Search Results (330)

Several successive crises during the first three decades of the third millennium created the premises for a world that, after expanding international relations, entered a new reality of slowbalization or deglobalization, shaping new development paradigms for national economies. In this context, where economic activity remains highly sensitive to energy market disruptions and strategic resource constraints, nations seek new opportunities to reduce their foreign dependencies through energy diversification and a green transition. Nations are seeking strategies to leverage their advantages and moderate their weaknesses. This research evaluates the relationship between energy-related features and economic growth in a complex context, describing dependency on foreign markets. Furthermore, the study discusses the effects of a selection of variables describing the green transition (energy import dependency, energy diversification, and the share of renewable energy) on economic growth. The data covers the period between 1995 and 2024 for 25 European countries. The study uses cross-sectionally ARD (CS-ARDL) for the main empirical analysis and augmented mean group (AMG) to check the robustness of the main results. Furthermore, the method of moments quantile regression (MMQR) is employed to capture the impact more precisely across various stages of countries’ development. The findings suggest a direct relationship between employment and renewable energy adoption across all quantiles. Moreover, the negative coefficient for the energy dependency in the first quantile documents an increased sensitivity of less developed economies to energy market uncertainties. Full article

Background: As populations age and digitalization accelerates globally, understanding whether digital inclusion can enhance the economic well-being of older adults is critical for achieving sustainable development. However, empirical evidence on the mechanisms linking digital life to sustainable income among older populations remains limited. Design: This study utilizes data from the 2023 Chinese General Social Survey (CGSS), comprising 3127 respondents aged 55 and older. We employ ordinary least squares (OLS) regression with city fixed effects, instrumental variable estimation, and mediation analysis to examine the impact of digital life on income and its underlying mechanisms, with a focus on sustainability outcomes. Results: Digital life significantly enhances income levels among older adults, a finding robust to endogeneity and sensitivity checks. Heterogeneity analysis shows stronger effects for rural seniors, those in western regions, and older women. Mediation analysis reveals that digital engagement boosts income through four pathways—employment, material capital, social capital, and human capital—each contributing to the economic sustainability of aging populations. Conclusions: Digital inclusion serves as a mechanism to transform seniors’ dormant assets into productive capital, thereby promoting sustainable income and contributing to the Sustainable Development Goals (SDGs), particularly SDG 8 (Decent Work and Economic Growth) and SDG 10 (Reduced Inequalities). Policies should prioritize targeted digital literacy training, age-friendly platform design, and integration with social protection systems to foster inclusive and sustainable aging societies. Full article

Reconciling economic growth with environmental protection continues to represent a central global challenge. As one of the world’s largest developing economies, China has advanced an ecological civilization strategy that offers a unique opportunity to evaluate how national policy can shape sustainable development trajectories. This study assesses whether China’s ecological civilization construction enhances urban green total factor productivity (GTFP). Using panel data for 283 Chinese cities (2006–2019), this study identifies ecological civilization pilot cities through a standardized and reproducible protocol, measures urban GTFP using the Global Malmquist–Luenberger (GML) index and estimates policy effects with a multi-period difference-in-differences (DID) design that accounts for staggered implementation and overlapping policies. The results indicate that urban GTFP exhibited an overall upward but fluctuating trend during the study period, with regional growth rates ranking East > Central > West and a tendency toward convergence in recent years. The analysis further indicates that national ecological civilization construction policies exert a statistically significant and positive effect on urban GTFP, with the findings remaining robust to parallel trend tests and multiple robustness checks. The promotion effect displays marked regional heterogeneity, being strongest in western cities, followed by eastern and central regions, and remains positive across different urban contexts, including resource-based and non-resource-based cities as well as cities within and outside the Yangtze River Economic Belt. Mechanism analysis further reveals that the policy effect operates primarily through industrial upgrading and green technological innovation, whereas the industrial structure rationalization channel is not statistically significant. Overall, this study provides a transparent and reproducible framework for pilot city identification and causal evaluation, offering policy-relevant insights for differentiated and region-specific ecological governance aimed at balanced regional development, industrial upgrading, and green technological innovation. Full article

