Search Results (1,788)

Cultivated land is fundamental to agricultural production, and the eco-efficiency of cultivated land utilization is widely acknowledged as a crucial indicator for assessing rational land use. Accordingly, this study applies a Super-SBM model with undesirable outputs to evaluate the eco-efficiency of cultivated land utilization (ECLU) across 31 provinces in China utilizing provincial panel data from 2005 to 2023 and further employs dynamic fuzzy-set qualitative comparative analysis to investigate, across spatial and temporal dimensions, how government policy, agricultural technology, socioeconomic conditions, and natural conditions interact to achieve a high ECLU and to elucidate the diverse configurational pathways through which these factors converge to deliver a high ECLU. Our findings demonstrate that the ECLU originates from the joint influence of several factors, and no single factor alone can provide a high level of eco-efficiency. In particular, a high GDP per capita and strong government agricultural expenditure intensity are pivotal for achieving a high ECLU, whereas a low GDP per capita and weak government agricultural expenditure intensity are the core conditions associated with poor eco-efficiency outcomes. We identify three distinct driving pathways that foster a high ECLU: the Economy–Technology–Government Synergistic Pathway, Nature–Economy Dual-Driver Pathway, and Government-Supported Land–Economy Pathway. Between-configuration consistency (BECONS) exhibits no significant temporal effect; however, a constellation of external factors triggered a pronounced, collective reduction in configurational consistency from 2008 to 2014. Regional analysis reveals pronounced heterogeneity: Spatially, the Economy–Technology–Government Synergistic Pathway is concentrated in China’s central and eastern provinces, the Nature–Economy Dual-Driver Pathway clusters mainly in the central belt, and the Government-Supported Land–Economy Pathway predominates in the west. Full article

The sustainable development of higher education exhibits a strong and measurable association with the level of regional innovation capacity. Drawing on panel data covering 31 provincial-level administrative regions in China from 2010 to 2022, we construct evaluation frameworks for both higher education and regional innovation capacity using the entropy weight method. These are complemented by kernel density estimation, spatial autocorrelation analysis, Dagum Gini coefficient decomposition, and the Obstacle Degree Model. Together, these tools enable a comprehensive investigation into the spatiotemporal evolution and driving mechanisms of coupling coordination dynamics between the two systems. The results indicate the following: (1) Both higher education and regional innovation capacity indices exhibit steady growth, accompanied by a clear temporal gradient differentiation. (2) The coupling coordination degree shows an overall upward trend, with significant inter-regional disparities, notably “higher in the east and low in the west”. (3) The spatial distribution of the coupling coordination degree reveals positive spatial autocorrelation, with provinces exhibiting similar levels tending to form spatial clusters, most commonly of the low–low or high–high type. (4) The spatial heterogeneity is pronounced, with inter-regional differences driving overall imbalance. (5) Key obstacles hindering regional innovation include inadequate R&D investment, limited trade openness, and weak technological development. In higher education sectors, limitations stem from insufficient social service benefits and efficiency of flow. This study recommends promoting the synchronized advancement of higher education and regional innovation through region-specific development strategies, strengthening institutional infrastructure, and accurately identifying and addressing key barriers. These efforts are essential to fostering high-quality, coordinated regional development. Full article

This study investigates the relationship between economic growth and energy consumption using the Energy Kuznets Curve (EKC) framework. Spatial econometric models, including the Spatial Panel Lag Model and the Spatial Dynamic Panel Lag IV Model, are employed to capture both spatial and dynamic effects. The results indicate that energy consumption in Thailand is spatially clustered, with energy use tending to spill over into neighboring provinces and concentrating in specific regions. Key factors that positively influence energy consumption include gross provincial product (GPP) per capita, population density, and road density. Regions characterized by favorable climates, sufficient infrastructure, and high levels of economic activity exhibit higher per capita energy consumption. The EKC analysis reveals a U-shape relationship between GPP per capita and energy consumption in the BKK&VIC, CE, EA, WE, and NE regions. As many regions continue to experience rising energy consumption, the findings underscore the importance of Thailand adopting more efficient energy usage strategies in tandem with its economic development. Full article

