Factor Mobility, Industrial Transfer and Industrial Carbon Emission: A Spatial Matching Perspective

Zheng, Xinyu; Yu, Hong; Yang, Lin

doi:10.3389/fenvs.2022.822811

Cited by 14 publications

(5 citation statements)

References 52 publications

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“…Consequently, it creates a favorable market environment for optimizing and upgrading industrial structures. Industrial activities are significant contributors to carbon emissions; numerous studies have demonstrated the role of industrial structure upgrading in emission reduction [29][30][31], which will not be reiterated here.…”

Section: Structure Effectmentioning

confidence: 88%

The Impact of Digital Trade on Regional Carbon Emissions: Evidence from China

Wan,

He,

Chen

2024

Pol. J. Environ. Stud.

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With the rise of China's economy and the expansion of China's foreign trade scale, the carbon emissions generated by China's trade are attracting extensive attention from political and academic circles. In the context of global 'decarbonization', this paper focuses on the new trade model of digital trade and uses China's provincial panel data from 2013 to 2021 to deeply explore the effect of digital trade development on carbon emissions and its transmission mechanism. We find that digital trade development can reduce regional carbon emissions through structural and technological effects; specifically, industrial structure upgrading, consumption upgrading, and green technology innovation play a crucial intermediary role in this process. Subsequent investigation reveals a nonlinear, diminishing trend in the marginal impact of digital trade on emission reduction. Furthermore, once digital trade surpasses the threshold of environmental regulation its marginal effect on emission reduction becomes more pronounced. Additionally, employing a spatial econometric model has revealed that the advancement of digital trade can also contribute to reducing carbon emissions in neighboring regions. Heterogeneity analysis results demonstrate that the eastern region exhibits the most significant emission reduction effect in relation to digital trade, followed by the western and central regions.

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Section: Structure Effectmentioning

confidence: 88%

The Impact of Digital Trade on Regional Carbon Emissions: Evidence from China

Wan,

He,

Chen

2024

Pol. J. Environ. Stud.

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“…The amount of carbon emitted for every unit of gross industrial production is referred to as industrial carbon emission intensity (ICEI) [39,40]. ICEI can reflect the relationship between CE and industrial development.…”

Section: Calculation Methods Of Carbon Emissionsmentioning

confidence: 99%

Spatiotemporal Evolution Characteristics of Carbon Emissions from Industrial Land in Anhui Province, China

Zhang

Chen

et al. 2022

Land

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Carbon emissions (CE) in Anhui Province are closely related to carbon emissions from industrial land (CEIL). In this study, based on industrial land, industrial energy consumption, and related statistical data in Anhui Province from 2000 to 2016, the carbon emissions coefficient method and the standard deviational ellipse were used to measure and analyze the CEIL and their spatial and temporal evolution characteristics, aiming to provide a basis for the relevant government departments to formulate CE policies. The main results showed that: (1) The total amount of CEIL followed an inverted U-shaped trend of rapid increase followed by a decrease, while the overall carbon emission intensity from industrial land (CEIIL) followed a downward trend. (2) The CE had an evident spatial differentiation, with those from resource-based cities being much higher than those of industrial and tourism-based cities; (3) The overall pattern of CEIL in Anhui Province showed that the increase in the north-south direction is significantly higher than that in the east-west direction, and mainly expanded in the north-south direction. The overall industrial growth rate of Southern Anhui, represented by the Wanjiang City Belt, was higher than that of Northern Anhui, although its CEIL center showed to move towards Northern Anhui.

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“…With the increasing severity of climate problems, the issue of carbon transfer has gradually attracted the attention of scholars, who have focused on exploring the causes (Dong et al , 2022), quantitative measurements (Ji et al , 2020) and flow directions (Zheng et al , 2022) of carbon transfer. López et al (2019) found that American multinational enterprises transferred carbon emissions from domestic production to other countries through cross-border investments.…”

Section: Literature Reviewmentioning

confidence: 99%

Effects of interactions between technology spillovers and carbon transfers on carbon emission reduction decisions and coordination within supply chains

Jiang,

Sun,

Wang

2024

JBIM

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Purpose This paper aims to refine the mechanisms affecting the two-way technology spillover and carbon transfer interactions between supply chain enterprises, and to guide their reduction of carbon emissions. Design/methodology/approach This study formulates a supplier-led Stackelberg game model to explore the effects of the interactions between two-way technology spillover effects and carbon transfers in decentralized and centralized decision-making scenarios. The optimized Shapley value is introduced to coordinate across the supply chain and determine the overall profits lost in the decentralized scenario. Findings Emission reductions by the low-carbon manufacturer are negatively correlated with the carbon transfers. Vertical technology spillovers promote carbon reduction, whereas horizontal technology spillovers inhibit it. The vertical technology spillovers amplify the negative effects of the carbon transfers, whereas the horizontal technology spillovers alleviate these negative effects. When the vertical technology spillover effect is strong or the horizontal technology spillover effect is weak in the centralized scenario, the carbon reduction is negatively correlated with the carbon transfers. Conversely, when the vertical technology spillover effect is weak or the horizontal technology spillover effect is strong, the enterprise’s carbon reduction is positively correlated with the carbon transfers. An optimized Shapley value can coordinate the supply chain. Originality/value This study examines the effects of carbon transfers on enterprises from a micro-perspective and distinguishes between vertical and horizontal technology spillovers to explore how carbon transfers and different types of technology spillovers affect enterprises’ decisions to reduce carbon emissions.

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Factor Mobility, Industrial Transfer and Industrial Carbon Emission: A Spatial Matching Perspective

Cited by 14 publications

References 52 publications

The Impact of Digital Trade on Regional Carbon Emissions: Evidence from China

The Impact of Digital Trade on Regional Carbon Emissions: Evidence from China

Spatiotemporal Evolution Characteristics of Carbon Emissions from Industrial Land in Anhui Province, China

Effects of interactions between technology spillovers and carbon transfers on carbon emission reduction decisions and coordination within supply chains

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