Xinzao Huang

Promoting low-carbon, green development in the industrial sector is crucial for the sustainable development of the economy and society in China. As the micro-entity of industrial carbon reduction, the question of how to enhance the carbon reduction capacity of industrial enterprises has attracted widespread attention. Research suggests that a multidimensional relationship network, consisting of government, market, industry, and public networks and network reputation, significantly influences enterprises’ carbon emission performance. Based on the survey data of 1226 manufacturing enterprises, this study empirically examines the impact of multidimensional relationship network on the carbon emissions of enterprises and its mechanism from a micro-perspective. The findings reveal that relational network embedding significantly reduces the carbon emission intensity, and the reduction effect becomes stronger as the embedding degree increases. Compared to the government and industry networks, the market network, public network, and network reputation have a more significant impact on carbon emission reduction. The heterogeneity analysis shows that the reduction effect is more significant in enterprises with a higher carbon emission intensity and digital level. The mechanism analysis also highlights the role of technological innovation as a mediator and regulator in strengthening the carbon emission reduction effect of relationship network embedding.

Fertilizer carbon emissions contribute the largest proportion to agricultural carbon emissions in China, while the extension of low-carbon fertilization technologies (LCFTs) is an effective measure to address this issue. Research suggests that the relational networks surrounding farmers significantly influence their carbon reduction behavior. This study conducted a field survey of 239 large-scale grain producers in August 2022 on China’s Poyang Lake Basin, which is the nation’s largest freshwater lake and a vital agricultural production area. Using cross-sectional data, probit and ordered probit models were employed to analyze the impacts of multidimensional relational networks (market, government, and social networks) on the adoption of LCFTs by large-scale grain producers. Additionally, a mediating-effect model was used to examine the pathways through which relational networks influence LCFT adoption. The findings indicated that relational networks not only increased the likelihood of large-scale grain producers adopting LCFTs but also enhanced the intensity of adoption. However, the effects of different relational networks on low-carbon behavior varied. The market network exerted the most prominent influence on LCFT adoption, followed by the social and government networks. A mediation analysis identified information sharing, demonstration effects, and resource guarantees as the mediating pathways between multidimensional relational networks and LCFT adoption by large-scale grain producers. Furthermore, a heterogeneity analysis revealed that the effects of multidimensional relational networks on LCFT adoption differed across generations and carbon intensity levels. The impact was greater among older grain producers than the younger generation, and those in the high-carbon-intensity group exhibited a stronger incentive compared to the medium- and low-carbon-intensity groups.

The China-ASEAN Free Trade Area (FTA), as the first FTA constructed in China, is an important initiative for China's industries to participate in the global division of labour and cooperation. This paper adopts the bibliometric analysis software ciespace from the technical level and summarizes the existing impact of China-ASEAN free trade agreement on the upgrading of China's industrial structure and its path, and prospects the opportunities and challenges brought by RCEP to China's industrial structure. Specifically, based on the CiteSpace metrology analysis softwarebased on Citespace analysis, the paper searches the literature on China-ASEAN FTA from two major databases, CNKI and Web of since, to sort out the research trends on China-ASEAN FTA and summarise the industrial clustering and industrial transfer effects of China-ASEAN FTA. Secondly, the path of the impact of the China-ASEAN FTA on the industrial structure is summarised, and the general view is that the trade effect as well as the tariff effect of the FTA will promote the optimisation of the industrial structure. Finally, we analyse how the upgraded FTA agreement RCEP will bring opportunities and challenges for China's industrial structure upgrading.