INFORMATION RESEARCH

Research on the Knowledge Feature Identification of Disruptive Technologies from Its Backward Scientific Citations: Taking the Field of Genetic Engineering as an Example

  • Ma Yaxue ,
  • Wang Jiajie ,
  • Ba Zhichao ,
  • Sun Jianjun
Expand
  • 1 Laboratory for Data Intelligence and Interdisciplinary Innovation, Nanjing University, Nanjing 210023;
    2 School of Information Management, Nanjing University, Nanjing 210023;
    3 Research Institute for Data Management Innovation, Nanjing University, Suzhou 215011

Received date: 2023-03-23

  Revised date: 2023-07-18

  Online published: 2024-01-16

Abstract

[Purpose/Significance] Disruptive technology plays an important supporting role in the political, economic, and social security of a country. Accurately identifying the features of disruptive technologies is of great significance for predicting the direction of technological innovation and optimizing the national innovation strategic layout. [Method/Process] This paper focuses on the ability of the knowledge features of patents’ scientific references (i.e., backward scientific citations) to foresee disruptive technologies. Firstly, the knowledge features of backward scientific citations are quantified from two aspects: the knowledge content of the cited scientific papers and the knowledge association between citing and cited literature. Then, the stepwise regression method is used to preliminarily identify the candidate features significantly related to the degree of patent innovation. Finally, machine learning methods and the Shapley additional explanations (SHAP) model are introduced to deeply analyze the correlation between the knowledge features of backward scientific citations and the degree of patent innovation, and thus identify the critical knowledge features of backward scientific citations that can predict disruptive technologies.[Result/Conclusion] The empirical analysis results in the field of genetic engineering indicate that, except for the novelty of cited papers’ knowledge combination, there is a significant nonlinear correlation between other knowledge features of scientific references and the degree of patent innovation. Within a certain threshold range, the knowledge features of disruptive technologies’ backward scientific citations may exhibit low knowledge impact and knowledge element diversity, high knowledge interdisciplinary, as well as long publication time interval and great knowledge correlation with citing patents.

Cite this article

Ma Yaxue , Wang Jiajie , Ba Zhichao , Sun Jianjun . Research on the Knowledge Feature Identification of Disruptive Technologies from Its Backward Scientific Citations: Taking the Field of Genetic Engineering as an Example[J]. Library and Information Service, 2024 , 68(1) : 116 -126 . DOI: 10.13266/j.issn.0252-3116.2024.01.010

