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长三角绿色技术转移空间关联网络演化及驱动因素研究 被引量:11

The Evolution and Driving Factors of Green Technology Transfer Network in the Yangtze River Delta
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摘要 绿色技术转移是实现长三角高质量一体化发展的关键环节,并为实现碳达峰、碳中和目标提供技术支撑。通过收集2012—2019年长三角41个城市绿色专利转让数据,运用社会网络分析法,剖析长三角绿色技术转移空间关联网络结构特征演化及驱动因素。研究结果表明:①长三角绿色技术转移空间关联网络日益稠密,呈现出多线程网络结构,网络结构愈发稳定,等级森严度降低,但两极分化特征明显;②长三角绿色技术转移空间异质性显著,网络形成双向溢出、经纪人、净溢入、净溢出四类板块,呈现出多中心、多层次阶梯式发展格局;③城市经济、金融水平、地理区位、环境规制四方面的联系对长三角绿色技术转移空间关联性有显著促进作用,政府科研教育支持力度、产业结构有待提升。在此基础上,从把握整体关联网络结构、拓展绿色技术转移渠道、明晰城市网络角色地位、实施差异化政策调控、促进城际要素流动共享、赋能绿色技术扩散应用等方面提出针对性建议。 Green technology transfer is the key link of high-quality integrated development in Yangtze River Delta,and it can provide technical support for achieving the goal of carbon peak and carbon neutralization.Yangtze River Delta is the regional representative with the most active economic development,the highest degree of openness and the strongest innovation ability in China.It is also the demonstration and pilot area of national green development and collaborative innovation.The economic development of Yangtze River Delta has entered a new stage of improving quality and efficiency.In this context,Yangtze River Delta has achieved remarkable results in environmental governance,active technology transfer,and green technology has gradually got rid of external dependence.However,the imbalance of regional development level of green technology is obvious and the polarization is serious.In order to accurately grasp the direction of green technology transfer in Yangtze River Delta and reasonably promote the development of green technology transfer,this paper takes 41 cities in Yangtze River Delta as the research object,uses the directional green patent transfer data from 2012 to 2019,constructs the inter city green technology transfer spatial correlation network with the help of social network analysis,and reveals its basic characteristics and evolution trend from the overall and individual levels.It also analyzes the impact mechanism,in order to stimulate the vitality of green technology transfer and carbon emission reduction in Yangtze River Delta,strengthen collaborative innovation among cities and solve the unbalanced and insufficient green development in Yangtze River Delta.The study provides reference for the realization of high-quality integrated development in Yangtze River Delta,and empirical evidence for China's realization of double carbon goal and green and low-carbon transformation.The results show that firstly in the integration process of Yangtze River Delta,the spatial correlation network of green technology transfer is becoming more and more dense,presenting a multi-threaded network structure.Although the network structure is becoming more and more stable and the level of strictness is reduced,the characteristics of polarization are obvious,and there is still room for improvement.Secondly during the investigation period,the green technology transfer in Yangtze River Delta showed a"core edge"network structure,forming the spatial distribution characteristics with Shanghai,Nanjing,Suzhou,Hangzhou and Hefei as the strong core and Zhenjiang,Nantong,Wenzhou,Jiaxing,Ningbo,Bengbu and Wuhu as the subcore.The polarization phenomenon and diffusion path of green technology transfer between Jiangsu,Zhejiang and Shanghai increased,and the remoter cities in Anhui are not actively involved in this.Thirdly the spatial heterogeneity of green technology transfer in Yangtze River Delta is significant.The network forms four types of plates:two-way spillover,broker,net spillover and net spillover.Eastern developed cities such as Shanghai,Nanjing,Suzhou and Wuxi can be classified as two-way spillover plates.Cities such as Hangzhou,Shaoxing,Nantong and Hefei belong to broker plates.Lianyungang,Suqian,Xuancheng,Huangshan and other cities can be included in the net overflow plate,while Lu'an,Quzhou and Fuyang belong to the net overflow plate respectively.The transmission path of interaction between core cities and transmission between core edge cities shows an obvious Matthew effect and forms a stepped development pattern.Fourthly the links of economy,finance,geographical location and environmental regulation between cities have a significant role in promoting the spatial relevance of green technology transfer in Yangtze River Delta.The negative effect of government support for scientific research and education is obvious,while the link of industrial structure has no obvious effect,which needs to be strengthened.On this basis,this paper puts forward targeted strategic suggestions from the following aspects:grasping the overall connected network structure,expanding the transfer channels of green technology,implementing policy regulation for the role and status of urban network and differentiation,promoting the flow and sharing of intercity elements,and enabling the diffusion and application of green technology.There is still room for further research in this paper.Firstly,green technology transfer includes various forms.In addition to patent transfer,there are also other forms such as talent flow,commodity trading,investment spillover and so on.Secondly,enterprises,universities,scientific research institutes and other different types of subjects are bound to have behavioral differences in the process of green technology transfer.In the future,scholars can expand the research on the embedded integration of green technology in different industrial chains,value chains and talent chains from a micro perspective,and conduct research based on the main types,industries,transfer forms and dynamic heterogeneity of green technology transfer,and explore the strategic suggestions to promote green technology transfer from a multi-dimensional perspective.
作者 黄永春 钱昕怡 严翔 邹晨 Huang Yongchun;Qian Xinyi;Yan Xiang;Zou Chen(Business School,Hohai University,Nanjing 211100,China)
机构地区 河海大学商学院
出处 《科技进步与对策》 CSSCI 北大核心 2022年第21期45-55,共11页 Science & Technology Progress and Policy
基金 国家社会科学基金项目(21BGL016) 国家社会科学基金一般项目(21BJY254) 教育部人文社会科学研究项目(20YJC630180) 江苏省知识产权局软科学项目(JSIP-2021-R-B04)。
关键词 绿色技术转移 长三角 空间关联网络 驱动因素 Green Technology Transfer Yangtze River Delta Spatial Evolution Driving Factors
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