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Capturing information on global knowledge flows from patent transfers: An empirical study using USPTO patents

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  • Liu, Weiwei
  • Tao, Yuan
  • Bi, Kexin

Abstract

In the global open innovation environment, one of the main characteristics of the knowledge-based economy is to pay more attention to the importance of global knowledge flows. This paper investigates global knowledge flows from the perspective of patent transfers, which can not only reflect the patents' economic value but also explore explicit and tacit knowledge flows comprehensively. This paper begins with the premise that global knowledge flows include the internal absorption of knowledge (IAK), knowledge outflows (KOFs) and knowledge inflows (KIFs) based on a dataset derived from United States Patent and Trademark Office (USPTO) during 2002 and 2016. Then, a global knowledge flow network is constructed by integrating patent transfer analysis and social network analysis. Our results show that more and more inventors and assignees are involved in the global knowledge flow network, China and India's ranking in the list of knowledge creators and users rises rapidly, cross-border knowledge flows will become a new trend; the rapid development of G06F (electric digital data processing), H04L (transmission of digital information) and other technological fields has accelerated the global knowledge flows; at present, the United States is the largest net knowledge inflow participant, the United Kingdom is the largest net knowledge outflow participant; the characteristics of a small-world effect in the cross-border knowledge flow network composed of 35 major participants become increasingly obvious. Our findings have clear policy implications. Establishing a global knowledge flow network is needed in order to promote global knowledge transfers, absorption and sharing.

Suggested Citation

  • Liu, Weiwei & Tao, Yuan & Bi, Kexin, 2022. "Capturing information on global knowledge flows from patent transfers: An empirical study using USPTO patents," Research Policy, Elsevier, vol. 51(5).
  • Handle: RePEc:eee:respol:v:51:y:2022:i:5:s0048733322000373
    DOI: 10.1016/j.respol.2022.104509
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