图书情报工作

图书情报工作 >

2021 , Vol. 65 >Issue 4: 89 - 101

DOI: https://doi.org/10.13266/j.issn.0252-3116.2021.04.010

综述述评

突破性创新早期识别与弱信号分析综述

  • 刘亚辉 ,
  • 许海云
展开
  • 1 中国科学院成都文献情报中心, 成都 610041;
    2 中国科学院大学经济与管理学院图书情报与档案管理系, 北京 100190;
    3 山东理工大学管理学院, 淄博 255000;
    4 中国科学技术信息研究所, 北京 100038
刘亚辉(ORCID:0000-0002-3577-6111),硕士研究生。

收稿日期: 2020-06-27

  修回日期: 2020-09-29

  网络出版日期: 2021-04-14

基金资助

本文系国家自然科学基金项目“基于科学-技术主题关联分析的创新演化路径识别方法研究”（项目编号：71704170）、国家重点研发计划项目课题“颠覆性技术地平线扫描系统”（项目编号：2019YFA0707202-01）和国家自然科学基金项目“科技关联视角下新兴技术弱信号扫描预判方法研究”（项目编号：72074014）研究成果之一。

收起

A Review of Early Recognition of Breakthrough Innovations and the Weak Signal Analysis

  • Liu Yahui ,
  • Xu Haiyun
Expand
  • 1 Chengdu Library of Chinese Academy of Sciences, Chengdu 610041;
    2 Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
    3 Business School, Shandong University of Technology, Zibo 255000;
    4 Institute of Scientific and Technical Information of China, Beijing 100038

Received date: 2020-06-27

  Revised date: 2020-09-29

  Online published: 2021-04-14

Fold

摘要

[目的/意义] 通过比较分析不同的突破性创新识别方法，总结现有方法存在的问题，将弱信号引入突破性创新研究的识别中，重点关注突破性创新早期的各类弱信号，尤其是弱关联关系分析，以期实现早期预判。[方法/过程] 首先，通过调研现有的识别方法，提炼当前存在的主要问题，指出研究弱信号的必要性。之后，从不同的学科角度介绍弱信号的内涵及表征形式，对其特征进行概括，梳理弱信号的几种识别方法。最后介绍弱关系分析的内涵及应用，提出借鉴多元关系融合算法模型可以实现多种弱关系的有效融合，获取更明确的信息。[结果/结论] 突破性创新的识别研究中受关注最多是文献间的引用关系、主题词之间的语义关系等强关系数据，而弱关系蕴含着更多元化的信息，加强弱关系分析可以实现对突破性创新研究的早期预判。未来研究需要寻求有效捕捉弱关联的方法，注重主题的动态演化规律，如利用高阶网络模型分析有效弱信号，提高突破性创新早期识别的准确性。

关键词： 突破性创新; 早期识别; 弱信号; 弱关系; 关系融合

本文引用格式

刘亚辉 , 许海云 . 突破性创新早期识别与弱信号分析综述[J]. 图书情报工作, 2021 , 65(4) : 89 -101 . DOI: 10.13266/j.issn.0252-3116.2021.04.010

Abstract

[Purpose/significance] This paper has summarized disadvantages of various recognition methods of breakthrough researches by comparing and analyzing these methods. Then this study has introduced weak signals into the identification of radical innovation, focusing on various types of weak signal (especially weak ties)with a view to achieving early prediction.[Method/process] Firstly, by analyzing the existing recognition methods, this paper summarized the main problems and pointed out the necessity of weak signal research. Then, this study introduced the concept and representation of weak signal from different disciplines summarized the characteristics of weak signal and combed several methods of weak signal identification. Finally, this paper introduced the connotation and application of weak ties, and proposed that the algorithm model that integrates multiple relationships can realize the effective fusion of various weak ties and obtain more clear directional information.[Result/conclusion] In the frontier research, most attention is paid to strong ties such as reference relations between literatures and semantic relations between topic terms. However, weak ties contain more diverse information, and strengthening the analysis of them can enable early recognition of breakthrough research frontier. In the future, it is necessary to seek effective methods to capture weak ties and further dig out the evolution of the theme such as:using high-order network models to analyze weak ties to improve the accuracy of early recognition.