In the context of a deep structural adjustment of China’s real estate sector and heightened macroeconomic uncertainty, quantitatively assessing the resilience of listed real estate enterprises is crucial for preventing systemic risk and promoting sustainable development. This paper proposes a multidimensional resilience evaluation framework for 37 Chinese A-share listed real estate firms using panel data from 2017–2024. An index system covering four dimensions—solvency and liquidity, profitability and cash flow, operational efficiency and asset structure, and growth and value—is constructed on the basis of financial ratios. The entropy-weighted TOPSIS method is employed to derive a composite resilience index, while principal component analysis (PCA) provides a complementary robustness check of the rankings. The empirical results indicate that (1) operational efficiency and asset structure receive the highest objective weight, followed by solvency and liquidity, whereas the weights of profitability, cash flow, and growth–value dimensions are relatively lower; at the indicator level, accounts receivable turnover, inventory turnover and the cash-to-short-term-debt ratio play a leading role, underscoring the central importance of liquidity safety and asset turnover under the “three red lines” regulatory regime. (2) Firms such as Shahe Co., Shenzhen, China, Huafa Co., Zhuhai, China and Wantong Development, Beijing, China exhibit persistently higher resilience scores, characterized by lower leverage, stronger cash buffers and faster operating turnover, whereas firms such as Yunnan Metropolitan Investment, Kunming, China, Greenland Holdings, Shanghai, China, Bright Real Estate, Shanghai, China and Rongsheng Development, Langfang, China remain at the lower tail of the resilience distribution with high leverage, tight liquidity and volatile profitability. (3) The resilience rankings obtained from entropy-weighted TOPSIS and PCA are positively and significantly correlated at the 1% level, suggesting a moderate level of consistency between distance-based and variance-based evaluation schemes. Building on these findings, this paper proposes resilience-oriented policy recommendations for regulators and managers in terms of differentiated prudential regulation, capital-structure and debt-maturity optimization, operational efficiency enhancement, and the integration of digital transformation and ESG governance. Full article

Within a spatial-economics framework, this paper extends a general-equilibrium model to examine how high-speed rail (HSR) openings reduce migration costs and thereby alleviate regional factor misallocation. The model predicts that improved connectivity lowers labor mobility frictions, facilitates cross-regional reallocation of productive factors, and reduces misallocation. Using a panel of China’s prefecture-level cities from 2006 to 2016 and a difference-in-differences design, we estimate the causal effects of HSR on the misallocation of labor and capital. The results show that HSR openings significantly improve both labor and capital allocation, and the findings remain robust to a range of endogeneity checks and alternative specifications. Heterogeneity analyses indicate that the improvement is concentrated in eastern cities, while the effects are statistically insignificant in central and western regions. We also find that the reduction in misallocation occurs in both provincial capital and non-capital cities. These results imply that HSR can enhance resource-use efficiency and support sustainable regional development by reducing spatial frictions and promoting more balanced factor allocation. From a policy perspective, accelerating HSR network expansion can lower cross-regional mobility costs and enable freer flows of labor and capital, thereby improving allocative efficiency and fostering inclusive and sustainable growth. Full article

This study examines the effects of Gross Domestic Product (GDP) per capita, its squared and cubic terms (GDP² and GDP³), renewable energy, fossil fuels, nuclear energy, and research and development (R&D) on environmental sustainability in G20 countries from 1994 to 2023, with a specific focus on testing the N-shaped Environmental Kuznets Curve (EKC) hypothesis. CS-ARDL serves as the baseline estimator, and robustness is checked using FMOLS and DOLS estimators and an alternative dependent variable, greenhouse gas (GHG) emissions. The coefficients of GDP, GDP², and GDP³ follow the expected +, −, + pattern of a cubic specification, indicating nonlinear income–environment dynamics. However, the implied turning points are not observed within the sample range, suggesting that a full N-shaped EKC trajectory is not empirically supported for G20 countries. Renewable energy consumption and R&D investment have negative coefficients, suggesting they help reduce environmental degradation. Fossil fuel consumption significantly increases ecological pressure, whereas nuclear energy shows a positive but insignificant effect. The findings remain robust across alternative estimators and when GHG emissions are used. Overall, the findings indicate that economic growth alone cannot ensure environmental sustainability, underscoring the need for renewable energy expansion, technological innovation, and reduced reliance on fossil fuels. Full article

