Search Results (63)

China has identified the high-quality development of its green manufacturing transition as the top priority for upgrading their industrial structure system which will lead to the sustainable development of an innovation ecosystem. To assess their progress in this area, this study selects the panel data of 31 provinces in China from 2011 to 2021 and constructs an evaluation index system for the green transformation of the manufacturing industry from four dimensions: environment, resources, economy, and industrial structure. This not only comprehensively and systematically reflects the dynamic changes in the green transformation of the manufacturing industry but also addresses the limitations of currently used indices. The entropy value method is used to calculate the comprehensive score of the green transformation of the manufacturing industry, while the key factors influencing the convergence of the green transformation of the manufacturing industry are further explored. The results show that first, the overall level of the green transformation of the manufacturing industry has significantly improved as evidenced by an approximate 32% increase. Second, regional differences are significant with the eastern region experiencing significantly higher levels of transformation compared to the central and western regions, along with a decreasing trend from the east to the central and western regions. From a policy perspective, the findings suggest that tailored production methods for each region should be adopted with a greater emphasis on knowledge exchanges to promote green transition in less developed regions. In addition, further regulations are required which, in part, focus on increasing the degree of openness to the outside world to promote the level of green manufacturing transition. Full article

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article

This study investigates the role of the digital economy (DE) in advancing the high-quality development of manufacturing in China, with a particular focus on the moderating effects of manufacturing agglomeration and digital literacy. Using provincial panel data from 2013 to 2023, we find that the digital economy significantly enhances manufacturing development across three key dimensions: green transformation, innovation, and high-end industrial upgrading. Manufacturing agglomeration strengthens this effect, especially in the Eastern and Western regions, by facilitating digital spillovers and leveraging digital infrastructure. However, in the Central region, the impact of agglomeration is weaker, hindered by fragmented industrial clusters and underdeveloped digital infrastructure. The study also highlights significant regional differences in the moderating effect of digital literacy. In the Eastern region, digital literacy negatively moderates the relationship between DE and manufacturing development due to skill mismatches, while in the Western region, localized concentrations of digital skills have a positive but geographically constrained impact. Temporal analysis reveals a shift in the moderating role of digital literacy, with its negative effect becoming more pronounced after 2018, suggesting a growing need for targeted skill development policies. These findings underscore the importance of regionally tailored strategies to promote digital manufacturing integration, with a focus on sustainable development through digital transformation and green manufacturing practices. Full article

Environmental regulation has become a central policy tool for reconciling the tensions between ecological sustainability and industrial development. Although most existing studies focus on its impact on green innovation or firm behavioral change, attention to how environmental regulation affects the structural resilience of manufacturing systems under external shocks remains limited. This paper constructs a balanced panel dataset covering 287 prefecture-level cities in mainland China from 2006 to 2021 to quantify the impact of environmental regulation intensity on the resilience of manufacturing development. Manufacturing resilience is assessed through a comprehensive indicator system, including the dimensions of adaptive capacity, recovery potential, and industrial continuity. The empirical results show that environmental regulation has a significant inhibitory effect on manufacturing resilience, and this effect is supported in a number of robustness analyses using instrumental variable estimation and lagged structural tests. Mechanism analysis suggests that, despite the overall negative effect, environmental regulations can indirectly enhance resilience performance by promoting industrial autonomy and digital transformation under certain conditions. Heterogeneity analysis further reveals that the negative effect is more pronounced in regions with higher regulatory intensity, in non-self-employed firms, in industries not subject to U.S. sanctions, and in eastern China. These findings suggest that the dynamic needs of the industrial system should be taken into account in the formulation of environmental policies, and that digital capacity building and autonomy upgrading should be the key paths to mitigate regulatory shocks. Full article

Under the impetus of the global urbanization, the synergistic relationship between smart city policies and green innovation capabilities has emerged as a critical agenda for achieving sustainable development goals. While existing studies have explored the techno-economic effects of smart cities, systematic evidence remains scarce regarding their pathways and heterogeneous impacts on green growth. This study investigates the influence of smart city pilot policies on urban green growth trajectories and their heterogeneous characteristics. Leveraging panel data from 293 Chinese prefecture-level cities, we employ a multi-period difference-in-differences (DID) model with two-way fixed effects to control for unobserved city-specific and time-specific factors, complemented by robustness checks including parallel trend tests, placebo tests, and alternative dependent variable specifications. Data sources encompass the China City Statistical Yearbook, CNRDS, and CSMAR databases, covering core metrics such as green patent applications and grants, industrial upgrading indices, and environmental regulation intensity, with missing values being addressed via mean imputation. The findings demonstrate that smart city pilot policies significantly enhance green innovation levels in treated cities, with effects exhibiting pronounced spatial and resource-based heterogeneity; there are notably stronger impacts in non-resource-dependent cities and eastern regions. Mechanism analysis shows that policies are driven by a dual effect of industrial upgrading and environmental regulation. The former is manifested by the high substitution elasticity of the digital economy for traditional manufacturing, while the latter is reflected in the rising compliance costs of polluting enterprises. This research advances a cross-nationally comparable theoretical framework for understanding green transition mechanisms in smart city development while providing empirical benchmarks for policy design in emerging economies. Full article

