Search Results (2,959)

Improving carbon emission efficiency (CEE) is crucial for coordinating economic development and reducing carbon emissions. Drawing on panel data for 30 provinces in China from 2013 to 2022, this paper selects six key antecedent conditions guided by the Technology–Organization–Environment (TOE) framework. Then the dynamic qualitative comparative analysis (DQCA) is employed to explore CEE improvement pathways from a configurational perspective, and regression analysis is used to compare the driving effects of different pathways. The findings reveal that (1) single factors cannot independently achieve high CEE; instead, multiple factors must work synergistically to form various improvement pathways, including “technology–organization dual-driven”, “environment-dominated”, and “multi-equilibrium” pathways, with industrial structure upgrading as the core factor for improving CEE; (2) temporally, these improvement pathways demonstrate universality, while, spatially, they exhibit significant provincial heterogeneity; and (3) in terms of marginal effects, the “multi-equilibrium” pathway has the strongest driving effect on CEE. The findings provide valuable policy implications for developing targeted CEE enhancement strategies across provinces at different developmental stages. Full article

Common prosperity serves as a pivotal condition for achieving sustainable development by fostering social equity, bolstering economic resilience, and promoting environmental stewardship. Differential land revenue, as a crucial form of property based on spatial resource occupation, significantly contributes to the achievement of common prosperity, though empirical evidence of its impact is limited. This study explores the potential influence of land utilization revenue disparity on common prosperity from the perspective of urban macro differential rent (UMDR). Utilizing panel data from 280 Chinese cities spanning 2007 to 2020, we discover that UMDR and common prosperity levels exhibit strikingly similar spatiotemporal evolution. Further empirical analysis shows that UMDR significantly raises urban common prosperity levels, with a 0.217 standard unit increase in common prosperity for every 1 standard unit rise in UMDR. This boost stems from enhanced urban prosperity and the sharing of development achievements, encompassing economic growth, improved public services, enhanced ecological civilization, and more equitable distribution of development gains between urban and rural areas and among individuals. Additionally, we observe that UMDR has a more pronounced effect on common prosperity in eastern cities and those with a predominant service industry. This study enhances the comprehension of the relationship between urban land revenue disparities, prosperity, and equitable sharing, presenting a new perspective for the administration to contemplate the utilization of land-based policy tools in pursuit of the common prosperity goal and ultimately achieve sustainable development. Full article

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

This article investigates the macroeconomic and labor market conditions that shape the adoption of artificial intelligence (AI) technologies among large firms in Europe. Based on panel data econometrics and supervised machine learning techniques, we estimate how public health spending, access to credit, export activity, gross capital formation, inflation, openness to trade, and labor market structure influence the share of firms that adopt at least one AI technology. The research covers all 28 EU members between 2018 and 2023. We employ a set of robustness checks using a combination of fixed-effects, random-effects, and dynamic panel data specifications supported by Clustering and supervised learning techniques. We find that AI adoption is linked to higher GDP per capita, healthcare spending, inflation, and openness to trade but lower levels of credit, exports, and capital formation. Labor markets with higher proportions of salaried work, service occupations, and self-employment are linked to AI diffusion, while unemployment and vulnerable work are detractors. Cluster analysis identifies groups of EU members with similar adoption patterns that are usually underpinned by stronger economic and institutional fundamentals. The results collectively suggest that AI diffusion is shaped not only by technological preparedness and capabilities to invest but by inclusive macroeconomic conditions and equitable labor institutions. Targeted policy measures can accelerate the equitable adoption of AI technologies within the European industrial economy. Full article

Evaluating the renewable energy potential, such as that of solar photovoltaics (PV), is important for developing renewable energy policies. This study investigated rooftop solar PV potential in Thailand based on open-source geographic information system (GIS) building footprints, solar PV power output, and the most recent land use data (2022). GIS-based overlay analysis, buffering, fishnet modeling, and spatial join operations were applied to assess rooftop availability across various building types, taking into account PV module installation parameters and optimal panel orientation. Economic feasibility and sensitivity analyses were conducted using standard economic metrics, including net present value (NPV), internal rate of return (IRR), payback period, and benefit–cost ratio (BCR). The findings showed a total rooftop solar PV power generation potential of 50.32 TWh/year, equivalent to 25.5% of Thailand’s total electricity demand in 2022. The Central region contributed the highest potential (19.59 TWh/year, 38.94%), followed by the Northeastern (10.49 TWh/year, 20.84%), Eastern (8.16 TWh/year, 16.22%), Northern (8.09 TWh/year, 16.09%), and Southern regions (3.99 TWh/year, 7.92%). Both commercial and industrial sectors reflect the financial viability of rooftop PV installations and significantly contribute to the overall energy output. These results demonstrate the importance of incorporating rooftop solar PV in renewable energy policy development in regions with similar data infrastructure, particularly the availability of detailed and standardized land use data for building type classification. Full article