This study investigated the relationship between digital governance and sustainable development across the European Union (EU-27) during the period 2015–2023. Although digital transformation has become a central policy priority, empirical evidence on how e-government adoption contributes to sustainability performance remains limited. Using panel data from Eurostat and the UN Sustainable Development Solutions Network, the analysis employed advanced econometric techniques, including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Method of Moments Quantile Regression (MMQR), to explore both long-run relationships and heterogeneous effects across countries. The model incorporates key indicators such as the percentage of individuals using e-government services, Gross Domestic Product (GDP) per capita growth, and Research and Development (R&D) expenditure, capturing, respectively, digital governance adoption, innovation potential, and economic capacity, as essential drivers of sustainable development. Results indicate a strong and statistically significant positive association between digital governance adoption and sustainable development outcomes. The quantile regression analysis reveals that this effect is more pronounced in countries with higher innovation intensity and stronger economic capacity, suggesting that digital governance amplifies sustainability benefits in countries with more advanced institutional and technological infrastructures. Robustness checks confirm the stability of the findings across multiple estimation techniques. The results underscore the need for inclusive and innovation-driven digital strategies to ensure that the benefits of digital governance are equitably distributed, ultimately enhancing the EU’s progress towards the Sustainable Development Goals. Full article

Heike 60, a cold-tolerant soybean cultivar developed at the Heihe Branch of the Heilongjiang Academy of Agricultural Sciences, was evaluated across seven locations in Heilongjiang Province, northeastern China, over four growing seasons (2015–2018), generating 28 site–year environments. The objectives were to characterize yield performance and stability, partition sources of agronomic variation, and identify the yield component pathways through which the cultivar adapts to contrasting cold–temperate environments. Grain yield across the trial network ranged from 1591 to 3219 kg ha⁻¹ with a grand mean of 2688 kg ha⁻¹, and Heike 60 consistently outperformed the regional check variety Heihe 43 across all evaluated locations and seasons, with a mean yield advantage of 11.5%. Two-way ANOVA revealed highly significant (p < 0.001) Year, Location, and Year × Location interaction effects for all eight agronomic traits examined, with the interaction term accounting for the largest proportion of yield variance, indicating that relative site performance was not consistent across seasons. Five of the seven locations were classified as stable by the coefficient of variation criterion (CV < 15%), with Eberhart–Russell regression coefficients of 1.000 across all sites confirming average and proportional responsiveness to environmental quality. Hierarchical cluster analysis partitioned the 24-core site–year environments into three agronomically distinct groups reflecting differences in accumulated thermal resources: a pod number-compensating profile under lower temperature accumulation, a seed weight-dominated profile under higher post-anthesis thermal supply, and a balanced yield component expression representing the predominant growing conditions of the region. Random forest modeling identified hundred-seed weight, pods per plant, and growth period as the primary predictors of grain yield across environments. Collectively, the results demonstrate that Heike 60 possesses broad adaptability and phenotypic plasticity across the cold–temperate soybean production zone of Heilongjiang Province, combining competitive mean yield with stable performance across diverse environmental conditions. Full article

Plants adapt to abiotic stresses by modulating morphological, physiological, and biochemical processes, which constitute the fundamental mechanisms of stress tolerance. Rice is highly susceptible to drought stress at all developmental stages, leading to substantial reductions in growth and yield, signifying the urgent need to develop drought-tolerant rice genotypes. In this study, recombinant inbred lines (RILs) in rice with enhanced drought tolerance were developed through a cross between the high-yielding rice variety BRRI-28 and the commercial variety BINA-7, followed by successive selfing and phenotypic selection. The resulting lines were evaluated using integrated morphological, physiological, biochemical, and anatomical analyses under well-watered (WW) and drought conditions (DC). BRRIdhan-56, a known drought-tolerant variety, was included as a check genotype. Among the tested lines, RIL-3 exhibited superior agronomic performance under DC, including a significantly higher tiller number, plant height, and seed dry weight, and improved root attributes compared with its parental lines and, for several traits, exceeding those of BRRIdhan-56. Leaf rolling was absent in RIL-3 and the check variety until the 23rd day of drought stress, whereas other genotypes exhibited varying degrees of stress symptoms. Panicle exertion under DC was observed exclusively in RIL-3 and the check. Although all genotypes showed reductions in biomass, relative water content, and chlorophyll levels under DC, RIL-3 consistently maintained higher values than its parental lines and comparable or superior levels to the check variety. Notably, RIL-3 exhibited a distinctive physiological response characterized by sustained chlorophyll retention and low proline accumulation under severe drought, in contrast to the high proline levels observed in sensitive lines. A root anatomical analysis further revealed well-developed aerenchyma formation in RIL-3 following drought treatment, supporting its drought tolerance. Together, these results demonstrate that RIL-3 combines an enhanced drought tolerance with a stable agronomic and yield-related performance and a unique physiological trait profile under drought stress, highlighting its potential value as a promising genotype for drought-tolerance breeding programs. Full article

