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Diffusion of science-based inventions

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  • Hohberger, Jan

Abstract

Scientific knowledge is central to the development of inventions in high-technology industries. Therefore, understanding the influence of scientific knowledge on the diffusion of innovation processes is essential to understanding and predicting future invention patterns. For this reason, this paper investigates how science intensity and the scope of technological knowledge of inventions influences the propensity and speed of diffusion of inventions in a sample of >40,000 patents from the US semiconductor and biotechnology field. The results show that patents with intermediate levels of science intensity displayed the highest citation propensity; however, the fastest diffusion speed is found in patents with high levels of science intensity. In the case of the semiconductor industry inventions with low levels of science intensity have the highest citation propensity but the science intensity does not influence diffusion speed. In regard to technological knowledge scope of invention, inventions with intermediate levels of technological knowledge scope have the highest citation propensity in both industries. However, a significant difference in the diffusion speed based on the technological knowledge scope exists only in the biotechnology industry. Overall, the results present a more detailed picture of diffusion process and support the idea that the norms and incentives of the scientific community positively affect the diffusion speeds of science-based inventions.

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  • Hohberger, Jan, 2016. "Diffusion of science-based inventions," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 66-77.
    • Handle: RePEc:eee:tefoso:v:104:y:2016:i:c:p:66-77
    DOI: 10.1016/j.techfore.2015.11.019
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    1. > Economic Development Technological Change, and Growth > Innovation and Invention: Processes and Incentives

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    4. Hou, Jianhua & Tang, Shiqi & Zhang, Yang & Song, Haoyang, 2023. "Does prior knowledge affect patent technology diffusion? A semantic-based patent citation contribution analysis," Journal of Informetrics, Elsevier, vol. 17(2).

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