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PDF(396 KB)
PDF(396 KB)
大数据分析方法在战略性新兴产业技术预见中的应用
Application of Big Data Analysis Methods for Technology Foresight in Strategic Emerging Industries
作为创新战略管理工具，技术预见受到越来越多的重视。学术界对技术预见方法及其应用进行了大量的相关研究，但是对不同路径的新兴产业进行技术预见，尤其针对发展中国家的追赶型产业创新进行技术预见，仍是亟待深入探讨的理论难题。另外，大多数技术预见仍然以德尔菲法专家分析法为主，其制定过程主要还是依赖专家的知识经验，而缺乏客观的大数据支撑，在分析研究上往往偏向主观而缺乏信度和效度。本文将探索专利、文献等大数据应用于支撑我国新兴产业技术预见的理论和方法研究。
As an innovative strategic management tool, technology foresight has received increasing interest. There is a large number of related scholarship on technology foresight and its application. The theoretical difficulty is how to conduct technology foresight for different kinds of emerging industries, especially for targeted types of industry innovation in a developing country. Delphi expert analysis is currently the most popular method for technology foresight. This method is undermined by a lack of reliabe and valid big data to support expert experience. The authors propose a new method for patent and technical document analysis for the use of technology foresight for China’s emerging industries.
技术预见 / 文献计量 / 专利分析 / 大数据分析 / 新兴产业
technology foresight / bibliometric / patent analysis / big data analysis / emerging industry
| [1] |
Miles I. The development of technology foresight: A review [J]. Technological Forecasting and Social Change, 2010, 77(9): 1448–1456.
|
| [2] |
Blind K, Cuhls K, Grupp H. Current foresight activities in Central Europe [J]. Technological Forecasting and Social Change, 1999, 60(1): 15–35.
|
| [3] |
Georghiou L. The UK technology foresight programme [J]. Futures, 1996, 28(4): 359–377.
|
| [4] |
MartinB R, Johnston R. Technology foresight for wiring up the national innovation system: experiences in Britain, Australia, and New Zealand [J]. Technological Forecasting and Social Change, 1999, 60(1): 37–54.
|
| [5] |
Kuwahara T. Technology forecasting activities in Japan [J]. Technological Forecasting and Social Change, 1999, 60(1): 5–14.
|
| [6] |
Lee S K, Mogi G, Kim J W. Energy technology roadmap for the 表 2 论文分析指标计量指标 计算方法 指标说明，表征的意义分区刊均论文数量分别统计 ABCD 四个分区（论文数量 / 该分区的期刊数）反映了该技术点不同研究水平的论文数量，从而可以了解该技术点学术研究活动水平论文综合 指标分区刊均论文数量 × 该分区的刊均影响因子反映了该技术点学术研究活动水平。指标越高，说明该技术点的学术研究水平越高文献增长率R =Pa(n) − Pa(n − 1)Pa(n − 1)(Pa(n) 表示第 n 年的文献发表数量 )文献增长率反映了技术创新能力的变化程度。指标越高，说明该技术的创新能力增强越多篇均引用量 论文被引用的总次数 / 论文总数 理论上讲，被引次数是衡量学术论文影响力和质量的标尺。指标越高，反映了该技术点越强的重要性和地位127中国工程科学 2016 年 第 18 卷 第 4 期next 10 years: The case of Korea [J]. Energy Policy, 2009, 37(2): 588–596.
|
| [7] |
Choi M, Choi H L, Yang H Y, et al. Characteristics of 4th Korean technology foresight[C]//Institute of Electrical and Electronics Engineers. 2012 Proceedings of PICMET’12: Technology management for emerging technologies (PICMET) July29-Aug 2, 2012, Vancouver, BC. New York: IEEE, 2012: 1330–1354.
|
| [8] |
郭卫东. 技术预见理论方法及关键技术创新模式研究[D]. 北京: 北京邮电大学, 2007.
|
| [9] |
薛澜, 周源, 李应博, 等. 战略性新兴产业创新规律与产业政策研究( 白皮书)[M]. 北京: 科学出版社, 2015.
|
| [10] |
Lee S, Seol H. Using patent information for designing new product and technology: Keyword based technology roadmapping [J]. R&D Management, 2008, 38(2): 169–188.
|
| [11] |
Phaal R, O’Sullivan E, Routley M, et al. A framework for mapping industrial emergence [J]. Technological Forecasting and Social Change, 2011, 78(2): 217–230.
