The threat of global climate change has encouraged the international community to pay close attention to the levels of greenhouse gases, such as carbon dioxide, in the atmosphere. China has the world’s largest metal smelting industry, which is a major energy-consuming and carbon-emitting industry. Thus, this industry’s low-carbon transition is of great significance. Carbon emission efficiency (CEE) is a key indicator for the metal smelting industry to prioritize sustainable development. This paper applies a three-stage data envelopment analysis model with undesirable outputs to estimate CEE for 30 provinces from 2005 to 2020 in China, and analyzes the influencing factors using a spatial Durbin model. The results show that the CEE level generally improved in all Chinese provinces during the sample period, but the average CEE in the eastern region was 1.05 compared to 1.07 in the western and central regions, with the latter two regions progressing faster in terms of low carbon production capacity. The national average Malmquist–Luenberger (ML) index demonstrates a significant increase in technical efficiency across regions in 2010 and 2017, peaking in 2017. The study also suggests that current green credit and environmental regulations are not effective in promoting CEE improvements in the metal smelting industry, and that existing policies should be modified. Moreover, the spatial regression results indicate that the cross-regional transfer of low-carbon production technologies in China is largely complete. This study provides a more objective evaluation of the CEE levels of metal smelting across China, providing the government with a new perspective to guide the green transformation of energy-intensive industries.
With the development and application of digital technology, the digital economy industry has gradually become the new vitality of China’s economic growth, and it has also become a vital driving force to promote a change in the GVC division of the manufacturing industry. This paper takes the embedded position of the GVC in the Chinese manufacturing industry as the research object, places the input level of the digital economy in the manufacturing industry into the analysis framework of the influence of its embedded position in the GVC, puts forward the theoretical mechanism of the influence of the input level of the digital economy on the relative breadth and height of its embedded position in the GVC, and explores the influence of the digital economy on the embedded position of the GVC in the Chinese manufacturing industry from the two levels of relative height and width. Through regression analysis, an intermediary effect test, and threshold regression of panel data, the study found that (1) improving the input level of the digital economy in manufacturing will positively affect the relative height and breadth of the GVC embedding position. (2) The improvement of the input level of the digital economy plays a role through two mechanisms: improving the innovation efficiency of the manufacturing industry, and improving the asset utilization efficiency of the manufacturing industry. The relative height and breadth of the embedded position of the GVC can be promoted through innovative efficiency channels. The captive allocation efficiency channel can promote the relative breadth of the embedded position of the GVC. (3) The influence of the input level of the digital economy on the relative breadth and height of the embedded position of the GVC presents a threshold effect with the technical level, and the influence on the relative height presents a threshold effect with the capital level. By clarifying the influence of the digital economy’s input level on the embedded position of the GVC, some suggestions can be taken to promote the manufacturing industry to move to a high-value acquisition position in the GVC division. Construction can be strengthened from the following aspects: improving the application level of digital technology in the manufacturing industry, strengthening the construction of digital infrastructure, and promoting the innovation system and industrial ecology led by digital technology.
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