Enhancing residents’ green consumption is essential to fostering high-quality economic advancement. This study constructs an indicator system for residents’ green consumption based on three subsystems: green manufacturing processes, sustainable lifestyles, and environmental ecosystems. A regression model analyzes how public environmental concern affects residents’ green consumption, using panel data from 30 provinces and cities in China over the period 2011–2023. Additionally, analyses of mechanisms and heterogeneity are carried out. The study results are presented below: First, public environmental concern (PEC) can significantly enhance residents’ green consumption (RGC), with an increase of 1% in PEC leading to a 0.261% rise in RGC. Second, green technological innovation (GTI) and market-based incentive environmental regulation (MER) mediate the relationship between PEC and RGC. However, the role of command-and-control environmental regulation (CER) as a mediator is insignificant. Third, there is heterogeneity in RGC based on region, pollution emissions, and innovation foundations. The impact of PEC is notably greater in central-western regions, areas with higher pollution emissions, and regions with better innovation foundations. Therefore, this study proposes policy recommendations from three aspects: improving public environmental concern, strengthening green technological innovation in enterprises, and formulating region-specific industrial upgrading paths to promote residents’ green consumption. Full article

China’s equipment-manufacturing industry accounts for a significant portion of its total carbon emissions. While intelligent equipment optimization has been found to be an effective way of reducing carbon emissions, understanding of its mechanisms remains limited. This paper takes the equipment-manufacturing industry as an example to explore the mechanisms and pathways for enhancing carbon emissions efficiency through intelligent equipment optimization. Using panel data from 243 equipment-manufacturing firms, the analysis identified a nonlinear, U-shaped relationship between intelligent equipment upgrades and carbon emissions efficiency. At the initial stage of intelligent upgrading of equipment, efficiency declines due to the high capital expenditures required for upgrading and integrating advanced systems. However, as these technologies become more integrated into production processes, carbon emissions efficiency improves significantly. This study also examines the mediating role of cost-saving effects and the moderating influence of energy intensity in this relationship. The effect of intelligent transformation on improving carbon emissions efficiency is more significant in high-energy-intensity enterprises. The findings suggest that intelligent equipment optimization not only enhances resource-utilization efficiency but also supports green and low-carbon transitions in equipment-manufacturing enterprises. These insights offer valuable guidance for policymakers and industry leaders aiming to further integrate intelligent manufacturing with carbon reduction strategies. Full article

In the global pursuit of sustainable development and climate change mitigation, reconciling export growth with environmental protection has emerged as a universal challenge. As the world’s largest developing economy, China has traditionally relied on a resource-intensive development model to fuel rapid foreign trade growth. However, this extensive growth pattern has not only led to environmental pollution domestically but has also encountered hurdles from international green trade barriers. Finance, as a key driver of stable economic growth, plays a pivotal role in achieving high-quality trade development. Against this backdrop, the Chinese government has introduced the green credit interest subsidies policy. This policy aims to coordinate government financial resources and guide capital toward green production, alleviating financing constraints and fostering the upgrading of export product quality. Utilizing data from the World Bank, China Customs statistics, and provincial panels from 2011 to 2020, this study employs a multi-period difference-in-differences (DID) model to examine the causal impact of the green credit subsidies policy on efforts to upgrade the export quality of green products across China’s regions. The benchmark regression results indicate that the green credit interest subsidies policy has significantly improved the export quality of green products across China’s manufacturing industries. Heterogeneity analysis shows that this policy has had a more pronounced positive impact on green product quality in industries with quality-based competition strategies, in regions with well-coordinated local finance and financial policies, as well as in countries that have concluded environmental clauses with China. Mechanism analysis reveals that, on the export side, the policy enhances green product quality by easing financing constraints, increasing green credit, boosting productivity, and upgrading industrial structures. On the import side, the policy promotes green product quality by expanding the scale, variety, and quality of green intermediate goods. This research offers valuable insights for developing countries aiming to establish export-oriented green transformation and upgrading strategies. Full article

