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The impact on Knowledge Transfer to Scientific and Technological Innovation Efficiency of Talents: analysis based on institutional environment in China.

Chen, S., Sun, J. and Liang, Y., 2022. The impact on Knowledge Transfer to Scientific and Technological Innovation Efficiency of Talents: analysis based on institutional environment in China. Technology Analysis and Strategic Management. (In Press)

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Official URL: https://www.tandfonline.com/journals/ctas20

DOI: 10.1080/09537325.2022.2093710

Abstract

Knowledge transfer is considered the efficient way to improve regional innovation, but relatively little is known about how the innovation efficiency of scientific and technological (S&T) talents is affected by knowledge transfers within institutional environment, particularly, limited studies carried out regional differentiation analysis. Using panel data from 30 provinces in China between 2005 to 2017, this article empirically tests the influence of institutional environment on knowledge transfer and analyses its impact between knowledge transfer and innovation efficiency of S&T talents in China. The results show knowledge transfer can significantly improve both the scientific and the economic innovation efficiency of S&T talents. Moreover, the effects of knowledge transfer on the innovation efficiency of S&T talents in eastern, central, western China had heterogeneity. Formal and informal institutions play mediating roles between knowledge transfer and innovation efficiency of S&T talents. This study contributes to the literature by constructing an econometric model with identified variables to test the impact of knowledge transfer on the innovation efficiency of S&T talents in China, in addition, the equation about knowledge transfer was explored. The research findings are valuable to regional governments and policy makers, our empirical evidence helps to develop more efficient strategy and policy planning.

Item Type:Article
ISSN:1465-3990
Uncontrolled Keywords:knowledge transfer; institutional environment; innovation efficiency; scientific and technological talents
Group:Bournemouth University Business School
ID Code:37088
Deposited By: Symplectic RT2
Deposited On:23 Jun 2022 10:04
Last Modified:23 Jun 2022 10:04

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