TY - JOUR
T1 - Geography of transnational knowledge flows from China
T2 - Distance, Pipelines and Hierarchy?
AU - Zhang, Jiaqian
AU - Si, Yuefang
AU - Yu, Jianhui
N1 - Publisher Copyright:
© 2025 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2025/6
Y1 - 2025/6
N2 - With the rise of China’s innovation capacity and position in the global innovation system, an increasing number of scholars are paying attention to the knowledge diffusion from developed economies to China. However, there is less research looking into the destinations of transnational knowledge diffusion from China and their influencing factors from the dynamic perspective. This study uses USPTO data for the period 2003–2022 to illustrate the spatial pattern of Chinese transnational knowledge diffusion and estimates the impact of geographical distance, knowledge pipelines, and hierarchy in the global innovation system. We find that the global innovation system has been comparatively stable, but that China has successfully transitioned from the periphery to being a semi-peripheral and then a core country. The knowledge transfer from China occurred firstly to core and semi-peripheral countries, as the reversed knowledge flow, and then to developing countries along the “Belt and Road” initiative with an increasingly important role in “South-South Cooperation”. Regarding its influencing factors, geographical distance is significant across all periods, highlighting that distance remains an indispensable factor in innovation and knowledge flow. Knowledge pipelines and hierarchy in the global innovation system are conditionally influential. Knowledge pipelines were only significantly positive when China was a semi-peripheral country. Compared with the periphery, the knowledge flow from China increasingly tended towards semi-peripheral countries during its catching-up process, but the knowledge could be accepted by the core countries only during the time when China was a semi-peripheral country. Our research unpacks the complexity of pipelines and hierarchy as influencing factors from the dynamic perspective.
AB - With the rise of China’s innovation capacity and position in the global innovation system, an increasing number of scholars are paying attention to the knowledge diffusion from developed economies to China. However, there is less research looking into the destinations of transnational knowledge diffusion from China and their influencing factors from the dynamic perspective. This study uses USPTO data for the period 2003–2022 to illustrate the spatial pattern of Chinese transnational knowledge diffusion and estimates the impact of geographical distance, knowledge pipelines, and hierarchy in the global innovation system. We find that the global innovation system has been comparatively stable, but that China has successfully transitioned from the periphery to being a semi-peripheral and then a core country. The knowledge transfer from China occurred firstly to core and semi-peripheral countries, as the reversed knowledge flow, and then to developing countries along the “Belt and Road” initiative with an increasingly important role in “South-South Cooperation”. Regarding its influencing factors, geographical distance is significant across all periods, highlighting that distance remains an indispensable factor in innovation and knowledge flow. Knowledge pipelines and hierarchy in the global innovation system are conditionally influential. Knowledge pipelines were only significantly positive when China was a semi-peripheral country. Compared with the periphery, the knowledge flow from China increasingly tended towards semi-peripheral countries during its catching-up process, but the knowledge could be accepted by the core countries only during the time when China was a semi-peripheral country. Our research unpacks the complexity of pipelines and hierarchy as influencing factors from the dynamic perspective.
UR - https://www.scopus.com/pages/publications/105008956739
U2 - 10.1371/journal.pone.0326503
DO - 10.1371/journal.pone.0326503
M3 - 文章
C2 - 40540461
AN - SCOPUS:105008956739
SN - 1932-6203
VL - 20
JO - PLoS ONE
JF - PLoS ONE
IS - 6 June
M1 - e0326503
ER -