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The Time Lags Effects of Innovation Input on Output in National Innovation Systems: The Case of China

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  • Dan Wang
  • Xinli Zhao
  • Zhenshan Zhang

Abstract

This paper investigates the time lags effects of innovation input on output in the national innovation systems (NIS). Firstly, we analyze the intrinsic properties of China’s NIS based on the conceptual framework and the causal loop diagram. Secondly, we construct a time lags distribution calculation model and employ the main innovation input indicators to measure the specific characteristics of time lags effects of innovation input on output for China in the period 2000–2012. The results indicate that there are considerable time lags in the four major feedback loops, and the distribution of time lags is various according to the characteristics of innovation input and influencing factors in the internal transformation. The trends of time lags from R&D personnel and industry-academia-research collaboration show steady growth, and the trends of time lags from R&D expenditure and government’s macro-control take inverted U-shaped pattern. Finally, we combine the estimation results of lags distribution calculation model with the analysis results of the causal loop diagram (including positive loops and negative loops) to provide some innovation policy suggestions. This study provides important implications for our understanding of the long-term complex lags effects of innovation input on output as well as for policy-makers designing and implementing the innovation strategies.

Suggested Citation

  • Dan Wang & Xinli Zhao & Zhenshan Zhang, 2016. "The Time Lags Effects of Innovation Input on Output in National Innovation Systems: The Case of China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-12, September.
    • Handle: RePEc:hin:jnddns:1963815
    DOI: 10.1155/2016/1963815
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    Cited by:

    1. Mohammed Ahmad S. Al-Shamsi, 2022. "Review of Korean Imitation and Innovation in the Last 60 Years," Sustainability, MDPI, vol. 14(6), pages 1-15, March.
    2. Inga Ivanova & Øivind Strand & Loet Leydesdorff, 2019. "An Eco-Systems Approach To Constructing Economic Complexity Measures: Endogenization Of The Technological Dimension Using Lotka–Volterra Equations," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-21, February.
    3. Xuan Wei & Wei Chen, 2019. "How Does A Firm’s Previous Social Network Position Affect Innovation? Evidence from Chinese Listed Companies," Sustainability, MDPI, vol. 11(4), pages 1-20, February.
    4. Shengli Dai & Weimin Zhang & Yingying Wang & Ge Wang, 2022. "Examining the Impact of Regional Development Policy on Industrial Structure Upgrading: Quasi-Experimental Evidence from China," IJERPH, MDPI, vol. 19(9), pages 1-18, April.

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