This study uses financial data from 872 Chinese listed companies (2018–2022). It tests the triple dividend effect and threshold effect of China’s environmental protection tax (EPT) using high-dimensional fixed effects models and panel threshold models. We document that (1) EPT creates an environmental dividend for Chinese listed companies. It significantly reduces pollution emissions. A 1-unit tax increase reduces LnTPPE by 2.5%. (2) EPT creates a significant innovation dividend. It forces enterprises to improve the quality of authorized patents. A 1-unit tax increase raises patent technological complexity by 0.79%. (3) EPT creates an economic dividend. It significantly improves firm performance. A 1-unit tax increase raises relative corporate revenue by 38.1%. (4) EPT exerts significant threshold effects on micro-level triple dividend outcomes among Chinese listed companies. A heterogeneity analysis shows significant differences in threshold effects between non-heavily polluting and heavily polluting industries. This study confirms that China’s EPT generates a micro-level triple dividend effect alongside coexisting threshold effects for listed companies. This provides literature references for China to design and implement differentiated policies and offers a quantitative empirical case for implementing globally sustainable EPT strategies. Full article

Green innovation is a critical driver of sustainable development, yet it often faces efficiency challenges in rapidly industrializing economies. This study investigates the effect of China’s Circular Economy Demonstration Policy (CEDP) on urban green innovation efficiency (GIE) using city-level panel data from 2010 to 2021. Employing a difference-in-differences (DID) approach, we find that CEDP significantly enhances GIE, with the policy effect becoming statistically significant after a three-year lag and accumulating over time. Robustness tests, including placebo analyses, alternative dependent variables, and propensity score matching, confirm the validity of the results. Mechanism analysis reveals that the policy improves green innovation primarily by reducing capital distortion, promoting market integration, and enhancing resource allocation efficiency. Further heterogeneity analyses show that the positive effects are stronger in central cities, capital cities, and eastern regions, reflecting the role of local economic and institutional conditions. The study concludes with policy implications emphasizing regionally tailored implementation, capacity building, and long-term commitment to maximize green innovation outcomes. Full article

Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO₂e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO₂e/ha) and 2014 (6.52 × 10⁷ t CO₂e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article

Recently, a number of natural biologically active substances have been proven to be attractive alternatives to conventional anticancer medicine or as adjuvants in contemporary combination therapies. Although lignin-based materials were previously accepted as waste materials with limited usefulness, recent studies increasingly report the possibility of their use for novel applications in various industrial branches, including biomedicine. In this regard, the safety, efficiency, advantages and limitations of lignin compounds for in vitro/in vivo applications remain poorly studied and described. This study was carried out to investigate the possibility of using newly synthesized, alkali lignin-based micro-/nano-biopolymer formulations (Lignin@Formulations/L@F) as carriers for substances with antioxidant and/or anticancer effectiveness. Moreover, we tried to assess the opportunity for using an electro-assisted approach for achieving improved intracellular internalization. An investigation was conducted on an in vitro panel of breast cell lines, namely two breast cancer lines with different metastatic potentials and one non-tumorigenic line as a control. The characterization of all tested formulations was performed via DLS (dynamic light scattering) analysis. We developed an improved separation procedure via size/charge unification for all types of Lignin@Formulations. Moreover, in vitro applications were investigated. The results demonstrate that compared to healthy breast cells, both tested cancer lines exhibited slight sensitivity after treatment with different formulations (empty or loaded with antioxidant substances). This effect was also enhanced after applying electric pulses. L@F loaded with Quercetin was also explored only on the highly metastatic cancer cell line as a model for the breast cancer type most aggressive and non-responsive to traditional treatments. All obtained data suggest that the tested formulations have potential as carriers for the electro-assisted delivery of natural antioxidants such as Quercetin. Full article

In this study, we examine the impact of mergers and acquisitions (M&As) on firm environmental performance, aiming to address the gap in research and guide firms, investors, and policymakers toward more environmentally conscious decision-making in M&A. Using panel data from Chinese A-share listed firms (2008–2022), we estimate a two-way fixed effect model. The Propensity Score Matching and the instrumental variable method address potential endogeneity concerns, and robustness checks validate the findings. We found that M&As have a significantly positive effect on firm environmental performance, with heterogeneous impacts across regions, industries, and M&A types. The environmental benefits are most pronounced in heavily polluting industries and hybrid M&A deals. Eastern China shows more modest improvements. The results of mechanism tests revealed that M&As enhance environmental performance primarily by boosting total factor productivity and fostering innovation. This study offers a novel perspective by linking M&A activities to environmental sustainability, enriching the literature on both M&As and corporate environmental performance. We show that even conventional M&A deals (not sustainability-focused) can improve environmental performance through operational synergies. Expanding beyond polluting industries, we reveal how sector characteristics shape M&A’s environmental impacts. We identify practical mechanisms through which standard M&A activities can advance sustainability goals, helping firms balance economic and environmental objectives. It provides empirical evidence from China, an emerging market with distinct institutional and regulatory contexts. The findings offer guidance for firms engaging in M&A to strategically improve sustainability performance. Policymakers can leverage these insights to design incentives for M&A in pollution-intensive industries, aligning economic growth with environmental goals. By demonstrating that M&As can enhance environmental outcomes, this study supports the potential for market-driven mechanisms to contribute to broader societal sustainability objectives, such as reduced industrial pollution and greener production practices. Full article

