突破性创新到颠覆性创新：内涵、特征与演化[J]. 科研管理, 2023, 44(2): 1-13. (XU J Q, WANG X F, LEI M, et al. From breakthrough innovation to disruptive innovation: their connotations, characteristics and evolution[J]. Science research management, 2023, 44(2): 1-13.)
[21] SAINIO L M, PUUMALAINEN K. Evaluating technology disruptiveness in a strategic corporate context: a case study[J]. Technological forecasting and social change, 2007, 74(8): 1315-1333.
[22] 邓建军, 刘安蓉, 曹晓阳, 等. 颠覆性技术早期识别方法框架研究――基于科学端的视角[J]. 中国科学院院刊, 2022, 37(5): 674-684. (DENG J J, LIU A R, CAO X Y, et al. Methodological framework of identifying disruptive technologies on emerging stage: based on science[J]. Bulletin of Chinese academy of sciences, 2022, 37(5): 674-684.)
[23] 庞弘燊, 钟秀梅. 颠覆性技术产生过程的多源数据多特征项可视化研究[J]. 图书情报工作, 2022, 66(19): 122-131. (PANG H S, ZHONG X M. A visualization study for understanding disruptive technology evolution based on multi-feature co-occurrence network analysis of multi-source literature[J]. Library and information service, 2022, 66(19): 122-131.)
[24] 吕璐成, 赵萍, 姜山, 等. 基于候选技术辅助生成和多源数据评估的颠覆性技术识别方法研究[J]. 情报理论与实践, 2023, 46(6): 136-144. (LV L C, ZHAO P, JIANG S, et al. Research on disruptive technology identification method based on candidate technology aided generation and multi-source data evaluation[J]. Information studies: theory & application, 2023, 46(6): 136-144.)
[25] 谭晓, 西桂权, 苏娜, 等. 科学—技术—项目联动视角下颠覆性技术识别研究[J]. 情报杂志, 2023, 42(2): 82-91. (TAN X, XI G Q, SU N, et al. Disruptive technology identification: from the perspective of science and technology project linkage[J]. Journal of intelligence, 2023, 42(2): 82-91.)
[26] KELLER A, HUSIG S. Ex ante identification of disruptive innovations in the software industry applied to web applications: the case of Microsoft’s vs. Google’s office applications[J]. Technological forecasting and social change, 2009, 76(8): 1044-1054.
[27] 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 the method of disruptive technology identification based on patent bibliometrics[J]. Studies in science of science, 2021, 39(7): 1166-1175.)
[28] 刘志辉, 张均胜, 林毅, 等. 基于隐性知识的潜在颠覆性技术评估方法研究[J]. 情报学报, 2021, 40(12): 1271-1278. (LIU Z H, ZHANG J S, LIN Y, et al. Potential disruptive technology assessment method based on implicit knowledge[J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(12): 1271-1278.)
[29] 陈育新, 李健, 韩毅. 核心—边缘理论视角下的颠覆性技术识别研究[J]. 情报理论与实践, 2022, 45(8): 121-129. (CHEN Y X, LI J, HAN Y. Research on a method to identify disruptive technologies in the view of core-periphery theory[J]. Information studies: theory & application, 2022, 45(8): 121-129.)
[30] 马永红, 孔令凯, 林超然, 等. 基于异构数据的颠覆性技术识别研究——以智能制造装备领域为例[J]. 现代情报, 2022, 42(07): 92-104. (MA Y H, KONG L K, LIN C R, et al. Research on the identification of disruptive technologies based on heterogeneous data: an example in the field of intelligent manufacturing equipment[J]. Journal of modern information, 2022, 42(7): 92-104.)
[31] 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.)
[32] BLEI D M, NG A Y, JORDAN M I. Latent Dirichlet allocation[J]. Journal of machine learning research, 2003, 3(4/5): 993-1022.
[33] 李牧南, 王雯殊. 基于文本挖掘的人工智能科学主题演进研究[J]. 情报杂志, 2020, 39(6): 82-88. (LI M N, WANG W S. Research on the topic evolution of artificial intelligence based on text mining[J]. Journal of intelligence, 2020, 39(6): 82-88.)
[34] 吕鲲, 陈箫羽, 靖继鹏. 基于组合分词方法和LDA模型的区块链金融产业关键技术识别研究[J]. 图书情报工作, 2022, 66(19): 110-121. (LV K, CHEN X Y, JING J P. Research on identification of key technologies in blockchain financial industry based on combined word segmentation method and LDA model[J]. Library and information service, 2022, 66(19): 110-121.)
[35] MIKOLOV T, CORRADO G, CHEN K, et al. Efficient estimation of word representations in vector space[J]. arXiv:1301.3781, 2013.
[36] 李牧南, 王良, 赖华鹏. 中文科技政策文本分类：增强的TextCNN视角[J]. 科技管理研究, 2023, 43(2): 160-166. (LI M N, WANG L, LAI H P. Text classification of Chinese S&T policies: enhanced TextCNN perspective[J]. Science and technology management research, 2023, 43(2): 160-166.)
