Examining the Impact of Urban Connectivity on Urban Innovation Efficiency: An Empirical Study of Yangtze River Delta in China DOI Open Access
Chuankai Yang, Shuaijun Xue, Gao Peng

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(13), P. 5647 - 5647

Published: July 2, 2024

Innovation serves as a vital catalyst for sustainable urban development, with the enhancement of innovation efficiency representing critical strategy to bolster cities’ innovative capacity. Rigorous scientific measurement and thorough investigation into key factors influencing it are imperative advancing Despite this significance, prior research has largely overlooked impact connections on efficiency. Therefore, paper undertakes task measuring 27 cities within China’s Yangtze River Delta (YRD) region using an improved DEA model, while also examining associated factors. The primary findings follows: (1) comprehensive in YRD remains relatively low, pure technical notable constraint, scale demonstrates higher overall performance. (2) can be classified four distinct categories: innovation-leading, innovation-optimizing, innovation-breaking, innovation-improving cities. (3) exhibits negative spatial spillover effects. (4) And notably, local economic social characteristics such human capital degree openness play positive role enhancing Conversely, foundation government involvement exhibit contributions Additionally, population mobility between is identified significant contributor This study sheds light complex dynamics shaping underscores importance leveraging capacity beyond.

Language: Английский

Regional differences and convergence of green innovation efficiency in China DOI
Peiyang Zhao,

Zhiguo Lu,

Jiali Kou

et al.

Journal of Environmental Management, Journal Year: 2022, Volume and Issue: 325, P. 116618 - 116618

Published: Nov. 3, 2022

Language: Английский

Citations

65
Impact of Foreign Direct Investment on Green Innovation: Evidence from China’s Provincial Panel Data DOI Open Access
Lifeng Chen,

Fuxuan Guo,

Lingyan Huang

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(4), P. 3318 - 3318

Published: Feb. 10, 2023

The last couple of decades have witnessed growing interest in the academic literature conciliation finance and sustainable development. Foreign direct investment (FDI) faces increasing pressure from both host home country towards adoptinsg approaches. Such solutions can be green innovation (GI) for climate change, environmental risks, processes products that allow tracking carbon footprint, as well many other technologies. Based on macro-level data 31 provinces China 2003 to 2020, this paper employed policy environment (PE) marketization level (ML) moderating variables further investigate impact FDI GI. Our results show following: (1) has a significant positive dynamic evolution feature diminishing marginal efficiency (2) heterogeneity analysis regional regression shows significantly increases GI eastern western regions. In contrast, central region inhibits but not significantly. (3) Both PE ML positively moderate Furthermore, our empirical robustness test 2SLS GMM are highly consistent with main test. conclusions provide implications local governments fully effectively utilize foreign capital activities.

Language: Английский

Citations

13
Understanding the overall difference, distribution dynamics and convergence trends of green innovation efficiency in China’s eight urban agglomerations DOI Creative Commons
Ke-Liang Wang,

Ru-Yu Xu,

Yunhe Cheng

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 148, P. 110101 - 110101

Published: March 6, 2023

Based on adopting the global super-efficiency slacks-based measure (GSSBM) model to calculate green innovation efficiency (GIE), this paper systematically investigates GIE's overall difference, distribution dynamics and convergence trends in eight national urban agglomerations (UAs) of China from 2004 to2018 by combining methods Dagum Gini Coefficient (DGC), Kernel Density Estimation (KDE), Variation (VC), fixed-effect (FEM) spatial Durbin (SDM). The results show that: (1) average GIE UAs was 0.632 during 2004–2018, which is generally low has substantial potential for improvement, seven them achieved positive growth with an annual rate 2.70%. (2) difference within significant inter-UA as main contributor. (3) curves were distinct terms location, form, ductility polarization trend. (4) Besides five presenting σ characteristics, all displayed absolute or conditional β different speeds cycles. findings can provide important insights promotion innovation-driven development China.

Language: Английский

Citations

13
Exploration of Coupling Effects in the Digital Economy and Eco-Economic System Resilience in Urban Areas: Case Study of the Beijing-Tianjin-Hebei Urban Agglomeration DOI Open Access
Kai Yuan, Biao Hu, Xinlong Li

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(9), P. 7258 - 7258

Published: April 27, 2023

Exploring the interaction and coupling effects within digital economy eco-economic system resilience in urban agglomeration areas is conducive to promoting high-quality sustainable development. Based on effect perspective, we construct a coordination development with multiple elements, information, flow. The JJJ from 2010 2019 was used as study sample. spatiotemporal differences spatial of coupled were evaluated by combining tools combined weight model, nuclear density estimation, exploratory data analysis. main results can be summarized follows. (1) From 2019, economic index maintained an upward trend, time series characteristics two sides showed significant positive correlation. Additionally, overall better than system. (2) In terms type coordination, region has experienced dynamic evolution process imbalance primary 2019. coordinated levels Beijing Tianjin are obviously those Hebei Province whole. (3) shows certain distribution. pattern presents core, gap between north south gradually narrowing. (4) Spatial spillovers diffusion evident. However, influential factors have this neighboring regions. may provide theoretical support for continuous improvement ecological environment quality green efficiency agglomeration. It provides decision-making reference regional synergistic strategy optimizing integration.