As semiconductor devices demand higher input–output density and faster signal transmission, fan-out panel-level packaging has emerged as a promising solution for next-generation electronic systems. However, the hygroscopic nature of epoxy molding compounds raises critical reliability concerns under high-temperature and high-humidity conditions. This study investigates the hygrothermal stress of a single fan-out panel-level package unit through experimental characterization and numerical simulation. Thermal–mechanical analysis was conducted at 100 °C and 260 °C to evaluate the strain behavior of two commercial epoxy molding compounds in granule form after moisture saturation. The coefficient of moisture expansion was calculated by correlating strain variation with moisture uptake obtained under 85 °C and 85% relative humidity, corresponding to moisture sensitivity level 1 conditions. These values were directly considered into a moisture -thermal coupled finite element analysis. The simulation results under reflow conditions demonstrate accurate principal stress and failure location predictions, with stress concentrations primarily observed at the die corners. The results confirm that thermal effects influence stress development more than moisture effects. Finally, a structural sensitivity analysis of the single-package configuration showed that optimizing the thickness of the dies and epoxy molding compound can reduce maximum principal stress by up to 12.4%, providing design insights for improving package-level reliability. Full article

The rapid development of the digital economy and the pursuit of green transformation are reshaping the innovation landscape of Chinese firms. However, limited attention has been paid to how digital industry agglomeration (DIA) influences corporate green innovation (CGI) at the firm level. Drawing on panel data from China’s A-share listed firms between 2017 and 2021, this study examines the differential effects of specialized agglomeration and diversified agglomeration of digital industry on CGI. The results indicate that DIA can promote CGI, with a 1% increase in DIA associated with a 1.503% increase in green innovation output. Further analysis reveals that specialized agglomeration exerts a significant positive effect, while diversified agglomeration has no evident impact. Our mechanism analysis indicates that knowledge spillovers serve as the key channel through which DIA fosters CGI. Moreover, heterogeneous effects analysis indicates that DIA exerts a stronger influence on non-high-tech enterprises and in regions where environmental regulation is less stringent. Drawing on these insights, fostering specialized digital clusters and strengthening knowledge-sharing mechanisms can help alleviate existing constraints on innovation diffusion, accelerating green innovation and supporting long-term sustainability. Full article

Exploring the impact of national park construction on county-level livelihood and well-being holds significant implications for enhancing social livelihood. This study treats Wuyishan National Park Construction (WNPC) as a quasi-natural experiment, utilizing panel data from 138 counties (2011–2023) to construct a county-level livelihood and well-being index through the CRITIC weighting method. Kernel density estimation and the Theil index are applied to depict the spatiotemporal dynamics of WNPC. Moreover, the difference-in-differences model and mediating effect model are employed to assess the impact and mechanisms of WNPC on livelihood and well-being. The results reveal that, in the period 2011–2023, livelihood and well-being scores ranged from 0.1329 to 0.4565, indicating considerable scope for improvement. Over time, inter-county disparities narrowed, displaying a spatial pattern of “higher in the east and west, lower in the middle.” Overall disparities remained pronounced, driven chiefly by within-region variation, and Jiangxi displayed notably larger internal gaps than Fujian and Zhejiang. Benchmark regressions confirm that WNPC significantly improved livelihood and well-being, with robust results according to multiple tests. Mechanism analysis indicates that WNPC enhances livelihood and well-being by promoting population mobility and improving infrastructure. Heterogeneity analysis suggests that compared to industrial counties, WNPC has a stronger positive effect on the livelihood and well-being of agricultural counties. Based on this, it is suggested that WNPC promotes population mobility and improves infrastructure construction. This study provides a scientific basis and decision-making reference for achieving high-quality construction of national parks and enhancing livelihood and well-being. Full article

This study investigates the impact and mechanisms of digital inclusive finance (DIF) on high-quality economic development in China. Drawing on panel data from 281 prefecture-level cities between 2011 and 2021, we employ a Spatial Durbin Model (SDM) to analyze both the direct effects and spatial spillovers of DIF. The results indicate that (1) DIF has a significantly positive effect on high-quality development, which remains robust after conducting various stability and endogeneity tests; (2) DIF strongly contributes to economic upgrading in eastern regions, while its impact is weaker or even negative in central and western regions, revealing notable regional disparities exist; (3) a key finding is the identification of a double-threshold effect, suggesting that the positive influence of DIF only emerges when financial and industrial development surpass certain thresholds; (4) results from the two-regime SDM further show that spillover effects are more prominent in non-central cities than in central ones; and (5) mechanism analysis reveals that DIF facilitates high-quality growth primarily by promoting industrial structure upgrading. These findings underscore the importance of region-specific policy strategies to enhance the role of DIF and reduce spatial disparities in development across China. Full article