Key words： radical innovation; early recognition; weak signal; weak linkage; multi-relations fusion

参考文献

[1] 万宁.浅析颠覆性创新、破坏性创新和突破性创新三者关系[J].商,2015(30):122-123.
[2] DOSI G, NELSON R R. Technological paradigms and technological trajectories[J]. Research policy, 1982, 11(3):147-162.
[3] TUSHMAN M L, ANDERSON P. Technological discontinuities and organizational environments[J]. Administrative science quarterly, 1986, 31(3):439-465.
[4] KOTELNIKOV V. Radical innovation versus incremental innovation[M]. Boston:Harvard Business School Press, 2000:41-85.
[5] 肖海林, 董慈慈.突破性技术创新研究:现状与展望——基于SSCI和CSSCI期刊的文献计量分析[J]. 经济管理,2020,42(2):192-208.
[6] ZHOU K Z, YIM C K,TSE D K. The effects of strategic orientations on technology- and market-based breakthrough innovations[J]. Journal of marketing, 2005, 69(2):42-60.
[7] 孙晓雅, 陈娟娟. 创新网络关系强度与创新模式关系的研究综述[J]. 技术与创新管理, 2016, 37(2):134-140.
[8] FORES B,CAMISON C.Does incremental and radical innovation performance depend on different types of knowledge accumulation capabilities and organizational size[J].Journal of business research,2016,69(2):831-848.
[9] 张金柱, 张晓林. 基于科技资源的突破性创新指标及识别方法综述[J]. 图书情报工作, 2012, 56(22):56-61.
[10] KUHN T S. The structure of scientific revolutions[J]. Physics today, 1962, 16(4):69.
[11] WRAY K B. Kuhn and the discovery of paradigms[J]. Philosophy of the social sciences, 2011, 41(3):380-397.
[12] ANDERSEN H, BARKER P, CHEN X. The cognitive structure of scientific revolutions[M]. Cambridge:Cambridge University Press, 2006:6-10.
[13] 杜建,孙轶楠,张阳,等.变革性研究的科学计量学特征与早期识别方法[J].中国科学基金,2019,33(1):88-98.
[14] GALISON P. Refections on image and logic:a material culture of microphysics[J]. Perspectives on science, 1999, 7(2):255-284.
[15] VAN RAAN A F J. On growth, ageing, and fractal differentiation of science[J]. Sentometrics, 2000, 47(2):347-362.
[16] HOLLINGSWORTH J R. Scientific discoveries:an institutionalist and path-dependent perspective[J]. Biomedical and health research, 2008,72:317-353.
[17] 蒋军锋, 李孝兵, 殷婷婷, 等. 突破性技术创新的形成:述评与未来研究[J]. 研究与发展管理, 2017(6):109-120.
[18] 李政, 刘春平, 罗晖. 浅析颠覆性技术的内涵与培育——重视颠覆性技术背后的基础科学研究[J]. 全球科技经济瞭望, 2016, 31(10):53-61.
[19] 李良德, 陈劲, 莫昕玮. 突破性创新管理模式研究[J]. 电子政务, 2001(11):38-41.
[20] 梁正, 邓兴华, 洪一晨. 从变革性研究到变革性创新:概念演变与政策启示[J]. 科学与社会, 2017(3):94-106.
[21] WINNINK J. Early-stage detection of breakthrough-class scientific research[D].Leiden:Universitite Leiden, 2017.
[22] 付玉秀, 张洪石. 突破性创新:概念界定与比较[J]. 数量经济技术经济研究, 2004, 21(3):73-83.
[23] KOSHLAND D E. The cha-cha-cha theory of scientific discovery[J]. Science, 2007, 317(5839):761-762.
[24] CAMPANARIO J M. Rejecting and resisting Nobel class discoveries:accounts by Nobel Laureates[J]. Entometrics, 2009, 81(2):549-565.
[25] Deep Tech.《麻省理工科技评论》2020年"全球十大突破性技术"[J].科技中国,2020(3):5-11.
[26] 中国科学院.2019科学发展报告[D].北京:科学出版社,2020.
[27] SMALLH G. A co-citation model of a scientific specialty:a longitudinal study of collagen research[J]. Social studies of science, 1977, 7(2):139-166.
[28] SCHNEIDER J W, COSTAS R. Identifying potential "breakthrough" publications using refined citation analyses:three related explorative approaches[J]. Journal of the Association for Information Science and Technology, 2017, 68(3):709-723.