Language: Английский

Citations

12
Evaluation of green innovation capability and influencing factors in the logistics industry DOI

Yana Nan,

Yi Tian,

Mengqi Xu

et al.

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: March 15, 2024

Language: Английский

Citations

4
Evolutionary characteristics and influencing mechanisms of green development efficiency in Chinese urban agglomerations: Analysis of the Yangtze River Delta urban agglomeration DOI
Yu Guo, Zihao Tong, Zhenbo Wang

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 375, P. 124236 - 124236

Published: Jan. 24, 2025

Language: Английский

Citations

0
Spatial correlation network structure of green innovation efficiency and its driving factors in the Bohai Rim region DOI

Kaixuan Di,

Zuankuo Liu, Shanglei Chai

et al.

Environment Development and Sustainability, Journal Year: 2023, Volume and Issue: 26(11), P. 27227 - 27247

Published: Aug. 14, 2023

Language: Английский

Citations

10
Assessing green production efficiency and spatial characteristics of China’s real estate industry based on the undesirable super-SBM model DOI Creative Commons
Bo-Wen An,

Peiyuan Xu,

Chunyu Li

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: July 16, 2024

Abstract As China strives to balance rapid urbanization with environmental conservation, increasing attention is being paid the pursuit of green production efficiency (GPE) in real estate industry. The undesirable super-SBM model was used calculate GPE China's industry from 2001 2020. Additionally, spatial distribution characteristics were analyzed using standard deviation ellipse (SDE), Moran’s index, Theil random kernel density estimation (RKDA), and Markov chain (SMC) methods. exhibited a U-shaped trend, 2008 as inflection point, first decreasing then increasing. It reached maximum value 0.747 index increased 0.043 0.121 nationwide, indicating overall low-level slow growth, imbalance. Discrepancies input–output scales, southward shift economic centers, population movements contribute significantly disparities between east west, north south, regions divided by Hu Huanyong Line (Hu Line). club convergence characteristics; however, polarization phenomena exist local areas. Spatial spillover effects also observed GPE. Finally, we provide recommendations for promoting development industry, including building technology, fiscal subsidy investment, migration management.

Language: Английский

Citations

2
Spatiotemporal Differentiation and Influencing Factors of Green Technology Innovation Efficiency in the Construction Industry: A Case Study of Chengdu–Chongqing Urban Agglomeration DOI Creative Commons
Bo Wang, Hongxi Chen, Yibin Ao

et al.

Buildings, Journal Year: 2022, Volume and Issue: 13(1), P. 73 - 73

Published: Dec. 28, 2022

In order to support the green and low-carbon transformation of China’s construction industry accomplish dual carbon objective, it is vital accelerate technology innovation. Therefore, this paper takes Chengdu–Chongqing urban agglomeration China as study area, using super-efficiency slacks-based measure (SBM)model gravity model assess efficiency innovation in industry, utilizing geographical detectors investigate drivers further. Additionally, we consider each influencing factor’s level impact on sector both under single factor double scenarios. The findings indicate that there a considerable difference metropolitan agglomeration’s trend upward. addition, research area exhibited spatially heterogeneous characteristics terms spatial spillover effect was significantly limited by distance. Further revealed environmental legislation, economic development, public concern, urbanization level, foreign direct investment were primary driving factors sector, industrial size potential factor. temporal differentiation also more affected interaction between dominating prospective than either acting alone. research’s are useful advancing offering theoretical decision-making reference.

Language: Английский

Citations

11
Spatial and temporal evolution characteristics of urban green innovation efficiency in Northeast China DOI Creative Commons

Wu Xiaolin,

Decheng Fan

Frontiers in Energy Research, Journal Year: 2023, Volume and Issue: 11

Published: May 30, 2023

In the strategic context of promoting comprehensive revitalization Northeast China, green innovation, as integration two development concepts innovation-driven and development, has become an essential means to promote sustainable high-quality in China. By constructing Super-SBM model with undesired output Global Malmquist-Luenberger index model, innovation efficiency total factor productivity 34 prefecture-level cities China from 2011 2020 are measured. Then natural break point classification method, standard deviation ellipse Dagum Gini coefficient decomposition method used explore their spatial temporal evolution characteristics. Based on measured results all classified into four types: high-high, high-low, low-high low-low. The study show that (GIE) northeast region shows excellent upward trend, distribution pattern “strong North weak South” is more prominent. a fluctuating decline, technical technological progress inhibit improvement efficiency. centre gravity generally migrated towards southwest, among gradually tended develop balanced manner, inter-provincial differences primary source concludes should continuously improve its resource allocation capacity, accelerate transformation upgrading industrial structure, clarify subjects, optimize environment formulate differentiated strategies synergistic cities.

Language: Английский

Citations

5