Journal
CHINESE GEOGRAPHICAL SCIENCE
Volume 31, Issue 3, Pages 413-428Publisher
SPRINGER
DOI: 10.1007/s11769-021-1198-4
Keywords
built environment; innovation productivity; patent; spatial heterogeneity; Pearl River Delta
Categories
Funding
- National Natural Science Foundation of China [41871150]
- GDAS' Project of Science and Technology Development [2021GDASYL-20210103004]
- National Key Research and Development Program [2019YFB2103101]
- Special Construction Project of Guangdong-Hong Kong-Macao Greater Bay Area Strategic Research Institute [2020GDASYL-20200201001]
- Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) [GML2019ZD0301]
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This study examines the impact of the built environment on the spatial heterogeneity of regional innovation productivity (RIP) using China's Pearl River Delta as a case study. The results show that factors such as healthy environment, mixed land use, commuting convenience, and technology atmosphere have significant positive impacts on RIP, with technology atmosphere having the greatest impact intensity. As regional development discourse shifts towards the knowledge and innovation economy, policymakers will need to focus on innovation-oriented design and updating of built environments.
With the global economy increasingly dependent on innovation, urban discourse has shifted to consider what kinds of spatial designs may best nurture innovation. We examined the relationship between the built environment and the spatial heterogeneity of regional innovation productivity (RIP) using the example of China's Pearl River Delta (PRD). Based on a spatial database of 522 546 patent data from 2017, this study proposed an innovation-based built environment framework with the following five aspects: healthy environment, daily interaction, mixed land use, commuting convenience, and technology atmosphere. Combining negative binomial regression and Geodetector to examine the impact of the built environment on RIP, the results show that the spatial distribution of innovation productivity in the PRD region is extremely uneven. The negative binomial regression results show that the built environment has a significant impact on the spatial differentiation of RIP, and, specifically, that healthy environment, mixed land use, commuting convenience, and technology atmosphere all demonstrate significant positive impacts. Meanwhile, the Geodetector results show that the built environment factor impacts the spatial heterogeneity of RIP to varying degrees, with technology atmosphere demonstrating the greatest impact intensity. We conclude that as regional development discourse shifts focus to the knowledge and innovation economy, the innovation-oriented design and updating of built environments will become extremely important to policymakers.
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