Digital economy and industrial energy efficiency performance: evidence from the city of the Yangtze River Delta in China

Wang, Liangjun; Yang, Peiling; Ma, Jia-Jun; Zhu, Zhen-Ning; Tian, Zhihua

doi:10.1007/s11356-022-24353-2

Cited by 14 publications

(4 citation statements)

References 73 publications

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“…Economic output can be measured by GDP. According to the geographic distribution, this study chose to analyze the CP of cities in 30 provinces in China and divided the 30 provinces into eight economic zones, as shown in Figure 2 [36]. In Figure 2, a total of 30 provinces are divided into eight comprehensive economic zones.…”

Section: Identification Of Cp-influencing Factorsmentioning

confidence: 99%

Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

Wang,

Chen

2024

Sustainability

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Given the threats to international energy security and the restructuring of energy sources in various countries, China faces the dual challenge of achieving the goals of carbon peaking and carbon neutrality. To promote a reduction in carbon emissions and enhance carbon productivity, it is crucial to innovate renewable energy technology for long-term, low-carbon transformational development. This paper identifies the key factors that affect carbon productivity through pathway analysis and quantitatively examines the direct and spatial spillover impacts of technological advancements in renewable energy using the spatial Durbin model. Finally, this study verifies the pathways through which innovations affect carbon productivity by combining them with the spatial mediation model. The results indicate that innovations in renewable energy technologies significantly enhance carbon productivity. The indirect effects of regional spillover are even more pronounced.

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Section: Identification Of Cp-influencing Factorsmentioning

confidence: 99%

Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

Wang,

Chen

2024

Sustainability

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“…The endowment of coal resource and rich mineral resources make the industrial structure of Shanxi Province biased toward heavy industry and relatively biased towards light industry. After 2019, the growth rate accelerated, which may be due to the outbreak of COVID-19, and local restriction on purchases affected social activities, leading to a higher share of heavy industry in the industrial structure [51].…”

Section: Control Variablesmentioning

confidence: 99%

The Empirical Effectiveness of China Digital Economy Enhancing Environmental Governance

Dai,

Fan,

Zhao

et al. 2023

Pol. J. Environ. Stud.

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At present, China is entering the era of digital economy. At the same time, "carbon peak" and "carbon neutral" are the main challenges. There is an urgent need to explore the role of the digital economy in reducing carbon emissions and environmental governance. In view of this, using the provincial panel data from 2011 to 2020, this paper makes an empirical study on the mechanism of the digital economy in environmental governance. It is found that with the growth of the digital economy, regional carbon emissions have decreased and the level of environmental governance has improved. After passing several kinds of robustness tests, this conclusion is still valid. The impact of the digital economy on environmental governance is heterogeneous. And the effect is even more obvious in the East. In addition, the transmission mechanism of strengthening environmental governance in the digital economy obviously benefits from the upgrading of industrial structure, the efficiency of capital allocation and labor allocation. Finally, according to the analysis and discussion of the results, some policy suggestions for developing countries to actively develop the digital economy and strengthen the effectiveness of environmental governance are put forward.

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“…Regarding the impact of energy efficiency and financial support on the green upgrading of industries, some scholars' research suggests that energy efficiency exerts a positive influence on industrial green upgrading [3,4] . Liang-Jun Wang et al argued that industrial energy efficiency is pivotal for achieving energy transformation, carbon emission reduction, and promoting industrial green transformation [5] . Karasek et al employed data envelopment analysis (DEA) to evaluate energy efficiency in European Union (EU) countries from a dynamic perspective [6] .…”

Section: Review Of Domestic and International Researchmentioning

confidence: 99%

Impact of Energy Efficiency and Financial Support on Green Upgrading in China’s Industrial Sector

Zhou,

Yang,

Meng

et al. 2023

PBES

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The report from the 20th National Congress of China emphasizes the importance of focusing on the clean, low-carbon, and efficient use of energy, increasing financial support, and promoting green upgrading within the industrial sector. This paper, based on annual data, employs the entropy weight method to construct a comprehensive index reflecting the impact of green upgrading in industrial sectors. To delve deeper, it utilizes the DEA model to measure energy efficiency and its subdivision BCC model to break down energy efficiency into technical and scale efficiency. The financial support landscape is examined from the vantage points of both direct and indirect financing. Using a multivariate time series model, this paper thoroughly investigates the influence of energy efficiency and financial support on the green upgrading of the industrial sector. The findings reveal a significant positive impact of both energy efficiency and financial support on green upgrading in industrial industries. Notably, scale efficiency emerges as the primary driver of energy efficiency. Moreover, indirect financing proves to be more effective in promoting financial support than direct financing. The empirical results retain their robustness even after substituting explanatory variables. The study concludes by contextualizing the research findings within the current real-world scenario, offering practical insights, and proposing specific recommendations.

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Digital economy and industrial energy efficiency performance: evidence from the city of the Yangtze River Delta in China

Cited by 14 publications

References 73 publications

Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

Impact Mechanism of Renewable Energy Technology Innovation on Carbon Productivity Based on Spatial Durbin Model

The Empirical Effectiveness of China Digital Economy Enhancing Environmental Governance

Impact of Energy Efficiency and Financial Support on Green Upgrading in China’s Industrial Sector

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