Spatial-Temporal Evolution and Influencing Factors of Urban Green and Smart Development Level in China: Evidence from 232 Prefecture-Level Cities.

quantile regression tests spatial-temporal evolutionary heterogeneity threshold effect urban GSDL

Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
25 03 2022
Historique:
received: 24 01 2022
revised: 08 03 2022
accepted: 22 03 2022
entrez: 12 4 2022
pubmed: 13 4 2022
medline: 14 4 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 35409620
pii: ijerph19073939
doi: 10.3390/ijerph19073939
pmc: PMC8997646
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Références

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Auteurs

Lingyan Xu (L)

School of Management, Jiangsu University, Zhenjiang 212013, China.
Research Center for Green Development and Environmental Governance, Jiangsu University, Zhenjiang 212013, China.

Dandan Wang (D)

School of Management, Jiangsu University, Zhenjiang 212013, China.

Jianguo Du (J)

School of Management, Jiangsu University, Zhenjiang 212013, China.
Research Center for Green Development and Environmental Governance, Jiangsu University, Zhenjiang 212013, China.

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Classifications MeSH