Xu Lingyan, Wang Dandan, Du Jianguo
School of Management, Jiangsu University, Zhenjiang 212013, China.
Research Center for Green Development and Environmental Governance, Jiangsu University, Zhenjiang 212013, China.
Int J Environ Res Public Health. 2022 Mar 25;19(7):3939. doi: 10.3390/ijerph19073939.
Green and smart city is an optimal choice for cities to realize their modernization of governance capacity and sustainable development. As such, it is necessary to clarify the evolutionary characteristics and driving mechanism of urban green and smart development level (GSDL) systematically. From the perspective of green total factor productivity (GTFP), this study adopted the SBM-GML (slack-based model & global Malmquist-Luenberger) method to measure the urban GSDL considering smart input-output elements. Based on the panel data of China's 232 prefecture-level cities from 2005 to 2018, the spatial and temporal evolution characteristics of urban GSDL were explored, and the factors and structural mutation points affecting urban GSDL were analyzed with quantile regression tests and threshold regression tests. The findings of this paper showed that (1) there is an upward trend in the volatility of urban GSDL from 2005 to 2018, in which the eastern region was highest, followed by the central and western regions, and the differentiation showed no converge among regions; (2) the effect of technical progress and technical efficiency improvement on the urban GSDL was demonstrated with a fluctuating "Two-Wheel-Drive" trend on the whole; (3) the urban GSDL was promoted by the opening-up level and urban scale significantly, while inhibited by the level of economic development and government size. Additionally, the effects of industrial structure, financial development level, and human capital level on the urban GSDL were distinctive at different loci; (4) the threshold effects of economic and financial development level on improving the positive effects of industrial structure and opening-up level on urban GSDL were significant. These findings may enrich the research literature on the evolutionary heterogeneity of green and smart cities and provide theoretical and practical exploration for the construction of green and smart cities.
绿色智慧城市是城市实现治理能力现代化和可持续发展的最优选择。因此，有必要系统地厘清城市绿色智慧发展水平（GSDL）的演变特征及驱动机制。本研究从绿色全要素生产率（GTFP）的视角出发，采用SBM-GML（松弛变量模型与全局Malmquist-Luenberger指数）方法，在考虑智慧投入产出要素的基础上对城市GSDL进行测度。基于2005—2018年中国232个地级市的面板数据，探究城市GSDL的时空演变特征，并运用分位数回归检验和门槛回归检验分析影响城市GSDL的因素及结构突变点。研究结果表明：（1）2005—2018年城市GSDL波动呈上升趋势，其中东部地区最高，中部和西部地区次之，区域间差异未出现收敛；（2）技术进步与技术效率提升对城市GSDL的影响总体呈波动的“双轮驱动”态势；（3）对外开放水平和城市规模对城市GSDL有显著促进作用，而经济发展水平和政府规模对其有抑制作用。此外，产业结构、金融发展水平和人力资本水平在不同分位点上对城市GSDL的影响具有差异性；（4）经济和金融发展水平对提升产业结构和对外开放水平促进城市GSDL的正向效应具有显著的门槛效应。这些研究结果可能丰富绿色智慧城市演变异质性的研究文献，并为绿色智慧城市建设提供理论与实践探索。
