Innovation Ecosystems and Sustainable High Innovation Performance: Evidence from the Guangdong–Hong Kong–Macao Greater Bay Area DOI Open Access
Fan Wu, Mingyang Li, Huang He

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9487 - 9487

Published: Oct. 31, 2024

The innovation ecosystem has a significant impact on regional development. Based the “actor-resource-environment” analytical framework, this study takes nine cities in mainland China within Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2012 to 2022 as case studies. By applying comprehensive evaluation model and kernel density estimation, analyzes development level dynamic evolution of GBA. Furthermore, using mixed-method approach QCA NCA, explores pathways achieving high performance key findings are follows: (1) score GBA shows rising trend, with pattern multi-polarization, “top-tier effect”, persistence strong region. (2) Technological actors digital economy environment have become necessary conditions for sustained Inter-group results highlight temporal effects technological actors, R&D personnel input, public service environment, which exhibit S-shaped, W-shaped, U-shaped patterns, respectively. Intra-group reveal notable differences necessity seven conditional variables across cities. (3) There two types ecosystems driving GBA: actor-driven resource–environment synergy-driven ecosystems. While no cross-time or cross-case exist between these types, inter-group consistency changes indicate that more mature stable since establishment 2017.

Language: Английский

Innovation Ecosystems and Sustainable High Innovation Performance: Evidence from the Guangdong–Hong Kong–Macao Greater Bay Area DOI Open Access
Fan Wu, Mingyang Li, Huang He

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9487 - 9487

Published: Oct. 31, 2024

The innovation ecosystem has a significant impact on regional development. Based the “actor-resource-environment” analytical framework, this study takes nine cities in mainland China within Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2012 to 2022 as case studies. By applying comprehensive evaluation model and kernel density estimation, analyzes development level dynamic evolution of GBA. Furthermore, using mixed-method approach QCA NCA, explores pathways achieving high performance key findings are follows: (1) score GBA shows rising trend, with pattern multi-polarization, “top-tier effect”, persistence strong region. (2) Technological actors digital economy environment have become necessary conditions for sustained Inter-group results highlight temporal effects technological actors, R&D personnel input, public service environment, which exhibit S-shaped, W-shaped, U-shaped patterns, respectively. Intra-group reveal notable differences necessity seven conditional variables across cities. (3) There two types ecosystems driving GBA: actor-driven resource–environment synergy-driven ecosystems. While no cross-time or cross-case exist between these types, inter-group consistency changes indicate that more mature stable since establishment 2017.

Language: Английский

Citations

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