黄河流域绿色创新的时空演化特征及影响因素分析
收稿日期: 2023-06-27
修回日期: 2023-09-14
网络出版日期: 2024-01-26
基金资助
国家自然科学基金项目(72004124);国家自然科学基金项目(72373084);山东省高等学校青创科技支持计划(省优秀青年创新团队)(2022RW064);山东省重点研发计划(软科学项目)(2022RKY04002);山东省人文社会科学课题(2022-YYJJ-32)
Spatiotemporal evolution characteristics and influencing factors of green innovation in the Yellow River Basin
Received date: 2023-06-27
Revised date: 2023-09-14
Online published: 2024-01-26
以2005—2020年黄河流域89个地级及以上城市为研究对象,运用绿色专利数据表征绿色创新水平,利用标准差椭圆和空间自相关揭示绿色创新的时空演化格局,并利用空间杜宾模型分析绿色创新的影响因素并分解各因素的空间效应。结果表明:(1) 黄河流域以及上游、中游和下游的绿色创新均呈现出快速发展趋势。(2) 绿色创新的标准差椭圆呈现“东北—西南”向分布格局,各参数基本稳定,重心呈现“先东后西”的移动特征。(3) 绿色创新全局空间自相关关系明显,局部空间自相关以高-高型和低-低型为主。(4) 科技投入对绿色创新具有显著的正向促进作用,城市研究与试验发展人员全时当量和第三产业占GDP比重具有显著的负向空间溢出效应,公共图书馆藏书量与建成区绿化覆盖率产生显著的正向空间溢出效应。(5) 科技投入对黄河上游绿色创新的正向促进作用最强,产业结构高级化可以显著促进黄河中游绿色创新的发展,社会文化对黄河下游绿色创新存在较强的正向促进作用。
任贵秀 , 刘凯 . 黄河流域绿色创新的时空演化特征及影响因素分析[J]. 干旱区地理, 2024 , 47(1) : 158 -169 . DOI: 10.12118/j.issn.1000-6060.2023.313
This study uses green patent data to characterize green innovation by taking 89 prefecture-level and above cities in the Yellow River Basin of China from 2005 to 2020 as the research object. It employs a standard deviation ellipse and spatial autocorrelation to unveil green innovation’s spatial and temporal evolution pattern. In addition, it uses a spatial Durbin model to analyze the factors influencing green innovation and decompose the spatial effects of various factors. The results indicate that: (1) green innovation in the Yellow River Basin and its upstream, midstream, and downstream areas demonstrate a rapid development trend. (2) The standard deviation ellipse of green innovation reveals a “northeast-southwest” distribution pattern with stable parameters. The center of gravity exhibits a moving pattern of “first east and then west”. (3) Global spatial autocorrelation of green innovation is evident, with local spatial autocorrelation primarily characterized by high-high and low-low patterns. (4) Science and technology investment substantially positively impacts green innovation. The full-time equivalent of urban research and experimental development personnel and the proportion of the tertiary industry exhibit a substantial negative spatial spillover effect. Conversely, the number of books in public libraries and the green coverage of built-up areas demonstrate a substantial positive spatial spillover effect. (5) Science and technology investment has the strongest positive effect of promoting green innovation in the upper reaches. The upgrading of industrial structure substantially promotes the development of green innovation in the middle reaches. Simultaneously, social culture plays a strong positive role in advancing green innovation in the lower reaches.
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