In the era of new productive forces, the efficient utilization of industrial land in high-tech zones is critical for fostering technological innovation, intelligent manufacturing, and green development. However, constrained by limited land reserves, inefficient stock utilization, and sluggish industrial upgrading, high-tech zones must establish a scientific early warning mechanism for industrial land redevelopment. This study constructs a four-tier early warning system (normal, alert, warning, and response) based on three key dimensions: enterprise life cycle, enterprise–park compatibility, and industrial land use efficiency. Using the Jinan High-Tech Zone as a case study, this study conducts an empirical analysis of 360 industrial land parcels from 2020 to 2022, employing DEA, fixed effects models, GIS visualization, and MCDA methods. The results indicate a strong correlation between enterprise life cycle and land use efficiency, with significant spatial differentiation in enterprise–park compatibility. Efficient land use is concentrated in areas with well-defined functions and high industrial agglomeration. This study identifies 360 land use scenarios, with 12% classified as normal, 28% requiring monitoring, 52% requiring optimization, and 8% necessitating redevelopment. Based on these findings, a “warning–monitoring–regulation” closed-loop management model is proposed, providing decision-making support for dynamic land optimization and sustainable development in high-tech zones. Full article

The global and domestic divisions of labor have had a great influence on the economy and environment in China during the last decade. With the refinement of production processes, national value chains (NVCs) coexist with global value chains (GVCs), enabling regions to participate in dual value chains (DVCs) simultaneously. This study calculates the NVCs and GVCs participation of manufacturing sectors in China’s provinces. On this basis, this research adopts a fixed effects model to analyze the impact of GVCs and NVCs participation and their interaction effect on manufacturing upgrades and green development. The results show, first, that significant regional differences in GVCs participation exist among provinces in China. In comparison, provincial NVCs participation demonstrates fewer regional differences. Second, there are significant sectoral differences of GVCs participation in China’s manufacturing industry—high-tech manufacturing is more embedded than other manufacturing industries. The sectoral differences in NVCs participation are relatively small. Third, GVCs and NVCs participation and their interaction effect have significantly promoted the upgrading and green development of manufacturing sectors in provinces of China, and this impact exhibits significant heterogeneity across regions, industries, and NVCs participation modes. The conclusions of this study provide empirical evidence and policy recommendations for the upgrading and green development of China’s manufacturing industry. Full article

Against the backdrop of the “dual carbon” goals, the transformation and upgrading of the manufacturing industry play a crucial role in achieving the dual objectives of controlling both total carbon emissions and carbon intensity. This study first defines the connotation of the integrated development of high-end, intelligent, and green manufacturing (referred to as “Three Modernization”) and constructs a conceptual framework illustrating its impact mechanisms on carbon emission dual control, with particular emphasis on intermediary pathways such as technological progress and energy structure optimization. Subsequently, based on provincial panel data from China covering the period 2009–2023, this paper employs fixed effects and spatial Durbin models to empirically examine the impact of the integrated development of “Three Modernization” on total carbon emissions and carbon emission intensity. The results show that the integration of high-end, intelligent, and green manufacturing significantly suppresses carbon emissions, with a more pronounced effect observed in economically developed regions. Mechanism tests further reveal that technological innovation enhances the application capacity of low-carbon technologies, while an increased share of clean energy usage effectively reduces reliance on fossil fuels, thereby indirectly facilitating the realization of the dual control targets. The spatial effect analysis indicates that the integration of “Three Modernization” exhibits significant spatial spillover effects, whereby regional synergies contribute to improved carbon reduction performance in neighboring areas. Furthermore, threshold model analysis confirms a notable nonlinear relationship moderated by technological complexity: when technological complexity is at a lower level, the emission-reduction effect of the “Three Modernization” integration is more substantial; however, once a certain threshold is exceeded, the marginal abatement effect diminishes, suggesting that in high-technology phases, the carbon-reduction efficiency of additional technological inputs declines. This nonlinear pattern indicates an inverted U-shaped relationship between the “Three Modernization” integration and carbon emission control. Therefore, differentiated dual control policies should be formulated to promote the region-specific integration of high-end, intelligent, and green development in manufacturing. This should be accompanied by continuous enhancement of technological innovation and green technology adoption, along with energy structure optimization, to ensure the sustainability of both total carbon emission control and intensity reduction. Full article