Recent theoretical and empirical studies highlight that information asymmetry and owner–manager conflict of interest can distort corporate investment decisions. Building on this premise, we hypothesize that superior environmental, social, and governance (ESG) performance mitigates these frictions by (H1) alleviating financing constraints and (H2) intensifying external analyst scrutiny. To test these hypotheses, we examine all Shanghai and Shenzhen A-share non-financial firms from 2009 to 2023. Using panel fixed-effects and two-stage least squares with an industry–province–year instrument, we find that higher ESG performance significantly reduces investment inefficiency; the effect operates through both lower financing constraints and greater analyst coverage. Heterogeneity analyses reveal that the improvement is pronounced in small non-state-owned, non-high-carbon firms but absent in large state-owned high-carbon emitters. These findings enrich the literature on ESG and corporate performance and offer actionable insights for regulators and investors seeking high-quality development. Full article

This study examines the complex relationship between environmental, social, and governance (ESG) and financial performance in the automotive industry, with a particular focus on how financial constraints shape this relationship. Using a global data set for the period 2008 to 2023 and employing a range of panel data techniques, including those addressing endogeneity concerns, we find that higher ESG scores positively affect financial performance. Specifically, a one-point rise in ESG score corresponds to an estimated 1–1.7% increase in the market-to-book ratio, with the effect reaching approximately 1.6% for firms facing financial constraints. These findings highlight the economic significance of ESG engagement, particularly for resource-constrained companies. The novelty of this study is that it focuses on the automotive sector, an industry with limited ESG-specific research, and that it makes a theoretical contribution by linking ESG performance outcomes to financial constraints, an angle largely overlooked in prior research. The findings offer critical policy insights, emphasizing the strategic importance of ESG initiatives for value creation under varying financial conditions. Full article

This study endeavors to elucidate the mechanisms and pathways through which the digital economy shapes agricultural green development, providing theoretical underpinnings and practical guidance for the green transformation of regional agriculture. (1) Using panel data from 18 prefecture-level cities in Sichuan Province (2013–2022), a comprehensive evaluation index system for agricultural green development was formulated. Fixed-effects, mediating-effects, and threshold-effects models were employed to systematically analyze the direct effects, transmission pathways, and nonlinear characteristics of the digital economy on agricultural green development. (2) The fixed-effects model shows that the digital economy markedly propels agricultural green development in Sichuan Province. The mediating-effects model verifies two transmission pathways: “digital economy → technological progression → agricultural green development” and “digital economy → industrial structure upgrading → agricultural green development”. The threshold-effects model suggests that when the digital economy is in the low-threshold interval, it exerts a suppressive impact on agricultural green development; however, once the threshold is surpassed, its promoting effect strengthens significantly. (3) The results demonstrate the following findings: First, the digital economy exerts a significant positive effect on agricultural green development. Second, this promoting effect exhibits significant nonlinear characteristics that vary with the level of digital economy development. Third, the impact manifests remarkable regional heterogeneity, necessitating context-specific development strategies. (4) Five optimization recommendations are proposed: promote the categorized development of agricultural digital technologies and industrial upgrading; advance digital infrastructure and technology adaptation in phases; design differentiated regional policies; establish a hierarchical and classified long-term guarantee mechanism; and strengthen the “industry-university-research-application” collaborative innovation and dynamic monitoring system. 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

As an important direction in industrial evolution, the synergistic agglomeration of manufacturing and productive service industries has become a key path to promote the green transformation of the economy. Based on China’s provincial panel data, this study utilizes a variety of econometric methods to explore in depth the mechanisms, spatial effects and regional differences in the impact of the synergistic agglomeration of manufacturing and productive service industries on the green, low-carbon and recycling development of the economy. The empirical results show that the synergistic agglomeration of manufacturing and productive services not only directly promotes the green, low-carbon and recycling development of the economy, but also generates an indirect impact through the intermediary channel and exhibits significant spillover characteristics in the spatial dimension. This conclusion holds firm after a series of robustness tests. In addition, environmental regulations and the level of regional industrialization play a moderating role on the impact of industrial synergistic agglomeration and green, low-carbon and recycling development of the economy, and the effect of the role varies across regions and levels of economic development. This paper provides a decision-making reference for further optimizing the regional layout of China’s industries and enhancing the green, low-carbon and recycling development of the economy in each province. Full article