|
|
Spatial-temporal Development Characteristics and Dynamic Evolution of Industrial Green Innovation Efficiency in the Urban Agglomerations of Yangtze River Delta |
Ma Zhiqiang,Wang Yan,Su Jialu |
(School of Management, Jiangsu University, Zhenjiang 212013, China) |
|
|
Abstract As one of the urban agglomerations with the highest level of economic development in China, the urban agglomerations of Yangtze River Delta has become an area with a high concentration of problems such as resource shortage, environmental pollution and ecological damage in promoting rapid development of industrialization and urbanization.Green innovation is an effective way to promote the sustainable development of urban agglomerations and coordinate the relationship between ecological civilization and economic growth. It is helpful to promote the green innovation development of urban agglomerations in the Yangtze River Delta by figuring out the temporal characteristics and evolution law of green innovation efficiency. Therefore, this study focuses on the urban agglomerations of the Yangtze River Delta, analyzes the spatial and temporal development characteristics and dynamic evolution process of their industrial green innovation efficiency,so as to further improve the industrial green innovation level of the urban agglomerations of the Yangtze River Delta, promote the differentiated development of various cities, and provide effective reference for promoting the construction of innovative urban agglomeration.#br#In this study, 41 cities in the Yangtze River Delta urban agglomerations are firstly taken as the research object to construct the industrial green innovation efficiency index system of the urban agglomerations of Yangtze River Delta. Secondly, the super-efficiency SBM-DEA model based on the undesired output is used to measure the industrial green innovation efficiency of the Yangtze River Delta urban agglomerations from 2010 to 2020. Through the construction of the inverse distance matrix, the global and local Moran's I are used to explore the spatial-temporal differentiation characteristics of industrial green innovation efficiency in the Yangtze River Delta urban agglomerations. Meanwhile, the Moran's I scatter plot is further analyzed according to the spatial-temporal analysis method, and the types and paths of its dynamic transitions are studied.#br#The results show that the measurement results of industrial green innovation efficiency in the urban agglomerations of the Yangtze River Delta show a fluctuation trend of "W" in general from the perspective of time series development, and the overall green innovation level of the urban agglomeration of the Yangtze River Delta gradually improves, except that the efficiency value decreases significantly due to the impact of the epidemic in 2020. On the spatial evolution pattern, there is an uneven distribution of green innovation efficiency on the whole space, and high efficiency main cities are gathered in the southeast and northwest area, with more cities of high-high and low-low are of agglomeration types. Besides there is a positive correlation of efficiency in general, and its spatial correlation decreases with time series development. The spatial leap shows high spatial stability, and the "spillover effect" and "siphon effect" coexist, while there are clear spatial aggregation and mobility.#br#Different from previous literatures, this study starts from the micro level of urban agglomeration in Yangtze River Delta. With the adjustment of national planning, the research object is expanded to 41 cities, enriching the research on urban agglomeration in the field of green innovation. At the same time, the influence of resource factors on green innovation efficiency is considered in the selection of input index. In terms of spatial auto-correlation analysis, the dynamic and transition analysis of industrial green innovation efficiency at urban agglomeration level is carried out, and the spatial evolution pattern of prefecture-level cities is analyzed as a unit, which has guiding significance for grasping the law of green innovation development in urban agglomeration. Future study is expected to explore the factors that affect the green innovation efficiency of the urban agglomerations of Yangtze River Delta, and analyze its spatial spillover effect on the green innovation efficiency.#br#
