4.4 Article

Knowledge innovation network externalities in the Guangdong-Hong Kong-Macao Greater Bay Area: borrowing size or agglomeration shadow?

Journal

TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT
Volume 34, Issue 9, Pages 1020-1037

Publisher

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/09537325.2021.1940922

Keywords

Knowledge innovation; network externalities; agglomeration shadow

Funding

  1. National Science Foundation of China (NSFC) [42071154]
  2. Ministry of Education Humanities and Social Sciences Planning Fund [20YJA790010]
  3. Natural Science Foundation of Shanghai [21ZR1421100]

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Analysis of the knowledge innovation network in the Guangdong-Hong Kong-Macao Greater Bay Area reveals that Guangzhou and Hong Kong have always been the cores, with Shenzhen emerging as an innovation center after 2012 and other cities becoming peripheral areas. Small- and medium-sized cities do not benefit from the innovative development of core cities, with institutional and cultural differences posing major obstacles.
The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most active innovation areas in China, but the complex institutional and cultural environment makes innovation cooperation among the cities challenging. Based on 2001-2019 data, this study analyses the spatial pattern and externalities of GBA's knowledge innovation network using a social network method and spatial econometric model. Results show that Guangzhou and Hong Kong have always been the cores of knowledge innovation in network. Shenzhen emerged as an innovation centre after 2012, and other cities have become peripheral areas in the network. Small- and medium-sized cities do not benefit from the innovative development of core cities but are trapped in their agglomeration shadow. Institutional and cultural differences are the main obstacles hindering innovation cooperation between cities. In comparison, distance has fewer limitations on innovation cooperation. The negative externality of knowledge innovation network indicates that this region should narrow the gap of spatial differences, optimise the innovation network pattern to improve the network externalities.

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