The energy quota trading policy is a pivotal market-oriented environmental regulation policy that propels the reform of the energy structure. Utilizing panel data from 30 provinces in China covering the period from 2012 to 2022, this study employed a difference-in-differences model to systematically examine the influence of the energy quota trading policy on the decarbonization of energy consumption, and further explores two transmission mechanisms of green technology innovation and energy consumption intensity through mechanism tests. The study reveals several key findings: (1) The energy quota trading policy significantly enhances the decarbonization of energy consumption. (2) This policy encourages the adoption of clean energy by fostering green technological innovation and decreasing overall energy consumption. As a result, it makes a considerable contribution to the decarbonization process in energy usage. (3) The heterogeneity analysis demonstrates that in areas with low levels of industrialization and plentiful resources, as well as within the Yangtze River Economic Belt and the central and western regions, the effects of the policy are significantly more pronounced. Conversely, in regions characterized by high industrialization and limited resources, particularly in the eastern region, the effectiveness of the policy is comparatively diminished. Furthermore, this study not only offers empirical evidence supporting the optimization and enhancement of the energy quota trading policy but also presents recommendations for improving the trading market, regional policies, and fostering green technological innovation. Full article

Ensuring food security necessitates a high level of coordinated development between agricultural trade and production. Based on China’s provincial panel data from 2010 to 2023, this study constructs an evaluation index system for agricultural trade and production, employing an entropy-weighted TOPSIS model to measure their development levels. On this basis, a coupling coordination degree model and Moran’s I indices are used to analyze the coordinated development level’s temporal changes and spatial effects. The research finds that the development levels of China’s agricultural trade and production show an upward trend but currently still exhibit the pattern of higher levels in Eastern China and lower levels in Western China. The coupling coordination level between them demonstrates an increasing trend, yet the overall level remains relatively low, with an average value of only 0.445, consistently staying in a marginal disorder “running-in stage” and spatially presenting a distinct “east-high–west-low” stepped distribution pattern. Furthermore, from a spatial perspective, the Global Moran’s index decreased from 0.293 to 0.280. The coupling coordination degree of agricultural trade and production in China generally exhibits a positive spatial autocorrelation, but this effect has been weakening over time. Most provinces show spatial clustering characteristics of high–high and low–low agglomeration in local space, and this feature is relatively stable. Building on these insights, this study proposes a refinement of the coordination mechanisms between agricultural trade and production, alongside the implementation of differentiated regional coordinated development strategies, to promote the coupled and coordinated advancement of agricultural trade and production. Full article

This study investigates the influence of monthly income level (low, medium, and high) on consumer behavior regarding a newly launched cream cheese product enriched with berry by-products. A panel of 345 participants was surveyed, and data were analyzed using the Kruskal–Wallis and Mann–Whitney tests. Most consumers were environmentally aware, recognizing the impact of personal food waste and expressing support for food products incorporating by-products. Respondents also favored the use of renewable energy and reducing greenhouse gas emissions in the food industry. Higher income levels were associated with greater health awareness and increased acceptance of cream cheese with berry by-products, with the high-income group showing a greater willingness to pay a premium. Health benefits and the product’s natural character were the main advantages identified. Individuals with lower incomes were more open to trying unfamiliar foods when ingredient details were not provided, while higher-income respondents expressed greater hesitation and distrust toward new products. Willingness to try novel items decreased with income level. Statistically significant differences (p < 0.05) were found between income groups for label reading, support for mountain dairies, and the influence of product origin, health benefits, nutrient diversity, pricing concerns, and consumer confidence in purchasing cream cheese with berry by-products. These findings are important for understanding how income affects consumer perceptions and willingness to consume innovative, sustainable food products like berry-enriched cream cheese, highlighting key areas for targeted marketing and product development. Full article

This article investigates the political cost of poverty in democracies marked by deep social divisions. We develop a probabilistic voting model that incorporates clientelism as a strategic tool employed by elite political parties to secure electoral support from non-elite voters. Unlike models based on ideological proximity, our framework conceptualizes party competition as structured by the socioeconomic composition of their constituencies. We demonstrate that in contexts of high inequality and widespread poverty, elite parties face structural incentives to deploy clientelistic strategies rather than universalistic policy agendas. Our model predicts that clientelistic expenditures by elite parties increase proportionally with both inequality (GINI index) and poverty levels, rendering clientelism a rational and cost-effective mechanism of political control. Empirical evidence from a cross-national panel (2013–2019) confirms the theoretical predictions: an increase of the 1 percent in the GINI index increase a 1.3 percent in the clientelism, even after accounting for endogeneity and dynamic effects. These findings suggest that in divided democracies, poverty is not merely a condition to be alleviated, but a political resource that elites strategically exploit. Consequently, clientelism persists not as a cultural residue or institutional failure, but as a rational response to inequality-driven constraints within democratic competition. Full article