Medium-sized cities are increasingly affected by processes of urban fragmentation and residential segregation, despite having traditionally been perceived as more socially cohesive and territorially balanced than large metropolitan areas. Acting as functional connectors between metropolitan hubs and rural regions, these cities are particularly vulnerable to unplanned suburban growth, housing market polarization and uneven access to urban opportunities. This study develops and applies a multidimensional Urban Territorial Index (UTI) to diagnose socio-spatial inequality in medium-sized cities, using Ciudad Real (central Spain) and its functional urban area as a case study. The UTI integrates six indicators across three analytical dimensions—socioeconomic, sociodemographic and housing—through a PCA-informed weighting scheme and GIS-based spatial analysis. The index is calculated at census-tract and neighborhood scales and is validated through internal consistency checks, external comparison with a local Human Development Index (r = 0.87; p < 0.001), and qualitative robustness assessments. Results reveal a pronounced core–periphery polarization: central and strategically located neighborhoods associated with key infrastructures (university, high-speed rail station and hospital) concentrate higher income levels, educational attainment and land values, while peripheral municipalities and disadvantaged neighborhoods exhibit higher unemployment, lower housing values and greater social vulnerability. The analysis also identifies population–housing mismatches linked to suburban expansion without equivalent functional integration. Beyond the local case, the study provides a transparent and replicable methodological framework tailored to medium-sized cities, where metropolitan-scale indices often fail to capture fine-grained socio-spatial disparities. The UTI offers a practical tool for comparative analysis, temporal monitoring and evidence-based urban policy, supporting more inclusive and territorially balanced development strategies in diverse institutional and geographical contexts. Full article

Green innovation has been widely regarded as an important driver of sustainable development; however, its implications for biodiversity conservation remain insufficiently explored. Existing studies primarily focus on the roles of green innovation in pollution control and energy efficiency, leaving its relationship with biodiversity outcomes largely understudied. This gap is particularly pronounced in regions experiencing intense ecological pressure, such as the Yangtze River Economic Belt (YREB), where rapid industrialization and human activities have substantially altered ecosystems. Using panel data from 11 provinces in the YREB over the period 2017–2020, this study examines the impact of green innovation development on biodiversity. Employing a two-way fixed-effects model, the results indicate that green innovation development is positively associated with biodiversity conservation, and this association remains robust to a range of endogeneity checks and robustness tests. To further explore potential transmission channels, we conduct a mechanism analysis. The findings provide indicative evidence that green innovation is associated with biodiversity outcomes through carbon emission reduction and improvements in environmental governance. Overall, this study contributes to the literature by shedding light on the biodiversity implications of green innovation and offers policy-relevant insights for regions seeking to balance innovation-driven growth with ecological protection. Full article

Technological progress and green, low-carbon growth are vital for sustainable economic development. Since supply chains are a major source of corporate carbon emissions and they face coordination challenges exceeding firm-level digitalization, China’s SCIAPP policy emphasizing cross-organizational green collaboration for low-carbon transformation applies to them. This study, using panel data from A-share listed companies (2013–2022), employs a difference-in-differences method to analyze how supply chain digitalization influences corporate carbon emissions within the framework of the Supply Chain Innovation and Application Pilot Program (SCIAPP). The results show that supply chain digitalization significantly lowers emissions, and the findings are robust to endogeneity tests and other robustness checks. Heterogeneity analysis indicates that firms with higher governance standards and advanced digital maturity gain the most in emission reductions, especially state-owned enterprises and manufacturing companies. Mechanism tests suggest that improvements in supply chain efficiency and increased corporate innovation drive this effect. Theoretically, the research extends the digitalization–emission relationship from individual firms to entire supply chains, proposing and confirming a dual-channel framework (efficiency and innovation) that combines transaction-cost and resource-based views. Methodologically, treating the implementation of the SCIAPP as a quasi-natural experiment yields strong causal evidence beyond mere correlations. The study highlights the importance of the SCIAPP in achieving dual carbon targets and tackling global climate challenges, providing empirical insights to help enterprises reduce emissions and promote high-quality, efficient development. Full article

