Please wait a minute...
New Technology of Library and Information Service  2008, Vol. 24 Issue (6): 56-60    DOI: 10.11925/infotech.1003-3513.2008.06.11
Current Issue | Archive | Adv Search |
Application Research on Monitoring & Analysis in Hi-Tech Industry’s Technology Innovation
Zhang Cheng1  Zhu Donghua2  Xu Zhijun1
1(Zhuhai Branch of Guangdong Co., Ltd., China Mobile Group, Zhuhai 519015, China)
2(School of Management & Economics, Beijing Institute of Technology, Beijing 100081, China)
Export: BibTeX | EndNote (RIS)      

 According to the characteristics of the hi-tech industry, this paper researches on monitoring & analysis of technology innovation, sets up an index system of analysis. And it takes the carbon nanotubes industry as the research object to carry on the empirical research. The purpose is to understand the hi-tech industry’s technology innovation present condition and the future development directions, draw up the strategy to provide the decision reference for the government and business enterprise.

Key wordsHi-tech industry      Technology innovation      Monitoring &      analysis      Carbon nanotubes     
Received: 12 March 2008      Published: 25 June 2008


Corresponding Authors: Zhang Cheng     E-mail:
About author:: Zhang Cheng,Zhu Donghua,Xu Zhijun

Cite this article:

Zhang Cheng,Zhu Donghua,Xu Zhijun. Application Research on Monitoring & Analysis in Hi-Tech Industry’s Technology Innovation. New Technology of Library and Information Service, 2008, 24(6): 56-60.

URL:     OR

[1] 李维胜,秦长文.高技术企业发展的现状分析及对策建议[J].中国科技论坛,2005(4):70-73.
[2] 张德贤,陈中慧,戴桂林. 高新技术产业化协同过程探讨[J].中国管理科学,1997,5(4):47-51.
[3] Lee H,Deguchi H.Technological Innovation of High-tech Industry and Patent Policy - Agent Based Simulation with Double Loop Learning[C].  Proceeding of 4th Pacific Rim International Workshop on Multi-Agents, Intelligent Agents: Specification Modeling and Application, 2001:168-82.
[4] Ku  Y  L, Liau  S J, Hsing W C. The High-tech Milieu and Innovation-oriented Development[J].Technovation,2005,25(2):145-153.
[5] 穆荣平. 中国高新技术产业国际竞争力评价指标研究[J]. 中国科技论坛,2000(3):28-31.
[6] 赵兰香,吴灼亮. 中国高新技术产业竞争力分析[J].中国创业投资与高科技,2006(2):46-47.
[7] 朱东华, 袁军鹏. 基于数据挖掘的科技监测方法研究 [J]. 管理工程学报,2004(4):135-139.
[8] Zhu D, Porter A L. Automated Extraction and Visualization of Information for Technological Intelligence and Forecasting[J].Technological Forecasting & Social Change, 2002(69):495-506.
[9] 叶苏,顾新,杨早林,等. 国外高技术企业运用专利制度的策略及趋势研究[J]. 软科学,2005,19(4):84-87.
[10] 马晓光,沈全锋,于浩. 高技术领域急需专利保驾护航[J].科研管理,2002,23(5):20-25.
[11] 汤才祥. 透过中国专利文献分类信息看我国高新技术产业[J].电子知识产权,2003(6):11-15.
[12] 郭韬. 高新技术企业成长生命周期中的组织创新[J]. 工业技术经济,2005,24(7):72-76.
[13] 任智军,朱东华,荆雷. 基于可视化数据挖掘的管理科学科技文本分析研究[J]. 科学学与科学技术管理,2006(1):8-12.
[14] 余翔,蒋文光. 世界纳米专利比较分析和我国纳米专利战略研究[J].研究与发展管理,2004,16(4):85-90.
[15] 李亚青,贾杲,邢润川. 技术创新与纳米技术产业化问题[J]. 科学学研究,2000,18(1):83-90.

[1] Zhou Yang,Li Xuejun,Wang Donglei,Chen Fang,Peng Lijuan. Visualizing Knowledge Graph for Explosive Formula Design[J]. 数据分析与知识发现, 2021, 5(9): 42-53.
[2] Xu Yuemei, Wang Zihou, Wu Zixin. Predicting Stock Trends with CNN-BiLSTM Based Multi-Feature Integration Model[J]. 数据分析与知识发现, 2021, 5(7): 126-138.
[3] Zhu Hou,Fang Qingyan. Quantifying and Examining Privacy Paradox of Social Media Users[J]. 数据分析与知识发现, 2021, 5(7): 111-125.
[4] Zhong Jiawa,Liu Wei,Wang Sili,Yang Heng. Review of Methods and Applications of Text Sentiment Analysis[J]. 数据分析与知识发现, 2021, 5(6): 1-13.
[5] Gao Yilin,Min Chao. Comparing Technology Diffusion Structure of China and the U.S. to Countries Along the Belt and Road[J]. 数据分析与知识发现, 2021, 5(6): 80-92.
[6] Liu Tong,Liu Chen,Ni Weijian. A Semi-Supervised Sentiment Analysis Method for Chinese Based on Multi-Level Data Augmentation[J]. 数据分析与知识发现, 2021, 5(5): 51-58.
[7] Yi Huifang,Liu Xiwen. Analyzing Patent Technology Topics with IPC Context-Enhanced Context-LDA Model[J]. 数据分析与知识发现, 2021, 5(4): 25-36.
[8] Wang Yuzhu,Xie Jun,Chen Bo,Xu Xinying. Multi-modal Sentiment Analysis Based on Cross-modal Context-aware Attention[J]. 数据分析与知识发现, 2021, 5(4): 49-59.
[9] Li Feifei,Wu Fan,Wang Zhongqing. Sentiment Analysis with Reviewer Types and Generative Adversarial Network[J]. 数据分析与知识发现, 2021, 5(4): 72-79.
[10] Li Yueyan,Wang Hao,Deng Sanhong,Wang Wei. Research Trends of Information Retrieval——Case Study of SIGIR Conference Papers[J]. 数据分析与知识发现, 2021, 5(4): 13-24.
[11] Chen Jun,Liang Hao,Qian Chen. Studying Investment Decisions of Rewarded Crowdfunding Users with Emotional Distance and Text Analysis[J]. 数据分析与知识发现, 2021, 5(4): 60-71.
[12] Chang Chengyang,Wang Xiaodong,Zhang Shenglei. Polarity Analysis of Dynamic Political Sentiments from Tweets with Deep Learning Method[J]. 数据分析与知识发现, 2021, 5(3): 121-131.
[13] Zhang Mengyao, Zhu Guangli, Zhang Shunxiang, Zhang Biao. Grouping Microblog Users of Trending Topics Based on Sentiment Analysis[J]. 数据分析与知识发现, 2021, 5(2): 43-49.
[14] Li Xiao, Qu Jiansheng. Review of Application and Evolution of Meta-Analysis in Social Sciences[J]. 数据分析与知识发现, 2021, 5(11): 1-12.
[15] Wu Shengnan, Pu Hongjun, Tian Ruonan, Liang Wenqi, Yu Qi. Network Structure’s Impacts on Link Prediction Algorithm from Meta-Analysis Perspective[J]. 数据分析与知识发现, 2021, 5(11): 102-113.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938