[29] WANG J, VEUGELERS R, STEPHAN P. Bias against novelty in science:a cautionary tale for users of bibliometric indicators[J]. Research policy, 2017, 46(8):1416-1436.
[30] 李勇, 安新颖, 赵迎光,等. 结合知识组织体系的突发主题监测研究[J]. 情报理论与实践, 2013, 36(5):120-123,128.
[31] KLEINBERG J. Bursty and hierarchical structure in streams[J]. Data mining & knowledge discovery, 2003, 7(4):373-397.
[32] 张金柱, 张晓林. 基于被引科学知识主题突变的突破性创新识别[J]. 数据分析与知识发现, 2016, 32(7-8):42-50.
[33] YOON J, KIM K. Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks[J]. Scientometrics, 2011, 88(1):213-228.
[34] 罗素平,寇翠翠,金金,等.基于离群专利的颠覆性技术预测——以中药专利为例[J].情报理论与实践,2019,42(7):165-170.
[35] PALOMERAS N. Sleeping patents:any reason to wake up?[J]. Iese research papers, 2003, 20(35):1-25.
[36] 杜建."睡美人"文献的识别方法与唤醒机制研究[D].南京:南京大学,2017.
[37] VAN RAAN A F J, WINNINK J J. Do younger sleeping beauties prefer a technological prince?[J]. Scientometrics, 2018, 114(2):701-717.
[38] SOOD A, TELLIS G J. Technological evolution and radical innovation[J]. Journal of marketing, 2005, 69(3):152-168.
[39] TELLIS G J. Disruptive technology or visionary leadership?[J]. Journal of product innovation management, 2006, 23(1):34-38.
[40] 杨国忠,陈佳.企业突破性技术创新行为研究——基于前景理论的演化博弈分析[J].工业技术经济,2020,39(5):57-64.
[41] MAO J, MA C, LIANG Z.Identifying emerging technology:a neural network based solution[EB/OL].[2020-03-23].https://vpinstitute.org/wp-content/uploads/2019/10/MTEGTM2019-Jin.pdf.
[42] 徐路路,王芳.基于支持向量机和改进粒子群算法的科学前沿预测模型研究[J].情报科学,2019,37(8):22-28.
[43] 刘博文,白如江,周彦廷,等.基金项目数据和论文数据融合视角下科学研究前沿主题识别——以碳纳米管领域为例[J].数据分析与知识发现,2019,3(8):114-122.
[44] 张丽华.研究前沿探测及演化分析方法与实证研究[D].北京:中国科学院大学,2015.
[45] 许海云,董坤,隗玲.学科交叉主题识别与预测研究[M].北京:科学技术文献出版社,2019:53-54.
[46] 罗瑞,许海云,董坤.领域前沿识别方法综述[J].图书情报工作,2018,62(23):119-131.
[47] 叶向东.关于科学不确定性的若干思考[J].全球科技经济瞭望,2008,23(2):32-34.
[48] 张华.论不完全信息条件下的片断情报分析法[J].情报理论与实践,2008(4):498-501.
[49] 莫乃兴.产品信息不对称下的市场信号[J].商场现代化,2007(13):38-39.
[50] HEIL O,ROBERTSON T S.Toward a theory of competitive market signaling:a research agenda[J].Strategic management journal,1991,12(6):403-418.
[51] DAY G S,SCHOEMAKER PAUL J H.Peripheral vision:detecting the weak signals that will make or break your company[M].Boston:Harvard Business School Press,2006:4-6.
[52] ANSOFF H I.Managing strategic surprise by response to weak signals[J].California management review,1975,18(2):21-33.
[53] ANSOFF H I,MCDONNELL E J.Implanting strategic management[M]. Upper Saddle River:Prentice Hall International Inc,1984.
[54] COFFMAN B.Weak signal research, part I:introduction[EB/OL].[2020-06-20].http://legacy.mgtaylor.com/mgtaylor/jotm/winter97/jotmwi97.htm.
[55] BROWN J S. Minding and mining the periphery[J]. Long range planning, 2004, 37(2):143-151.
[56] 赵小康.弱信号:识别、探测与应对[J].情报杂志,2010,29(1):159-163.
[57] 邓胜利,林艳青,王野.企业竞争弱信号的特征提取与定量识别研究[J].图书情报工作,2016,60(10):67-75.
[58] KUUSI O,HILTUNEN E,LINTURI H. Heikot tulevaisuussignaalit:Delfoi-tutkimus[J]. Futura, 2000(2):78-92.
[59] MOIJANEN M. Heikot signaalit tulevaisuudentutkimuksessa[J]. Futura,2003(4):38-60..
[60] PITKÄNEN R. Tulevaisuuden tutkimuksesta kilpailuetua-Opponentti[J]. Yritystalous, 2006:1-2.
[61] HILTUNEN E. The future sign and its three dimensions[J]. Futures, 2008, 40(3):247-260.
