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Research on the evolution of the Chinese urban biomedicine innovation network pattern: An analysis using multispatial scales.
Ren, Zhimin; Yu, Jiaao; Qiu, Liping; Hong, Xuya; Wei, Shaobin; Zhou, Haiyan; Hu, Xiao; Zhang, Xiaolei; Zhang, Wei; Bathuure, Isaac Akpemah; Yang, Qican; Su, Ning; Lee, Wei; Wang, Xiaoping; Hu, Hao.
Afiliação
  • Ren Z; School of MBA, Zhejiang Gongshang University, Hangzhou, China.
  • Yu J; London College of Communication, University of the Arts London, London, United Kingdom.
  • Qiu L; Global Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
  • Hong X; Global Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
  • Wei S; Institute of Digital Economy and Green Development, Chifeng University, Chifeng, China.
  • Zhou H; Institute of Digital Economy and Green Development, Chifeng University, Chifeng, China.
  • Hu X; Cash Crop Workstation, Shangcheng Bureau of Agriculture and Rural Affairs, Xinyang, China.
  • Zhang X; School of Economics and Management, Chifeng University, Chifeng, China.
  • Zhang W; Academic Affairs Office, Xing'an Vocational and Technical College, Ulanhot, China.
  • Bathuure IA; Global Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
  • Yang Q; School of MBA, Zhejiang Gongshang University, Hangzhou, China.
  • Su N; School of MBA, Zhejiang Gongshang University, Hangzhou, China.
  • Lee W; School of Urban and Regional Science, East China Normal University, Shanghai, China.
  • Wang X; College of Business Administration, Ningbo University of Finance and Economics, Ningbo, China.
  • Hu H; School of Economics, Shanghai University, Shanghai, China.
Front Public Health ; 10: 1036586, 2022.
Article em En | MEDLINE | ID: mdl-36452959
This paper addresses the spatial pattern of urban biomedicine innovation networks by separately using four scales, i.e., the national scale, interregional scale, urban agglomeration scale, and provincial scale, on the basis of Chinese biomedicine patent data from the incoPat global patent database (GPD) (2001-2020) and using the method of social network analysis (SNA). Through the research, it is found that (1) on the national scale, the Chinese biomedicine innovation network becomes denser from west to the east as its complexity continuously increases. Its spatial structure takes the form of a radial network pattern with Beijing and Shanghai as its centers. The COVID-19 pandemic has not had an obvious negative impact on this network at present. (2) On the interregional scale, the strength of interregional network ties is greater than that of intraregional network ties. The eastern, central and western biomedicine innovation networks appear to be heterogeneous networks with regional central cities as the cores. (3) At the urban agglomeration scale, the strength of intraurban-agglomeration network ties is greater than that of interurban-agglomeration network ties. The three major urban agglomerations have formed radial spatial patterns with central cities as the hubs. (4) At the provincial scale, the intraprovincial networks have poor connectivity and low internal ties strength, which manifest as core-periphery structures with the provincial capitals as centers. Our research conclusion helps to clarify the current accumulation of technology and offer guidance for the development of China's biomedicine industry.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pandemias / COVID-19 Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Front Public Health Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pandemias / COVID-19 Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Front Public Health Ano de publicação: 2022 Tipo de documento: Article