It is a hot topic to enhance the stability, security, and sustainability of industrial chains, against the backdrop of adjustments and rising uncertainty in global value chains. Using Chinese A-share listed firms from 2012 to 2022 as the research sample, this study treats the establishment of Cross-Border E-Commerce Comprehensive Pilot Zones (CBECCPZs) as a quasi-natural experiment and employs a difference-in-differences approach to empirically examine the impact of digital trade (DT) on industrial chain resilience (ICR) and its underlying mechanisms. The findings demonstrate that DT exerts a significantly positive effect on ICR, providing strong support for the long-term sustainability of the economic system. This conclusion remains robust after a series of robustness checks, including the incorporation of high-dimensional fixed effects, exclusion of confounding policy effects, adjustments to the sample, dimension-specific tests, consideration of lagged effects, and propensity score matching. Mechanism analysis reveals that DT strengthens ICR primarily by promoting firms’ digital transformation and improving human capital levels. The heterogeneity results suggest that the contribution of digital trade to resilience differs markedly across structural dimensions: the effect is more significant among firms located in eastern regions, state-owned enterprises, firms operating in regions with higher levels of digitalization, manufacturing firms, firms in more competitive industries, and firms with stronger internal control systems. From the perspective of ICR, this study elucidates the intrinsic mechanisms through which DT fosters high-quality development and sustainable economic growth. The findings provide robust empirical evidence for understanding the strategic role of DT in enhancing the security, stability, and sustainable operation of industrial chains and in building a modern industrial system that is autonomous, controllable, secure, and efficient. Moreover, the study offers important policy implications for governments seeking to advance DT institutional innovation and promote coordinated regional development, as well as for firms aiming to leverage DT to enhance long-term competitiveness and achieve sustainable development goals. Full article

Enhancing Energy-Embedded Green Utilization Efficiency of Urban Land (E-GUEUL) is crucial for reconciling economic growth with carbon neutrality targets, with the Integration of the Digital–Real Economy (IDRE) emerging as a key driver. This study measures city-level E-GUEUL using the super-efficiency SBM–Malmquist index model. To rigorously identify the causal effect of IDRE on E-GUEUL and address potential model misspecification and high-dimensional confounding factors, a Double Machine Learning (DML) framework is employed. Findings reveal a robust and significant positive effect of IDRE on E-GUEUL, a conclusion that holds across a series of robustness checks and endogeneity controls. Heterogeneity analysis indicates that the efficiency enhancement is more pronounced in non-resource-based, digitally developed, and eastern or central cities. Mechanism analysis reveals that optimizing Energy Consumption Intensity acts as a short-term driver, while Green Technology Innovation and Environmental Regulation serve as long-term sustainers. Furthermore, moderating effects reveal that Marketization exerts a positive moderating influence. This study provides empirical evidence and policy insights for leveraging IDRE to advance green growth through tailored approaches. Full article

We develop an informational extension of spacetime thermodynamics in which local entropy production is coupled to spacetime curvature within an effective covariant framework. Spacetime is modeled as a continuum limit of finite-capacity information registers, giving rise to a coarse-grained entropy field whose gradients define an informational flux. Within a nonminimally coupled scalar–tensor formulation, the resulting field equations imply that the local divergence of this flux is sourced by the Ricci scalar, establishing a direct relation between curvature and entropy production. The corresponding integral form links cumulative entropy generation to the integrated spacetime curvature over a causal region. In stationary limits, the framework reproduces the Bekenstein–Hawking entropy of horizons, while in homogeneous expanding cosmologies it yields monotonic entropy growth consistent with the observed arrow of time. The construction remains compatible with unitarity at the microscopic level and with holographic entropy bounds in the stationary limit. Numerical solutions in flat FLRW backgrounds are used as consistency checks of the coupled evolution equations and confirm the expected curvature–entropy behavior across cosmological epochs. Overall, the results provide a thermodynamically consistent interpretation of curvature as a geometric source of irreversible information flow, without modifying the underlying gravitational field equations. Full article