[62] LESCA H,LESCA N.Strategic decisions and weak signals[M].London:ISTE Ltd,2014:17.
[63] SCHOEMAKER P J H,DAY G S,SNYDER S A.Integrating organizational networks, weak signals, strategic radars and scenario planning[J].Technological forecasting & social change,2013,80(4):815-824.
[64] 单彬.认知视角下的弱信号分析及实证研究[D].北京:中国人民解放军军事医学科学院,2014.
[65] HILTUNEN E.Where do future-oriented people find weak signal?[M].Turku:Finland Futures Research Centre,2007.
[66] 党倩娜.新兴技术弱信号监测机制研究[M].上海:上海科学技术文献出版社,2018:26-27.
[67] ROSSEL P.Weak signals as a flexible framing space for enhanced management and decision-making[J].Technology analysis & strategic management,2009,21(3):307-320.
[68] PARK C, CHO S. Future sign detection in smart grids through text mining[J]. Energy procedia, 2017, 128:79-85.
[69] SAUL P.Seeing the future in weak signals[J].Journal of futures studies,2006,10(3):93-102.
[70] KUOSA T. Different approaches of pattern management and strategic intelligence[J].Technological forecasting & social change,2011,78(3):458-467.
[71] 董尹,刘千里,宋继伟,等.弱信号研究综述:概念、方法和工具[J].情报理论与实践,2018,41(10):147-154.
[72] DENG C, ZHANG S. The weak signal detection based on chaos and genetic algorithms[C]//2009 Second International Symposium on Information Science and Engineering. Washington:IEEE Computer Society, 2009:579-582.
[73] 国育家. 基于混沌理论的弱信号检测方法的研究[D].西安:西安科技大学,2017.
[74] WAGNER R,SCHOLZ S W,DECKER R.An internet-based approach to environmental scanning in marketing planning[J].Marketing intelligence & planning,2005,23(2):189-199.
[75] AMANATIDOU E,BUTTER M,CARABIAS V,et al.On concepts and methods in horizon scanning:lessons from initiating policy dialogues on emerging issue[J].Science & public policy,2012,39(2):208-221.
[76] KAUFMANN V, RAVALET E. From weak signals to mobility scenarios:a prospective study of france in 2050[J]. Transportation research procedia, 2016, 19:18-32.
[77] MEISSNER P, BRANDS C, WULF T. Quantifiying blind spots and weak signals in executive judgment:a structured integration of expert judgment into the scenario development process[J]. International journal of forecasting, 2017, 33(1):244-253.
[78] 郑圆圆,陈再良.模糊理论的应用与研究[J].苏州大学学报(工科版),2011,31(1):52-58.
[79] 董尹,刘千里.供应链风险识别中的弱信号介入、感知机制与观测方法研究[J].情报工程,2019,5(3):49-64.
[80] NOYONS E C M, RAAN A F J V. Monitoring scientific developments from a dynamic perspective:self-organized structuring to map neural network research[J]. Journal of the American Society for Information Science, 1998, 49(1):68-81.
[81] 赵松年. 突变理论:形成、发展与应用[J]. 世界科学, 1989(4):12-14.
[82] SCHEFFER M, BASCOMPTE J, BROCK W A, et al. Early-warning signals for critical transitions[J]. Nature, 2009, 461(7260):53-59.
[83] 吴浩, 侯威, 颜鹏程. 试用临界慢化原理探讨气候突变[J]. 物理学报, 2016(3):556-565.
[84] SCHEFFER M. Foreseeing tipping points[J]. Nature, 2010,467(7314):411-412.
[85] PERLA R J, CARIFIO J. The nature of scientific revolutions from the vantage point of chaos theory[J]. Science & education, 2005, 14(3/5):263-290.
[86] YOON J. Detecting weak signals for long-term business opportunities using text mining of Web news[J]. Expert systems with applications, 2012, 39(16):12543-12550.
[87] THORLEUCHTER D, VAN DEN POEL D. Weak signal identification with semantic web mining[J]. Expert systems with applications, 2013, 40(12):4978-4985.
