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长江经济带绿色创新效率的时空演化趋势 被引量:6

Spatiotemporal Evolution Trend of Green Innovation Efficiency in the Yangtze River Economic Belt
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摘要 从细化城市层面及动态演化视角研究长江经济带绿色创新效率。采用超效率SBM-DEA模型和探索性空间数据分析(ESDA)方法,研究长江经济带108个城市2004—2018年绿色创新效率的时空演变特征和空间相关性。结果表明:长江经济带绿色创新效率前期呈倒“V”型发展趋势,全球金融危机后呈缓慢波动上升状态,纯技术效率是影响绿色创新效率的关键因素;上中下游区域绿色创新效率存在差异,其中下游区域的效率水平最高,上游和中游城市的绿色创新效率均值在各年份交替领先;长江经济带绿色创新效率的空间格局由呈现上游和下游高于中游的“U”型分布特征逐渐转变为多中心分布特征,随着时间的推进,城市间绿色创新效率的正向空间相关性愈发显著,但低效率城市聚集的规模大于高效率城市,局部两极分化现象加剧。 This paper studies the green innovation efficiency of the Yangtze River Economic Belt from the perspective of refined city level and dynamic evolution.Using the super-efficiency SBM-DEA model and exploratory spatial data analysis(ESDA)method,the paper studies the spatiotemporal evolution characteristics and spatial correlation of green innovation efficiency in 108 cities in the Yangtze River Economic Belt from 2004 to 2018.The results show that the green innovation efficiency of the Yangtze River Economic Belt has an inverted"V"-shaped development trend in the early stage,and after the financial crisis,it has been slowly fluctuating and rising,and pure technical efficiency is the key factor affecting green innovation efficiency;there are differences in green innovation efficiency in the upper,middle and lower reaches,among them,the efficiency level of the downstream area is the highest,and the average green innovation efficiency of the upstream and midstream cities alternately leads in each year;the spatial pattern of the green innovation efficiency of the Yangtze River Economic Belt has gradually changed from a"U"-shaped distribution characteristics that the upstream and downstream are higher than the midstream reaches to the multi-center distribution characteristics,as time progresses,the positive spatial correlation of green innovation efficiency between cities becomes more and more significant,but the scale of low-efficiency cities is larger than that of high-efficiency cities,and the phenomenon of local polarization is intensified.
作者 张长江 侯梦晓 陈雨晴 Zhang Changjiang;Hou Mengxiao;Chen Yuqing(School of Economics and Management,Nanjing Tech University,Nanjing 211816,China)
出处 《科技管理研究》 CSSCI 北大核心 2022年第6期51-58,共8页 Science and Technology Management Research
基金 国家社会科学基金重点项目“基于战略协同与激励相容的高校科技创新绩效提升研究”(19AGL009)。
关键词 长江经济带 绿色创新效率 超效率SBM-DEA模型 探索性空间数据分析 the Yangtze River Economic Belt green innovation efficiency super SBM-DEA model exploratory spatial data analysis(ESDA)
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