科研管理

科研管理 ›› 2018, Vol. 39 ›› Issue (12): 78-85.

• 论文 • 上一篇    下一篇

基于社会网络分析的区域创新关联网络研究

苏屹1, 2，韩敏睿1，雷家骕2   

  1. 1.哈尔滨工程大学经济管理学院，黑龙江 哈尔滨150001；
    2.清华大学经济管理学院，北京100084
  • 收稿日期:2018-01-09 修回日期:2018-04-23 出版日期:2018-12-20 发布日期:2018-12-21
  • 通讯作者: 苏屹
  • 基金资助:
    国家自然科学基金资助项目（71403066，2015-2017；71774036，2018-2021；71872057，2019-2022；71804084，2019-2022）；教育部人文社科青年项目（18YJC630245，2019-2021）；黑龙江省社会科学基金项目（17GLH21，2018-2019）；黑龙江省自然科学基金项目（QC2018088，2018-2020）。

An analysis of regional innovation correlation network in China based on social network analysis

Su Yi 1,2, Han Minrui1, Lei Jiasu2   

  1. 1. School of Economics and Management, Harbin Engineering University, Harbin 150001, Heilongjiang, China;
    2. School of Economics and Management, Tsinghua University, Beijing 100084, China
  • Received:2018-01-09 Revised:2018-04-23 Online:2018-12-20 Published:2018-12-21
  • Contact: Su Yi

摘要： 以我国29个省市2000年至2015年的发明专利授权数为样本，应用Eviews软件，在对样本数据进行平稳性检验及格兰杰因果关系检验的基础上，构建区域创新关联关系网络。论文采用社会网络分析的方法，并运用Ucinet软件，分析我国区域创新关联关系网络发展状况。实证研究表明：区域创新关联关系网络整体密度为0.1687，各子群密度仍有较大差异；第一、四子群的密度明显差异于第二、三子群的密度，且第四子群省市数量最多；区域创新关联关系网络内部的各省市创新关联关系分布不均，子群间的融合度也较差。

关键词: 格兰杰因果关系检验, 社会网络分析, Ucinet, 区域创新关联

Abstract: Taking the authorized number of invention patents of China's 29 provinces during 2000 to 2015 years as the sample data, this paper carries out stationarity test and Grainger causality test for sample data by using Eviews software. On this basis, it constructs regional innovation linkage network. This paper uses social network analysis method and Ucinet software to analyze the development of regional innovation linkage network in China.The empirical study shows that the overall density of regional innovation correlation network in China is 0.1687, and the density of each subgroup is still quite different. The density of the first, fourth subgroups is obviously different from the density of the second, third subgroups, and the number of the fourth subgroups and provinces is the most. The innovation related relationship among provinces in China's regional innovation linkage network is uneven, and the fusion degree between subgroups is also poor.

Key words: granger causality test, social network analysis, Ucinet, regional innovation correlation