[88] THORLEUCHTER D, VAN DEN POEL D. Idea mining for web-based weak signal detection[J]. Futures, 2015, 66(Feb.):25-34.
[89] KIM S, KIM Y E, BAE K J, et al. NEST:a quantitative model for detecting emerging trends using a global monitoring expert network and Bayesian network[J]. Futures, 2013, 52(Aug.):59-73.
[90] KIM J, LEE C. Novelty-focused weak signal detection in futuristic data:assessing the rarity and paradigm unrelatedness of signals[J]. Technological forecasting and social change, 2017, 120(Jul.):59-76.
[91] JOANNY G, PERANI S, EULAERTS O. Detection of disruptive technologies by automated identification of weak signals in technology development[C]//Proceedings of the International Conference on Scientometrics and Informetrics. Rome:INT SOC Scientometrics & Informetrics-ISSI,2019:2644-2645.
[92] GRANOVETTER M S. The strength of weak ties:a network theory revisited[J]. Sociological theory,1983,1(1):201-233.
[93] WEI L, XU H, WANG Z, et al. Topic detection based on weak tie analysis:a case study of LIS research[J]. Journal of data and information science, 2017, 1(4):81-101.
[94] JULIEN P A, ANDRIAMBELOSON E, RAMANGALAHY C. Networks, weak signals and technological innovations among SMEs in the land-based transportation equipment sector[J]. Entrepreneurship & regional development, 2004, 16(4):251-269.
[95] ZHAO J, WU J, XU K. Weak ties:subtle role of information diffusion in online social networks[J]. Physical review E, 2010, 82(1):016105.
[96] 刘俊婉,丁凯悦,王菲菲,等.科学合作的弱关系、强关系以及超级关系研究[J].科学学研究,2017,35(4):500-510,543.
[97] YOO S H, WON D K. Simulation of weak signals of nanotechnology innovation in complex system[J]. Sustainability, 2018, 10(2):486-499.
[98] 许海云,武华维,罗瑞,等.基于多元关系融合的科技文本主题识别方法研究[J].中国图书馆学报,2019,45(1):82-94.
[99] JENSEN S, LIU X, YU Y, et al. Generation of topic evolution trees from heterogeneous bibliographic networks[J]. Journal of informetrics, 2016, 10(2):606-621.
[100] ZHANG D, YIN J, ZHU X, et al. Metagraph2vec:complex semantic path augmented heterogeneous network embedding[C]//Pacific-Asia conference on knowledge discovery and data mining. Melbourne:Springer,2018:196-208.
[101] 刘彤, 杨冠灿, 侯元元. 基于多重关系整合的专利网络分析方法研究与应用[J]. 情报理论与实践, 2016, 39(2):59-63.
[102] SHI C, HU B, ZHAO X,et al.Heterogeneous information network embedding for recommendation[J].IEEE transactions on knowledge and data engineering,2019,31(2):357-370.
[103] 马蒙周. 基于多层网络的关键基因识别方法研究[D].西安:西安理工大学,2018.
[104] GAUVIN L, PANISSON A, CATTUTO C. Detecting the community structure and activity patterns of temporal networks:a non-negative tensor factorization approach[J]. PloS one, 2014, 9(1):e86028.
[105] 罗永恩, 胡继承, 徐茜. 基于超图的多模态关联特征处理方法[J]. 计算机工程, 2017,43(1):226-230.
[106] BENSON A R, GLEICH D F, LESKOVEC J. Higher-order organization of complex networks[J]. Science, 2016, 353(6295):163-166.
[107] XU J, WICKRAMARATHNE T L, CHAWLA N V. Representing higher-order dependencies in networks[J]. Science advances, 2016, 2(5):e1600028.
[108] LAMBIOTTE R, ROSVALL M, SCHOLTES I. From networks to optimal higher-order models of complex systems[J]. Nature physics, 2019, 15(4):313-320.
Options
文章导航

/

〈 〉