农业图书情报学报 ›› 2020, Vol. 32 ›› Issue (5): 55-64.doi: 10.13998/j.cnki.issn1002-1248.2019.12.06-1071

所属专题: 知识产权服务

• 研究论文 • 上一篇    下一篇

基于多元数据融合的专利竞争力分析——以东南5省高校为例

张锐, 郑美玉, 曾金晶*   

  1. 福建农林大学图书馆,福州 350002
  • 收稿日期:2019-12-06 出版日期:2020-05-05 发布日期:2020-05-20
  • 通讯作者: 曾金晶(1986-),女,博士研究生,馆员,研究方向:信息管理与知识产权。
  • 作者简介:张锐(1986-),女,硕士研究生,馆员,研究方向:科技查新与专利分析。郑美玉(1963-),女,本科,副研究馆员,研究方向:学科分析与专利分析。
  • 基金资助:
    福建省教育厅中青年教师教育科研项目“高校专利信息化的驱动机制及其模式研究”(项目编号:JAT170208); 2017年福建省中青年教师教育科研重点项目“FULink成员馆高校专利竞争力研究”(项目编号:JZ170291)

Patent Competitiveness Analysis Based on Multivariate Data Fusion—— Taking Universities in Five Southeast Provinces as an Example

ZHANG Rui, ZHENG Meiyu, ZENG Jinjing*   

  1. Library of Fujian Agricultural and Forestry University, Fuzhou 350002
  • Received:2019-12-06 Online:2020-05-05 Published:2020-05-20

摘要: [目的/意义]通过对高校专利数据进行全方位、科学性的分析,研究其专利竞争力水平的文献,不止对高校的科研能力有着具体的评判意义,对国家的科技发展也有一定的参考价值。[方法/过程]从专利数量、专利价值、维护能力、研发潜力4个维度展开,制定了14项专利数据融合的评价体系,并应用该评价体系对东南5省(广东、广西、福建、浙江、江苏)中具有代表性的25所高校进行了专利竞争力的分析评估。[结果/结论]根据该评价体系最终将专利竞争力分成3个梯队,第一梯队由浙江大学、东南大学、华南理工大学、中山大学、南京大学、苏州大学、浙江工业大学、暨南大学8所高校组成;第二梯队则由华南农业大学、厦门大学、南京理工大学、福州大学、华南师范大学、宁波大学、南京农业大学7所高校组成;其余的为第三梯队。高校专利竞争力排名与武书连榜排名并不完全一致,部分在武书连榜上排名靠后的高校,其专利竞争力反而高过排名在前的高校。高校专利竞争力受到高校的文理偏向的干扰,并不能完全与其综合实力挂钩,同时,专利竞争力还与高校所在地区的经济实力密切相关。广东江苏浙江地区高校的专利竞争力显著高于其他地区,但是,广东省高校在专利数量上略显不足,而江苏省高校在4个维度上均没有短板,浙江省高校专利数量虽多,但专利价值和维护能力尚有欠缺。

关键词: 专利竞争力, 高校, 东南

Abstract: [Purpose / Significance] Through the comprehensive and scientific analysis of the patent data of colleges and universities and the literature on the level of patent competitiveness. We will be in a better position to judge the research capability of colleges and universities, and in the meanwhile our analysis has a certain reference value for the development of science and technology of the country. [Method / Process] From the four dimensions of patent quantity, patent value, maintenance ability and R & D potential, a patent data fusion evaluation system of 14 indicators was established, and 25 representative universities in Southeast five provinces (Guangdong, Guangxi, Fujian, Zhejiang and Jiangsu) were analyzed and evaluated by using the evaluation system. [Results / Conclusions] According to the evaluation system, the patent competitiveness was divided into three echelons. The first echelon was composed of eight universities: Zhejiang University, Southeast University, South China University of Technology, Sun Yat-sen University, Nanjing University, Suzhou University, Zhejiang University of Technology and Jinan University. The second echelon was composed of South China Agricultural University, Xiamen University, Nanjing University of Technology, Fuzhou University and South China Normal University, Ningbo University and Nanjing Agricultural University; the rest are the third echelon. The ranking of patent competitiveness of colleges and universities is not completely consistent with that of Wushu list. Some lower-ranking colleges and universities on Wushu list have higher patent competitiveness than those higher-ranking ones. The patent competitiveness of colleges and universities is impacted by their cultural and scientific focus, and not completely related to their comprehensive strength. At the same time, the patent competitiveness is also closely related to the economic strength of the region where colleges and universities are located. For example, of colleges and universities in Jiangsu and Zhejiang are obviously more competitive in patent competitivenesss than those in other regions. However, colleges and universities in Guangdong have slightly insufficient patents patents, while colleges and universities in Jiangsu are not weak in four dimensions. Although colleges and universities in Zhejiang have a large number of patents, the value and maintenance capacity of their patents are still insufficient.

Key words: patent competitiveness, university, southeast

中图分类号: 

  • G306、G255.53

引用本文

张锐, 郑美玉, 曾金晶. 基于多元数据融合的专利竞争力分析——以东南5省高校为例[J]. 农业图书情报学报, 2020, 32(5): 55-64.

ZHANG Rui, ZHENG Meiyu, ZENG Jinjing. Patent Competitiveness Analysis Based on Multivariate Data Fusion—— Taking Universities in Five Southeast Provinces as an Example[J]. Journal of Library and Information Science in Agriculture, 2020, 32(5): 55-64.