The semiconductor industry is essential to information technology and the ongoing artificial intelligence transformation but also poses significant environmental challenges, including greenhouse gas emissions, air pollution, solid waste, and high water and energy consumption. This review identifies key emission sources in semiconductor manufacturing, focusing on the release of fluorinated gases from chemical-intensive processes and the sector’s substantial energy demands. We evaluate the effectiveness and limitations of current mitigation strategies, such as process optimization, clean energy adoption, and material substitution. We also examine supply chain interventions, including green procurement, logistics optimization, and intelligent management systems. While technological innovation is crucial for the sustainable transition of the global semiconductor industry, the high cost of upgrading to greener production processes remains a major obstacle. Despite progress in clean energy integration and material alternatives, significant challenges persist in reducing emissions across the entire value chain. This review underscores an urgent need for collaborative, integrated approaches to drive the sustainable transition of the semiconductor sector and its upstream supply chain. Full article

Fiber-reinforced resin composites (FRRCs) are widely used in several fields such as construction, automotive, aerospace, and power. Basalt fiber (BF) has been increasingly used to replace artificial fibers such as glass fiber and carbon fiber in the production of BF-reinforced resin matrix composites (BFRRCs). This preference stems from its superior properties, including high temperature resistance, chemical stability, ease of manufacturing, cost-effectiveness, non-toxicity, and its natural, environmentally friendly characteristics. However, the chemical inertness of BF endows it with poor compatibility, adhesion, and dispersion in a resin matrix, leading to poor adhesion and a weak BF–resin interface. The interfacial bonding strength between BF and resin is an important parameter that determines the service performance of BFRRC. Therefore, the interfacial bonding strength between them can be improved through fiber modification, resin–matrix modification, mixed enhancers, etc., which consequently upgrade the mechanical properties, thermodynamic properties, and durability of BFRRC. In this review, first, the production process and properties of BFs are presented. Second, the mechanical properties, thermodynamic properties, and durability of BFRRC are introduced. Third, the modification effect of the non-destructive surface-modification technology of BF on BFRRC is presented herein. Finally, based on the current research status, the future research direction of BFRRC is proposed, including the development of high-performance composite materials, green manufacturing processes, and intelligent applications. Full article

The coordinated development of digitalization and greening is essential for economic transformation and upgrading, especially given the pressing global carbon emission challenges. China’s commitment to achieving “dual carbon” goals highlights the need for sustainable solutions, particularly in the manufacturing sector, which is a significant source of energy consumption and emissions; carbon emissions account for more than 30%. Integrating advanced digital technologies with manufacturing is critical for reducing carbon and sustainable growth. According to the research results, more than 70% of scholars believe that digital transformation boosts green innovation and low-carbon development, but the mechanisms still need to be clarified, slowing transformation efforts and reducing efficiency. Taking the intellectualization and green low-carbon development of manufacturing enterprises as latent variables, and taking the nine paths obtained by scholars’ research results and investigation interviews to promote green low-carbon performance as observation variables, this paper constructs a structural equation model and deeply explores the mechanism and paths of the intellectualization transformation of manufacturing enterprises affecting carbon reduction, emission reduction and sustainable development of enterprises. The research results show that the digital intelligent transformation of manufacturing enterprises affects the green and low-carbon performance improvement and sustainable development of enterprises through technological innovation, industrial structure transformation and upgrading, and reshaping resource allocation. These strategies lower energy use and emissions, strengthen sustainability, and improve green performance. The findings offer theoretical and practical insights, providing a roadmap for efficient digital transformation in manufacturing to achieve the “dual carbon” goals and support sustainable development. Full article

With the advancement of global sustainable development goals and the introduction of the ‘dual-carbon’ strategy, intelligent manufacturing (IM) has become an important pathway to promote the transformation and upgrading of enterprises. However, the ways in which IM enhances environmental, social, and corporate governance (ESG) performance, along with its potential mechanisms, remain unexplored. This study employs a two-way fixed-effects model with panel data from 4417 Chinese listed firms spanning the period 2009–2022 to examine these relationships. It is found that IM significantly improves corporate ESG performance. Robustness tests confirm the reliability of these results, and mechanism analysis highlights the mediating effects of information transparency, green technology innovation, and supply chain collaborative innovation. Furthermore, the heterogeneity analysis indicates that IM has a notably stronger effect in high-carbon-emission sectors, state-owned enterprises, and high-tech industries. This suggests that policymakers should design differentiated policies based on industry and firm characteristics to promote the adoption of IM and foster sustainable development strategies. This research contributes to expanding the theoretical understanding of how IM affects ESG while also providing empirical evidence for enterprises and governments to promote green transformation. Full article