|
| [12] |
Daim T U, Rueda G, Martin H, et al. Forecasting emerging technologies: Use of bibliometrics and patent analysis [J]. Technological Forecasting and Social Change, 2006, 73(8): 981–1012.
|
| [13] |
李欣, 黄鲁成. 基于文献计量的染料敏化太阳能光伏技术可视化分析[J]. 情报杂志, 2013, 32(12): 98–103.
|
| [14] |
Jun S, Lee S J. Emerging technology forecasting using new patent information analysis [J]. International Journal of Software Engineering and Its Applications, 2012, 6(3): 107–114.
|
| [15] |
Kim Y G, Suh J H, Park S C. Visualization of patent analysis for emerging technology [J]. Expert Systems with Applications, 2008, 34(3): 1804–1812.
|
| [16] |
张嶷, 汪雪峰, 郭颖, 等. 基于文献计量学方法的技术路线图构建模型研究[J]. 科学学研究, 2012, 30(4): 495–502.
|
| [17] |
郭颖, 汪雪峰, 朱东华, 等. “ 自顶向下” 的科技规划—基于专利数据和技术路线图的新方法[J]. 科学学研究 , 2012, 30(3): 349–358.
|
| [18] |
Robinson D K R, Huang L, Guo Y, et al. Forecasting innovation pathways (FIP) for new and emerging science and technologies [J]. Technological Forecasting and Social Change, 2013, 80(2): 267–285.
|
| [19] |
李欣, 黄鲁成. 基于技术路线图的新兴产业形成路径研究[J]. 科技进步与对策, 2014, 31(1): 44–49.
|
| [20] |
Li X, Zhou Y, Xue L, et al. Integrating bibliometrics and roadmapping methods: A case of dye-sensitized solar cell technology-based industry in China [J]. Technological Forecasting and Social Change, 2015, 97: 205–222.
|
| [21] |
乔杨. 专利计量方法在技术预见中的应用—— 以国内冶金领域为例[J]. 情报杂志, 2013, 32(4): 34–37.
|
| [22] |
王金鹏. 基于科学计量的技术预见方法优化研究(硕士学位论文) [D]. 武汉: 华中师范大学, 2011.
|
| [23] |
崔志明, 万劲波, 浦根祥, 等. 技术预见与国家关键技术选择应遵循的基本原则[J]. 科学学与科学技术管理, 2002, 23(12): 9–12.
|
| [24] |
王旭超, 吴腾枫, 江小蓉, 等. 面向技术预测的专利情报分析实证研究[J]. 情报科学, 2014, 32(7): 139–144.
|
| [25] |
穆荣平, 任中保, 袁思达, 等. 中国未来20 年技术预见德尔菲调查方法研究[J]. 科研管理, 2006, 27(1): 1–7.
|
| [26] |
孙静芬, 袁建华, 赵滟, 等. 国外航天未来发展技术预见实施研究[J]. 中国航天, 2015(10): 37–41.
|
| [27] |
Zhang Y, Zhang G Q, Chen H S, et al. Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research [J].
|
| [28] |
Wang X F, Qiu P J, Zhu D H, et al. Identification of technology development trends based on subject–action–object analysis: The case of dye-sensitized solar cells [J]. Technological Forecasting and Social Change, 2015, 98: 24–46.
|
| [29] |
Nassirtoussi A K, Aghabozorgi S, Wah T Y, et al. Text mining of news-headlines for FOREX market prediction: A Multi-layer dimension reduction algorithm with semantics and sentiment[J]. Expert Systems with Applications, 2015, 42(1): 306–324.
|
| [30] |
Keppell M. Principles at the heart of an instructional designer: Subject matter expert interaction [C]// Sims R, O’ Reilley M, Sawkins S, et al. Learning to choose—Choosing to learn. Proceedings of the 17th Annual Conference of the Australasion Society for Computers in Learning in Tertiary Education, 2000, Coffs Harbour, NSW. Australia: ASCILITE, 2000: 317–326.
|
| [31] |
Quiamzade A, Mugny G, Cléopas A D, et al. Interaction styles and expert social influence [J]. European Journal of Psychology of Education, 2003, 18(4): 389–404.
|
| [32] |
Lee M F, Mehlenbacher B. Technical writer/subject-matter expert interaction: The writer’s perspective, the organizational challenge [J]. Technical Communication, 2000, 47(4): 544–552.
|
| [33] |
Kenny P G, Parsons T D, Gratch J, et al. Evaluation of novice and expert interpersonal interaction skills with a virtual patient [J]. Lecture Notes in Computer Science, 2009, 5773: 511–512.
|
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