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Does Intelligence Improve the Efficiency of Technological Innovation?

Author

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  • Xing Zhao

    (Nanjing Normal University)

  • Sasa Yang

    (Xiamen University)

Abstract

Despite the rapid advancement of intelligent process, few studies investigate the impact of intelligence on the efficiency of technological innovation, and none focus on examining the mechanism underlying this impact or investigating whether this effect exhibits heterogeneity. Accordingly, this paper uses panel data from 30 regions in China from 2005 to 2016 to test the impact of intelligence on technological innovation efficiency and the mechanism underlying this impact. The paper further investigates the heterogeneity of this impact given different levels of government attention, different levels of R&D intensity, and different geographical locations. The results show that first, on the whole, intelligence can significantly improve the efficiency of regional technological innovation. This conclusion remains valid after robustness testing and instrumental variable regression. Second, the results concerning the mechanism by which intelligence impacts the efficiency of technological innovation show that intelligence improves the efficiency of regional technological innovation through human capital accumulation, knowledge spillover, and optimization of the allocation of innovation factors. Third, further analysis shows that the beneficial effect of intelligence on regional technological innovation efficiency is obviously heterogeneous. In areas featuring high levels of government attention, R&D intensity, and geographical advantages, the beneficial effect of intelligence on technological innovation efficiency is more obvious.

Suggested Citation

  • Xing Zhao & Sasa Yang, 2023. "Does Intelligence Improve the Efficiency of Technological Innovation?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 3671-3695, December.
    • Handle: RePEc:spr:jknowl:v:14:y:2023:i:4:d:10.1007_s13132-022-01011-z
    DOI: 10.1007/s13132-022-01011-z
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