[37] 丁敬达, 陈一帆, 刘超, 等. 基于共词和Word2Vec加权向量的文献—主题语义匹配分析方法[J]. 图书情报工作, 2022, 66(12): 108-116. (DING J D, CHEN Y F, LIU C, et al. An article-topic semantic matching analysis method based on co-word and weighted Word2Vec[J]. Library and information service, 2022, 66(12): 108-116.)
[38] 靳嘉林, 王曰芬, 巴志超, 等. 基金项目研究的主题挖掘与动态演化分析——以美国NSF数据中AI领域为例[J]. 情报学报, 2022, 41(9): 967-979. (JIN J L, WANG Y F, BA Z C, et al. Topic mining and dynamic evolution analysis of funding projects: case studies of AI field in NSF data[J]. Journal of the China Society for Scientific and Technical Information, 2022, 41(9): 967-979.)
[39] GROVER A, LESKOVEC J J A. Node2Vec: scalable feature learning for networks[J]. arXiv:1607.00653, 2016.
[40] 岳丽欣, 刘自强, 刘春江, 等. 融合引用和文本特征的技术创新路径识别研究[J]. 图书情报工作, 2023, 67(3): 49-60. (YUE L X, LIU Z Q, LIU C Q, et al. Research on technology innovation path recognition integrating citation and text features[J]. Library and information service, 2023, 67(3): 49-60.)
[41] 曹琨, 吴新年, 靳军宝, 等. 基于共词和Node2Vec表示学习的新兴技术识别方法[J]. 数据分析与知识发现, 2023, 7(9): 89-99. (CAO K, WU X N, JIN J B, et al. Identification of emerging technology based on co-words and Node2Vec representation learning[J]. Data analysis and knowledge discovery, 2023, 7(9): 89-99.)
[42] DEVLIN J, CHANG M W, LEE K, et al. BERT: pre-training of deep bidirectional transformers for language understanding[J]. arXiv:1810.04805, 2018.
[43] VASWANI A, SHAZEER N, Parmar N, et al. Attention is all you need[C]//31st annual conference on neural information processing systems (NIPS). La Jolla: Neural Information Processing Systems, 2017.
[44] VELIKOVI P, CUCURULL G, CASANOVA A, et al. Graph attention networks[J]. arXiv, 2017. arXiv:1710.10903
[45] ISMAGILOVA E, HUGHES L, DWIVEDI Y K, et al. Smart cities: advances in research-an information systems perspective[J]. International journal of information management, 2019, 47: 88-100.
[46] AAZAM M, ZEADALLY S, HARRAS K A. Deploying fog computing in Industrial Internet of Things and Industry 4.0[J]. IEEE transactions on industrial informatics, 2018, 14(10): 4674-4682.
[47] KHAN W Z, REHMAN M H, ZANGOTI H M, et al. Industrial Internet of things: recent advances, enabling technologies and open challenges[J]. Computers & electrical engineering, 2020, 81: 106522.
[48] 王昶, 邓婵, 何琪, 等. 工业互联网使用如何促进中小企业智能化转型:驱动因素与赋能机制[J]. 科技进步与对策, 2024, 41(3): 103-113. (WANG C, DENG C, HE Q, et al. How the use of industrial Internet promotes intelligent transformation of SMES: driving factors and enabling mechanism[J]. Science & technology progress and policy, 2024, 41(3): 103-113.)
[49] 吴鸣然, 黄卫东. 智慧城市建设对城市绿色创新效率的直接影响与扩散效应——基于173个城市的“准自然实验”[J]. 软科学, 2024, 38(3): 29-36. (WU M R, HUANG W D. The direct and spillover effects of smart city policy on urban green innovation efficiency: a quasi-natural experiment based on 173 cities[J]. Soft science, 2024, 38(3): 29-36.)
[50] HEIDARI A, NAVIMIPOUR N J, UNAL M. Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: a systematic literature review[J]. Sustainable cities and society, 2022, 85: 104089.
[51] DEEPA N, PHAM Q V, NGUYEN D C, et al. A survey on blockchain for big data: approaches, opportunities, and future directions[J]. Future generation computer systems-the international journal of e-science, 2022, 131: 209-226.
[52] CORALLO A, LAZOI M, LEZZI M, et al. Cybersecurity awareness in the context of the Industrial Internet of Things: a systematic literature review[J]. Computers in industry, 2022, 137: 103614.
[53] 李牧南, 王业信. 基于LDA-KeyBERT模型的技术预见：以工业互联网为例[J]. 创新科技, 2023, 23(7): 53-65. (LI M N, WANG Y X. Technology foresight based on the LDA-KeyBERT model: an instance of industrial Internet[J]. Innovation science and technology, 2023, 23(7): 53-65.)
[54] 李牧南, 赖华鹏. 基于专利文本挖掘的智慧城市技术热点分析[J]. 科技管理研究, 2023, 43(9): 132-139. (LI M N, LAI H P. Analyzing technology hotspots on smart-city based on mining patent text[J]. Science and technology management research, 2023, 43(9): 132-139.)