|
Received: 09 March 2022
|
|
|
|
|
[1] 刘晓丽,方创琳. 城市群资源环境承载力研究进展及展望[J].地理科学进展,2008,27(5):35-42. [2] CHEN G, MORAWSKA L, ZHANG W, et al. Spatiotemporal variation of PM1 pollution in China[J]. Atmospheric Environment, 2018, 178:198-205. [3] HOOKER R E,SEMAN N,GOVINDAN K,et al. The mediating effect of green innovation on the relationship between green supply chain management and environmental performance[J]. Journal of Cleaner Production, 2020, 229:115-127. [4] TARIQ A,BADIR Y F,TARIQ W,et al. Drivers and consequences of green product and process innovation: a systematic review, conceptual framework and future outlook[J]. Technology in Society, 2017, 51:8-23. [5] FAN F,LIAN H,LIU X,et al. Can environmental regulation promote urban green innovation efficiency? an empirical study based on Chinese cities[J]. Journal of Cleaner Production, 2020, 287(1):125060. [6] 赵琳,范德成. 我国高技术产业技术创新效率的测度及动态演化分析——基于因子分析定权法的分析[J].科技进步与对策,2011,28(11):111-115. [7] 乔元波,王砚羽. 基于三阶段DEA-Windows分析的中国省域创新效率评价[J].科学学与科学技术管理,2017,38(1):88-97. [8] 刘佳,宋秋月. 中国旅游产业绿色创新效率的空间网络结构与形成机制[J].中国人口·资源与环境,2018,28(8):127-137. [9] 罗良文,梁圣蓉. 中国区域工业企业绿色技术创新效率及因素分解[J].中国人口·资源与环境,2016,26(9):149-157. [10] 孙燕铭,谌思邈. 长三角区域绿色技术创新效率的时空演化格局及驱动因素[J].地理研究,2021,40(10):2743-2759. [11] 肖黎明,高军峰,韩彬.中国省际绿色创新效率的空间溢出效应——同质性和异质性检验[J].工业技术经济,2018,37(4):30-38. [12] 黄杰,金华丽. 中国绿色创新效率的区域差异及其动态演进[J].统计与决策,2021,37(21):67-71. [13] 孙振清,李欢欢,刘保留. 中国东部沿海四大城市群协同创新效率综合测度及影响因素研究[J].科技进步与对策,2021,38(2):47-55. [14] 段永峰,顼文晴,罗海霞. 中国省域绿色创新效率与绿色发展效率耦合协调研究[J].科技管理研究,2020,40(17):235-243. [15] 吴旭晓.中国区域绿色创新效率演进轨迹及形成机理研究[J].科技进步与对策,2019,36(23):36-43. [16] 吕岩威,谢雁翔,楼贤骏. 中国区域绿色创新效率时空跃迁及收敛趋势研究[J].数量经济技术经济研究,2020,37(5):78-97. [17] 董会忠,李旋,张仁杰. 粤港澳大湾区绿色创新效率时空特征及驱动因素分析[J].经济地理,2021,41(5):134-144. [18] 潘春苗,母爱英,翟文.中国三大城市群协同创新网络结构与空间特征——基于京津冀、长三角城市群和粤港澳大湾区的对比分析[J].经济体制改革,2022(2):50-58. [19] 葛世帅,曾刚,杨阳,等.基于DEA-Malmquist和Tobit模型的长三角城市群绿色创新绩效研究[J].长江流域资源与环境,2022,31(4):738-749. [20] CHARNES A,COOPER W W,RHODES E . Measuring the efficiency of decision-making units[J]. European Journal of Operational Research, 1978, 2(6):429-444. [21] BANKER R D,CHARNES A,COOPER W W . Some models for estimating technical and scale inefficiencies in DEA[J]. Management Science, 1984, 32:1613-1627. [22] TONE K. A slacks-based measure of efficiency in data envelopment analysis[J]. European Journal of Operational Research, 2001, 130(3):498-509. [23] 成刚. 数据包络分析方法与MaxDEA软件[M].北京:知识产权出版社, 2014. [24] 李昊,范德成,张书华,等.我国区域绿色技术创新效率的分类测度和提升模式研究——基于非期望产出的SBM-SupSBM模型[J].运筹与管理,2022,31(4):184-189,203. [25] LI H,ZHANG J,EDWARD O,et al. Sustainable development of China's industrial economy:an empirical study of the period 2001—2011[J]. Sustainability, 2018, 10(3):764. [26] 丁显有,肖雯,田泽. 长三角城市群工业绿色创新发展效率及其协同效应研究[J].工业技术经济,2019,38(7):67-75. [27] 肖振红,李炎.知识产权保护、R&D投入与区域绿色创新绩效[J].系统管理学报,2022,31(2):374-383. [28] 王问苈,时培豪,黄庆华.成渝地区双城经济圈绿色创新效率、演变趋势与影响因素研究[J].西南大学学报(自然科学版),2022,44(3):172-182. [29] 肖仁桥,沈路,钱丽.“一带一路”沿线省份工业企业绿色创新效率及其影响因素研究[J].软科学,2020,34(8):37-43. [30] MANAGI S,KANEKO S . Economic growth and the environment in China: an empirical analysis of productivity[J]. International Journal of Global Environmental Issues, 2006, 6(1):89-133. [31] REY S J,JANIKAS M V . Stars:space-time analysis of regional systems[J]. Geographical Analysis, 2006,38(1):67-86. [32] 滕堂伟,瞿丛艺,胡森林,等.长三角城市群绿色创新效率格局分异及空间关联特征[J].华东师范大学学报(哲学社会科学版),2019,51(5):107-117,239-240.
|
|
|
|