References

[1] 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.)
[2] 窦超, 代涛, 李晓轩, 等. DARPA颠覆性技术创新机制研究——基于SNM理论的视角[J]. 科学学与科学技术管理, 2018, 39(6): 99-108. (DOU C, DAI T, LI X X, et al. Research on DARPA's disruptive technological innovation mechanism: based on the perspective of SNM theory [J]. Science of science and management of S.& T., 2018, 39(6): 99-108.)
[3] SCHOENMAKERS W, DUYSTERS G. The technological origins of radical inventions[J]. Research policy, 2010, 39(8): 1051-1059.
[4] 储节旺, 李佳轩, 安怡然. 基于专利分析的颠覆性技术演化与预测研究——以量子信息技术为例[J]. 科技进步与对策, 2023, 40(22): 130-140. (CHU J W, LI J X, AN Y R. The evolution and prediction of disruptive technologies based on patent analysis: an example of quantum information technology [J]. Science & technology progress and policy, 2023, 40(22): 130-140.)
[5] 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. Topic prediction for disruptive technologies based on patent literature: a case study of artificial intelligence patents [J]. Journal of the China Society for Scientific and Technical Information, 2022, 41(11): 1124-1133.)
[6] CARPENTER M P, NARIN F. Validation study: patent citations as indicators of science and foreign dependence[J]. World patent information, 1983, 5(3): 180-185.
[7] 李睿, 向姝璇, 黄靖芸.专利许可与专利引用的关联逻辑及其情报学应用[J]. 情报学报, 2021, 40(11): 1195-1208. (LI R, XIANG S X, HUANG J Y. Logical link between patent licensing and patent citation and its application from the perspective of information science [J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(11): 1195-1208.)
[8] AGUIRRE-URRETA M I, RONKKO M, HU J. Polynomial regression and measurement error: implications for information systems research[J]. Data base for advances in information systems, 2020, 51(3): 55-80.
[9] FRIEDRICH A B, MASON J, MALONE J R. Rethinking explain ability: toward a post phenomenology of black-box artificial intelligence in medicine[J]. Ethics and information technology, 2022, 24(1): 1-9.
[10] 石慧, 潘云涛, 苏成. 颠覆性技术及其识别预测方法研究综述[J]. 情报工程, 2019, 5(3): 33-48. (SHI H, PAN Y T, SU C. A review of research on disruptive technology and its recognition and prediction methods [J]. Technology intelligence engineering, 2019, 5(3): 33-48.)
[11] MUSHTAQ M, AHMAD DAR A, SKALICKY M, et al. Crispr-based genome editing tools: insights into technological breakthroughs and future challenges[J]. Genes, 2021, 12(6): 797.
[12] 章德宾, 罗瑶, 陈文进. 基因编辑技术发展现状[J]. 生物工程学报, 2020, 36(11): 2345-2356. (ZHANG D B, LUO Y, CHEN W J. Current development of gene editing [J] Chinese journal of biotechnology, 2020, 36(11): 2345-2356.)
[13] 刘柳, 吴新年. 颠覆性技术识别方法研究进展述评[J]. 数字图书馆论坛, 2022(1): 2-9. (LIU L, WU X N. Review on the research progress of disruptive technology identification methods [J]. Digital library forum, 2022(1): 2-9.)
[14] 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.)
[15] 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.)
[16] 刘小玲, 谭宗颖, 张超星. 国内外“科学-技术关系”研究方法述评——聚焦文献计量方法[J]. 图书情报工作, 2015, 59(13): 142-148. (LIU X L, TAN Z Y, ZHANG C X. Research review of “science-technology relationship” research methods: highlights on bibliometrics method [J] Library and information service, 2015, 59(13): 142-148.)
[17] PEZZONI M, VEUGELERS R, VISENTIN F. How fast is this novel technology going to be a hit? antecedents predicting follow-on inventions[J]. Research policy, 2022, 51(3): 104454.
[18] 张金柱, 张晓林. 利用引用科学知识突变识别突破性创新[J]. 情报学报, 2014, 33(3): 259-266. (ZHANG J Z, ZHANG X L. Identification of radical innovation based on mutation of cited scientific knowledge [J]. Journal of the China Society for Scientific and Technical Information, 2014, 33(3): 259-266.)
[19] PAAP J, KATZ R. Anticipating disruptive innovation[J]. Research-technology management, 2004, 47(5): 13-22.
[20] GOVINDARAJAN V, KOPALLE P K. Disruptiveness of innovations: measurement and an assessment of reliability and validity[J]. Strategic management journal, 2006, 27(2): 189-199.
[21] 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 & social change, 2009, 76(8): 1044-1054.
[22] KIM J, PARK Y, LEE Y. A visual scanning of potential disruptive signals for technology roadmapping: investigating keyword cluster, intensity, and relationship in futuristic data[J]. Technological analysis & strategic management, 2016, 28(10): 1225-1246.
[23] SOMMARBERG M, MAKINEN S J. A method for anticipating the disruptive nature of digitalization in the machine-building industry[J]. Technological forecasting and social change, 2019, 146: 808-819.
[24] GUO J F, PAN J F, GUO J X, et al. Measurement framework for assessing disruptive innovations[J]. Technological forecasting and social change, 2019, 139: 250-265.
[25] 周波, 冷伏海. 技术识别研究进展[J]. 情报学进展, 2022, 14(1): 315-348. (ZHOU B, LENG F H. The research progress of technology identification [J]. Advances in information science, 2022, 14(1): 315-348.)
[26] 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.)
[27] ZHOU X, HUANG L, PORTER A, et al. Tracing the system transformations and innovation pathways of an emerging technology: solid lipid nanoparticles[J]. Technological forecasting and social change, 2019, 146: 785-794.
[28] 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. Research review on disruptive technology identification method [J]. Library and information service, 2020, 64(17): 145-152.)
[29] JIA W, XIE Y, ZHAO Y, 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.
