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Examining the evolving structures of intercity knowledge networks: The case of scientific collaboration in China

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dc.contributor.author Dai, Liang
dc.contributor.author Derudder, Ben
dc.contributor.author Cao, Zhan
dc.contributor.author Ji, Yufan
dc.date.accessioned 2024-02-28T19:40:15Z
dc.date.available 2024-02-28T19:40:15Z
dc.date.issued 2023
dc.identifier.citation International Journal of Urban Sciences, vol. 27(3), 2023, pp. 371-389.
dc.identifier.other https://doi.org/10.1080/12265934.2022.2042365
dc.identifier.uri http://repozytorium.umk.pl/handle/item/6994
dc.description.abstract Drawing on data on scientific co-publications derived from the Web of Science for the periods 2002–2006 and 2012–2016, we construct and analyse a key element of China’s intercity knowledge networks (CIKNs): scientific collaboration networks. Employing networkanalytical and exponential random graph modelling techniques, we examine the evolving structures and driving mechanisms underlying these CIKNs. Our results show that the density of the CIKNs has significantly increased over time. CIKN flows are dense in the Southeastern but sparse in the Northwestern part of China, with the Hu Line acting as a clearly visible border. As the dominant knowledge centre, Beijing is involved in scientific collaboration networks throughout the country, with the diamond-shaped structure anchored by Beijing-Shanghai- Guangzhou-Chengdu becoming evident. We find that preferential attachment and transitivity are significant endogenous processes driving scientific collaboration, while a city’s administrative level and R&D investment are the strongest exogenous factors. The impact of GDP and geographical proximity is limited, with institutional proximity being the most sizable of the well-known suite of proximity effects.
dc.description.sponsorship The research presented in this paper was financially supported through research project number 2020/38/A/HS4/00312 of the Polish National Science Centre (NCN).
dc.language.iso eng
dc.rights Attribution 4.0 Poland
dc.rights.uri https://creativecommons.org/licenses/by/4.0/deed.pl
dc.subject Intercity knowledge network
dc.subject scientific collaboration
dc.subject social network analysis
dc.subject exponential random graph model
dc.subject China
dc.title Examining the evolving structures of intercity knowledge networks: The case of scientific collaboration in China
dc.type info:eu-repo/semantics/article


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Attribution 4.0 Poland Ta pozycja jest udostępniona na licencji Attribution 4.0 Poland