The worldwide air pollution situation reveals significant environmental challenges. In addition to being a major contributor to the deterioration of air quality, particulate matter (PM) is also an important factor affecting the performance of solar energy systems given its ability to decrease light transmission to solar panels. As part of our research, the present investigation involves monitoring concentrations of PM using a high-performance optical instrument, the in situ calibration protocol of which is described in detail. For the city of Rabat, observations revealed significant variations in concentrations between day and night, with peaks observed around 8 p.m. correlating with high relative humidity and low wind speeds, and the highest levels recorded in February with a monthly average value reaching 75 µm/m³. In addition, an experimental protocol was set up for an analysis of the elemental composition of particles in the same city using SEM/EDS, providing a better understanding of their morphology. To assess the impact of meteorological variables on PM concentrations in two distinct climatic environments, a database from the city of Marrakech for the year 2024 was utilized. Overall, the distribution of PM values during this period did not fluctuate significantly, with a monthly average value not exceeding 45 µm/m³. The random forest method identified the most influential variables on these concentrations, highlighting the strong influence of the type of environment. The findings provide crucial information for the modeling of solar installations’ soiling and for improving understanding of local air quality. Full article

This study investigates the relationship between social media use and subjective well-being among South Korean women in their 20s, with a particular emphasis on the moderating role of self-esteem. Cross-sectional data from 611 women in their 20s who had experience using social media platforms was drawn from the Korean Media Panel Survey 2021. A regression analysis revealed that increased social media use was associated with lower subjective well-being. Self-esteem acted as a moderator in the relationship between social media use and subjective well-being. Among individuals with low or medium levels of self-esteem, higher social media use was linked to decreased subjective well-being; however, for those with high self-esteem, social media use did not significantly impact subjective well-being. These findings underscore the significance of self-esteem as a protective factor in the context of social media use and its influence on the subjective well-being among women in their 20s. Full article

The rapid development and adoption of artificial intelligence (AI) technology has sparked debates about its implications for labor markets, yet the micro-level relationship between AI and labor share remains underexplored. Based on the theory of skill-biased technological change, this study aims to examine whether AI technology increases labor share by labor structure upgrading at the enterprise level. Using panel data for China’s listed companies from 2012 to 2022, this study tests this relationship using a two-way fixed effects model. The empirical results reveal that AI technology significantly increases labor share, with labor structure upgrading playing a mediating role in this relationship. Heterogeneity analysis reveals that the influence of AI technology on labor share is stronger for enterprises characterized by low labor market rigidity, high labor market supply, and talent policy support in external environments, as well as among labor-intensive, high-tech, and non-state-owned enterprises. Notably, this study finds that advancements in AI technology have achieved mutually beneficial outcomes of improving labor share and enhancing total factor productivity. Our research findings provide detailed empirical evidence for enterprises to formulate and implement AI strategies. Full article

Background/Objectives: Psychological safety is essential for effective learning in high-fidelity simulation (HFS); however, no validated Japanese instrument currently exists to measure psychological safety among nursing students. This study aimed to translate the Psychological Safety in High-Fidelity Simulation (PS-HFS) scale into Japanese (PS-HFS-J) and evaluate its psychometric properties. Methods: Following COSMIN guidelines, the PS-HFS was translated through forward and back translation, reviewed by an expert panel, and tested for face validity via pilot testing. The scale’s reliability and validity were subsequently examined in 263 undergraduate nursing students using confirmatory factor analysis (CFA), Cronbach’s alpha, and intraclass correlation coefficients (ICC). Results: CFA confirmed a good fit of the original four-factor model (CFI = 0.990, TLI = 0.988, RMSEA = 0.026). The scale demonstrated excellent internal consistency (Cronbach’s α = 0.906 overall) and strong test-retest reliability (ICC range: 0.859–0.914). Content validity indices were also high (I-CVI = 0.80–1.00, S-CVI/Ave = 0.94). Conclusions: The PS-HFS-J is a reliable, valid, and culturally adapted instrument for assessing psychological safety in Japanese nursing education. It can support educational research, curriculum development, and faculty training, contributing to safer and more effective simulation-based education. Future studies should examine its applicability across diverse educational levels and clinical contexts. Full article