[30] 白光祖, 郑玉荣, 吴新年, 等. 基于文献知识关联的颠覆性技术预见方法研究与实证[J]. 情报杂志, 2017, 36(9): 38-44. (BAI G Z, ZHENG Y R, WU X N, et al. Research and demonstration on forecasting method of disruptive technology based on literature knowledge correlation [J]. Journal of intelligence, 2017, 36(9): 38-44.)
[31] 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.
[32] 李睿, 青杨媚, 范九江. 基于专利引用跨越度计量的两国间间接创新合作机会发现[J]. 图书情报工作, 2020, 64(23): 31-39. (LI R, QING Y M, FAN J J. To discover the indirect innovation cooperation opportunities between two countries based on their patent citation crossing degree [J]. Library and information service, 2020, 64(23): 31-39.)
[33] KWON S, YOUTIE J, PORTER A L. Interdisciplinary knowledge combinations and emerging technological topics: implications for reducing uncertainties in research evaluation[J]. Research evaluation, 2021, 30(1): 127-140.
[34] 王萍萍, 王毅. 技术新颖性从何而来?——基于纳米技术专利的分析[J]. 管理工程学报, 2020, 34(6): 79-89. (WANG P P, WANG Y. Identifying the sources of technological novelty: empirical analysis based on nanotechnology patents [J]. Journal of industrial engineering and engineering management, 2020, 34(6): 79-89.)
[35] BORNMANN L, ANEGON F D, LEYDESDORFF L. Do scientific advancements lean on the shoulders of giants? A bibliometric investigation of the Ortega hypothesis[J]. Plos one, 2010, 5(10): e13327.
[36] 孙建军, 裴雷, 马亚雪, 等. 数据驱动下智库话语逻辑及互证体系思考[J]. 中国科学院院刊, 2022, 37(2): 153-159. (SUN J J, PEI L, MA Y X, et al. Thoughts on data-driven discursive logic and triangulation of think tank [J]. Bulletin of Chinese Academy of Sciences, 2022, 37(2): 153-159.)
[37] SAVOV P, JATOWT A, NIELEK R. Identifying breakthrough scientific papers[J]. Information processing & management, 2020, 57(2): 102168.
[38] FUNK R J, OWEN-SMITH J. A dynamic network measure of technological change[J]. Management science, 2017, 63(3): 791-817.
[39] PORTER A, COHEN A, DAVID ROESSNER J, et al. Measuring researcher interdisciplinarity[J]. Scientometrics, 2007, 72(1): 117-147.
[40] 赵明珍, 林鸿飞, 徐博, 等. 面向社交网络的潜在药物不良反应发现[J]. 中文信息学报, 2017, 31(5): 194-202. (ZHAO M Z, LIN H F, XU B, et al. Potential adverse drug reactions discovery from social networks [J]. Journal of Chinese information processing, 2017, 31(5): 194-202.)
[41] LIU M, BU Y, CHEN C, et al. Pandemics are catalysts of scientific novelty: evidence from COVID‐19[J]. Journal of the Association for Information Science and Technology, 2021, 73(8): 1065-1078.
[42] MORAL-MUNOZ J A, LUCENA-ANTÓN D, PEREZ-CABEZAS V, et al. Highly cited papers in microbiology: identification and conceptual analysis[J]. FEMS microbiology letters, 2018, 365(20): fny230.
[43] 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.
[44] 张光进, 张士菊. 知识传承与增长视角的行政学研究进路——一项多学科比较研究[J]. 华中科技大学学报(社会科学版), 2016, 30(4): 61-71. (ZHANG G J, ZHANG S J. The forwarding route of public administration researches improvement from the view of knowledge inheritance and knowledge growth: a comparison study between different disciplines [J]. Journal of Huazhong University of Science and Technology (social science edition), 2016, 30(4): 61-71.)
[45] CHEN L. Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations[J]. Journal of informetrics, 2017, 11(1): 63-79.
[46] JIN L, HUANG X Y, SHI X M. A study on influence of predictor multicollinearity on performance of the stepwise regression prediction equation[J]. Acta meteorologica sinica, 2010, 24(5): 593-601.
[47] 陈成梦, 黄永春, 吴商硕, 等. 基于XGBoost算法的机会型创业预测研究[J]. 科技进步与对策, 2023, 40(5): 14-22. (CHEN C M, HUANG Y C, WU S S, et al. The prediction of opportunity-driven entrepreneurship based on XGBoost algorithm [J]. Science & technology progress and policy, 2023, 40(5): 14-22.)
[48] PRAIRIE Y T. Evaluating the predictive power of regression models[J]. Canadian journal of fisheries and aquatic sciences, 1996, 53(3): 490-492.
[49] MENG Y, YANG N, QIAN Z, et al. What makes an online review more helpful: an interpretation framework using XGBoost and SHAP values[J]. Journal of theoretical and applied electronic commerce research, 2021, 16(3): 466-490.
[50] 曹晓辉, 段异兵. 基因工程专利维持特征及影响因素分析[J]. 科研管理, 2012, 33(2): 26-32. (CAO X H, DUAN Y B. Genetic engineering patent renewal characters and their influencing factors [J]. Science research management, 2012, 33(2): 26-32.)
[51] PATIL S J, BHALKE S L, DESHPANDE N. A state of the art in genetic improvement of asparagus plants: patent based perspective[J]. Journal of commercial biotechnology, 2019, 25(1): 8-24.
[52] 陈茜, 毛进, 马亚雪, 等. 创新型企业的论文与专利关联性研究——以基因工程领域为例[J]. 科学学研究, 2023, 41(3): 565-576. (CHEN Q, MAO J, MA Y X, et al. Research on the linkage between papers and patents in innovation-oriented enterprises: take the field of genetic engineering [J]. Studies in science of science, 2023, 41(3): 565-576.)
[53] WU L, WANG D, EVANS J A. Large teams develop and small teams disrupt science and technology[J]. Nature, 2019, 566(7744): 378-382.
[54] MARX M, FUEGI A. Reliance on science: worldwide front-page patent citations to scientific articles[J]. Strategic management journal, 2020, 41(9): 1572-1594.
[55] MARX M, FUEGI A. Reliance on science by inventors: hybrid extraction of in-text patent-to-article citations[J]. Journal of economics & management strategy, 2022, 31(2): 369-392.
[56] TEO A C, TAN G W H, OOI K B, et al. The effects of convenience and speed in m-payment[J]. Industrial management & data systems, 2015, 115(2): 311-331.
Outlines

/

〈 〉