绿色技术创新效率的时空演化格局及影响因素研究  

Study on the Spatial-Temporal Evolution Pattern and Influencing Factors of Green Technology Innovation Efficiency

作　　者：曹泽 苏建辉 CAO Ze;SU Jian-hui(School of Economics,Anhui Jianzhu University,Hefei Anhui 230071,China)

机构地区：[1]安徽建筑大学经济与管理学院,安徽合肥230071

出　　处：《铜陵学院学报》2025年第1期42-47,共6页Journal of Tongling University

基　　金：安徽省科研计划编制项目“专精特新企业梯度培育及制造业高质量发展研究”(2022AH050214)。

摘　　要：绿色技术创新作为驱动绿色发展和实现创新引领的契合点与核心驱动力,在推动经济发展和环境保护双赢中具有重要作用。文章通过构建含非期望产出的超效率SBM-DEA模型,测度了2013—2022年中国30个省份的绿色技术创新效率,并剖析了其时空演化格局与影响因素。研究发现,在时序上,各省份绿色技术创新效率呈波动变化,历经先升后降,在2019—2020年达峰值。在空间上,区域差异显著且呈集中趋势,中南与西北地区集聚水平渐弱,华东地区态势强劲。在影响因素方面,产业结构升级、环境规制、城镇化水平会负向影响本地的绿色技术创新效率,而财政分权的影响则反之;环境规制、财政分权、对外开放对周边地区的绿色技术创新效率有负向影响;而技术水平则对本地和周边地区均有正向影响。基于此,建议各地因地制宜、协同施策,优化各因素以提升绿色技术创新效率。Green technology innovation,a pivotal driver of green development,enables synergistic economic growth and environmental protection.The article constructs a super-efficiency SBM-DEA model incorporating undesirable outputs to evaluate green technology innovation efficiency across 30 Chinese provinces from 2013 to 2022,exploring its spatial-temporal evolution and influencing factors.Temporally,provincial efficiency exhibited fluctuating trends,peaking in 2019 and 2020 after an initial rise.Spatially,significant regional disparities emerged,with agglomeration levels weakening in central-south and northwest China,while eastern regions maintained strong performance.Key influencing factors reveal that industrial structure upgrading,environmental regulation,and urbanization negatively impacted local efficiency,whereas financial decentralization had a positive effect.Environmental regulation,financial decentralization,and openness adversely affected neighboring regions,while technological advancement positively influenced both local and adjacent areas.The study recommends region-specific strategies and factor optimization to enhance green technology innovation efficiency.

关 键 词：绿色技术创新效率 影响因素 超效率SBM-DEA模型 

分 类 号：F062.2[经济管理—政治经济学] F062.4