Configuration paths of carbon emission efficiency in manufacturing industry DOI Creative Commons
Yafeng Li,

Jingting Sun,

Jing Bai

et al.

Energy Informatics, Journal Year: 2024, Volume and Issue: 7(1)

Published: Aug. 26, 2024

From the perspective of configuration, this paper takes region manufacturing efficiency as explanatory variable, selects eight antecedent conditions, and applies fuzzy set qualitative comparative analysis (fsQCA) to study paths methods improving emission efficiency. The results show that there are two configuration carbon in industry, namely, research frontier technological innovation level labour force structure, R&D investment, science technology level, output value, environmental regulation synergistic path.

Language: Английский

Impact of Digital Technology Innovation on Carbon Emission Reduction and Energy Rebound: Evidence from the Chinese Firm Level DOI
Yue Liu,

Liu Nengyu,

Yijia Huo

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135187 - 135187

Published: Feb. 1, 2025

Language: Английский

Citations

0

Digital–real economy integration and urban low-carbon development in China DOI

Zhenhua Xu,

W. Xu, Daleng Xin

et al.

Economic Analysis and Policy, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0

Nonlinear spatial impacts of the digital economy on urban ecological welfare performance: evidence from China DOI Creative Commons
Sen Wang, Jinye Li

Frontiers in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 12

Published: March 13, 2024

Introduction With the rapid development of digital technology and its deep integration with environmental ecological fields, economy has become an effective way to guide transition cities eco-friendly model. However, empirical studies on nonlinear spatial effects between welfare performance are still insufficient. Methods Based panel data 270 prefecture-level in China from 2011 2020, this paper empirically examines impact mechanism action using econometric modeling. Results The promotion effect is characterized by “J” shape increasing marginal effect, spillover neighboring inverted “U” inhibiting first then promoting later. test shows that can enhance through incremental green technological innovation local a positive effect. have direct U influencing factor allocation efficiency energy utilization efficiency. It also U-shaped Environmental regulation moderating eco-welfare affected economy. As level rural revitalization increases, it produces inhibiting. Heterogeneity analysis reveals more significant facilitating central China. Discussion This will provide reference for synergistic optimization among regions. findings study promote accelerate realization goal “Beautiful China”.

Language: Английский

Citations

3

The spatial effect of integrated economy on carbon emissions in the era of big data: a case study of China DOI Creative Commons
Yan Wang, Qian Ke, Shuzhen Lei

et al.

Frontiers in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 12

Published: April 24, 2024

The digital economy has the characteristics of resource conservation, which can solve China’s high carbon emissions problems. quickly integrate with real economy, forming an integrated economy. However, it is still unclear whether effectively reduce and achieve ‘dual goals’. Therefore, this study takes 30 provinces in China as research object, constructs integration index system through statistical data from 2011-2021, explores spatial effect impact on by using principal component analysis, coupled coordination model econometric model. results are follows. (1) From 2011 to 2021, comprehensive showed a trend increasing yearly (from 0.667 0.828), slow decrease 0.026 0.017). (2) Due infiltration economic development eastern western, distribution shows decreasing east west. may be related industrial layout heavy industry northern, light southern, showing low south north. (3) significantly (the coefficients influence, -0.146), reduction will more obvious if spillover effects taken into account (-0.305). (4) coast, middle reaches Yangtze River, Yellow River zones all increase at certain level significance (0.065, 0.148, 3.890). Northeast, South Coastal Southwest (-0.220, -0.092, -0.308). Northern Coast Northwest not significant (-0.022 0.095). (5) should tailor regional policies, such strengthening investment infrastructure Economic Zone fully leveraging Southern Coastal, Zones emissions.

Language: Английский

Citations

1

The Impact and Mechanism behind the Effect of a Digital Economy on Industrial Carbon Emission Reduction DOI Open Access
Gang Zhou, Jiaxin Gao, Yao Xu

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(13), P. 5705 - 5705

Published: July 3, 2024

Digital technologies hold significant potential for addressing environmental issues, such as air pollution and rising global temperatures. China is focusing on accelerating the dual transformation of industrial greening digitization to accomplish UN’s 2030 Agenda Sustainable Development sustainable economic growth. By combining a two-way fixed effect model, mediated panel threshold this research endeavors explore that expansion digital economy has level carbon emission intensity produced by industry. The yielded following primary conclusions. (1) effectively reduces via three distinct mechanisms: enhancements technological innovative capacities China, improvements in energy efficiency, country’s overall structure. (2) Regions where industrialization are highly integrated developing, well early pilot regions Comprehensive Big Data Pilot Zones, particularly susceptible inhibitory effect. This offers theoretical backing advancements economy; achievement energy-saving carbon-reducing development objectives; establishment green, ecologically friendly, recycling strategies.

Language: Английский

Citations

1

Research On the Path of High Quality Development Enabled by Big Data Technology in the Curved Area of The Yellow River DOI Creative Commons

Minjie Wang Jiangxin He

Deleted Journal, Journal Year: 2024, Volume and Issue: 20(2), P. 2013 - 2017

Published: April 8, 2024

Big data is a key factor of production to promote the current social development, and good use big technology must achieve high-quality development. Jiziwan Yellow River strategic overlapping area western development overland Silk Road, which has very important value both in terms geographical space historical Therefore, it particularly enable region with technology. By analyzing relevant main provinces Bend recent years, this paper makes comparison gross product added three major industries, R&D investment industrial enterprises, so as get results existing problems. Through these analysis results, puts forward some solutions: using optimize regional structure, ecological innovative These optimization paths help importance digital economy high-quality, sustainable coordinated region.

Language: Английский

Citations

0

Digital development of manufacturing industry in Yangtze River Delta based on fuzzy control model DOI
Rui Li, Feng Zhao, Boyu Zhao

et al.

Journal of Computational Methods in Sciences and Engineering, Journal Year: 2024, Volume and Issue: 24(4-5), P. 2657 - 2671

Published: Aug. 14, 2024

In the context of global economic integration and Industry 4.0, digital manufacturing has become crucial. As one cores China, digitization process industry in Yangtze River Delta is particularly critical to overall growth. Based on theory 4.0 manufacturing, this study deeply analyzes current development Delta. More importantly, paper successfully constructs a fuzzy control model quantitatively evaluate guide transformation region. The empirical results reveal how key factors such as capital, talent, technology data security affect process, provide concrete operational strategies for addition, combined with industrial advantages, policy support, technological progress market demand, predicts prospects Overall, not only provides in-depth insights Delta, but also practical guidance actual operation, which high theoretical value.

Language: Английский

Citations

0

Configuration paths of carbon emission efficiency in manufacturing industry DOI Creative Commons
Yafeng Li,

Jingting Sun,

Jing Bai

et al.

Energy Informatics, Journal Year: 2024, Volume and Issue: 7(1)

Published: Aug. 26, 2024

From the perspective of configuration, this paper takes region manufacturing efficiency as explanatory variable, selects eight antecedent conditions, and applies fuzzy set qualitative comparative analysis (fsQCA) to study paths methods improving emission efficiency. The results show that there are two configuration carbon in industry, namely, research frontier technological innovation level labour force structure, R&D investment, science technology level, output value, environmental regulation synergistic path.

Language: Английский

Citations

0