Influence of Human Resources Agglomeration on Capability of Science and Technology Innovation

被引:0
|
作者
Chen Q. [1 ]
Yan T. [1 ]
Liu X. [1 ]
机构
[1] School of Economics and Management, Tongji University, Shanghai
来源
| 1722年 / Science Press卷 / 45期
关键词
Human resource agglomeration; Influencing factors; Innovation capability of science technology; Innovation of science technology;
D O I
10.11908/j.issn.0253-374x.2017.11.021
中图分类号
学科分类号
摘要
This paper draws on a theoretical model focusing on the relationship between the agglomeration of human resource and capability of science and technology innovation, by using hierarchical regressions analysis with provincial panel data from 2010 to 2014. The results indicate that agglomeration of human resources contract value of regional tech-market, the share of “211 project” universities and the share of high technology firms have all positive influence on science and technology innovation. Moreover, agglomeration of human resource has a totally mediating effect on the relationship between contract values of regional tech-market, the share of “211 project” universities and innovation capability of science technology; while also has a partially mediating effect on the relation between the share of high technology firms and innovation capability of science technology. © 2017, Editorial Department of Journal of Tongji University. All right reserved.
引用
收藏
页码:1722 / 1730
页数:8
相关论文
共 45 条
  • [21] Jiang L., Liang H., Liu Z., Correlation study on human resources in science and technology and regional economy in the Bohai rim area, China Soft Science, 5, (2010)
  • [22] Jin H., Jian L., China's regional innovation efficiency and its influencing factors considering the lag effect, Systems Engineering, 31, 9, (2013)
  • [23] Feng G., Liu J., Xu Z., Study on the factors on Chinese industries R&D efficiency, China Industrial Economics, 11, (2006)
  • [24] Wu Y., Evaluating technical efficiency and technical progress of knowledge production by using DEA, The Journal of Quantitative & Technical Economics, 25, 7, (2008)
  • [25] Xu X., Huang X., Liang P., Evaluating of science and technology innovation efficiency of a region based on DEA and malmquist exponent approach, Journal of Applied Statistics And Management, 28, 6, (2009)
  • [26] Yu Y., Innovation cluster governmrnt support and the technological innovation efficiency based on spatial econometrics of panel data with provincial data, Economic Review, 2, (2011)
  • [27] Wang S., Fan J., Zhao D., Et al., Regional innovation environment and innovation efficiency: The Chinese case, Technology Analysis & Strategic Management, 28, 4, (2016)
  • [28] Leydesdorff L., Meyer M., Triple Helix indicators of knowledge-based innovation systems: Introduction to the special issue, Research Policy, 35, 10, (2006)
  • [29] Carayannis E.G., Campbell D.F.J., Mode 3 knowledge production in quadruple helix innovation systems, 7, (2012)
  • [30] Benneworth P., Seven samurai opening up the ivory tower? The construction of Newcastle as an entrepreneurial university, European Planning Studies, 15, 4, (2005)