2023
DOI: 10.3389/fenvs.2023.1134882
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The impact of digital transformation on low-carbon development of manufacturing

Abstract: Objective: To measure the low-carbon development level and digital transformation degree of China’s manufacturing industry, and to examine the impact of digital transformation on low-carbon development.Methods: This paper uses Super Slack Based Measure (SBM) model and multi-regional input-output model to measure the low-carbon development level and digital transformation degree of 17 manufacturing industries in 30 provinces of China from 2012 to 2018, and uses high-dimensional fixed effect model and mediation … Show more

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Cited by 7 publications
(6 citation statements)
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“…Zhang et al [48] indicated the effect of digital technology development on reducing domestic embodied carbon intensity by analyzing the panel data of regions in China. Similarly, Lyu et al [49] pointed out that digital transformation had significant promotion on the development of low-carbon technology. Our paper aims to provide insights for formulating appropriate policies to accelerate the manufacturing digital transformation and regional economy development, which also contributes to sustainable development of manufacturing industry.…”
Section: Innovation and Research Path Of This Papermentioning
confidence: 99%
“…Zhang et al [48] indicated the effect of digital technology development on reducing domestic embodied carbon intensity by analyzing the panel data of regions in China. Similarly, Lyu et al [49] pointed out that digital transformation had significant promotion on the development of low-carbon technology. Our paper aims to provide insights for formulating appropriate policies to accelerate the manufacturing digital transformation and regional economy development, which also contributes to sustainable development of manufacturing industry.…”
Section: Innovation and Research Path Of This Papermentioning
confidence: 99%
“…Secondly, the level of development of the digital economy in the previous period will affect the current period. Choosing the intersection of the lag phase of the digital economy and the first-order difference as the instrumental variable can meet the correlation assumption (Lyu et al, 2023). This paper uses the twostage least squares method of instrumental variables to estimate.…”
Section: Endogenous Treatmentmentioning
confidence: 99%
“…With the rapid development of the digital economy, the environmental effects of the digital economy have received extensive attention from the academic community. Some scholars believe that the information and communication technology industry and e-commerce industry in the digital economy, as environmentally friendly industries, can optimize the industrial structure by squeezing out industries with high energy consumption and high emissions, thus promoting economic and social low-carbon development Lyu et al, 2023). Other scholars believe that the wide application of digital technology increases electricity consumption and thus has a negative impact on the environment (Salahuddin and Alam, 2015;Lin and Huang, 2023).…”
Section: Introductionmentioning
confidence: 99%
“…In the construction operation and management phase, companies generate fewer carbon emissions in future construction activities by applying industrial IoT to collect past data from the construction process and using digital twin architecture to monitor real-time architectural situations (Shen et al, 2022) to compose models and predict their future behavior (Metallidou et al, 2022). Finally, the application of digital construction technology can enhance the ability of information interaction and sharing within enterprises, such as the use of data creation and sharing, cross-temporal information dissemination and other channels to transmit, flow green emission reduction technology and other aspects of information (Lyu et al, 2023), for the purpose of reducing unnecessary activities, in addition, big data technology can offer data support for enterprise carbon emission reduction by improving the integration of data information such as energy input structure and CO 2 emissions (Zhang et al, 2021). Based on the above, a hypothetical H1 is proposed.…”
Section: Digital Construction and Carbon Emissionsmentioning
confidence: 99%