Search Results (1,757)

This study examines the impact of technological progress on food price dynamics and supply stability across the 27 European Union Member States during 2011–2024. Using a balanced panel dataset, the analysis explores four dependent indicators—consumer food prices, food price inflation, price volatility, and food supply variability—while controlling for trade openness, GDP per capita growth, and population. Technological progress is estimated through panel least squares regression with fixed effects. The results reveal that technological advancement significantly reduces food prices and inflation, suggesting that innovation-driven productivity and efficiency gains stabilize consumer markets. However, its influence on food price volatility and supply variability is statistically insignificant, indicating that innovation alone cannot fully mitigate systemic risks in the European food system. The results provide policy-relevant evidence supporting the integration of technological innovation into food system governance across the European Union. They underline the need for targeted investment and regulatory coordination to translate innovation gains into tangible resilience outcomes, thus offering practical guidance for policymakers and stakeholders involved in implementing the European Green Deal and the Farm to Fork Strategy. Full article

Climate change is driving the need for forest management strategies that simultaneously enhance ecosystem resilience and contribute to climate change mitigation. Voluntary carbon markets (VCMs), regulated in the European Union by the Carbon Removal Certification Framework (CRCF), offer potential financial incentives for such management, but eligibility criteria—particularly biodiversity requirements—limit the applicability of certain species. This study assessed the ecological and economic outcomes of six alternative management scenarios for a 4.7 ha, 99-year-old Scots pine (Pinus sylvestris) stand in western Hungary, comparing them against a business-as-usual (BAU) regeneration baseline. Using field inventory data, species-specific yield tables, and the Forest Industry Carbon Model, we modelled living and dead biomass carbon stocks for 2025–2050 and calculated potential CO₂ credit generation. Economic evaluation employed total discounted contribution margin (TDCM) analyses under varying carbon credit prices (€0–150/tCO₂). Results showed that an extended rotation yielded the highest carbon sequestration (958 tCO₂ above BAU) and TDCM but was deemed operationally unfeasible due to declining stand health. Black locust (Robinia pseudoacacia) regeneration provided high mitigation potential (690 tCO₂) but was ineligible under CRCF rules. Grey poplar (Populus × canescens) regeneration emerged as the most viable option, balancing biodiversity compliance, climate adaptability, and economic return (TDCM = EUR 22,900 at €50/tCO₂). The findings underscore the importance of integrating ecological suitability, market regulations, and economic performance in planning carbon farming projects, and highlight that regulatory biodiversity safeguards can significantly shape feasible mitigation pathways. Full article

This study evaluated the effects of high doses of phytase on the growth performance, carcass characteristics, and serum chemistry of late-finishing pigs housed under space-restricted conditions. Pigs (n = 375; 94.63 ± 0.61 kg) were randomly assigned to 48 pens, with 7 to 8 pigs per pen, balanced for gilts and barrows. Two phytase doses (control of 2500 FTU/kg or hyper-dose of 5000 FTU/kg) and two space allocation dimensions (adequate with 0.85 m²/pig or restricted with 0.66 m²/pig) were combined to create a 2 × 2 factorial arrangement (12 replicates per treatment). The three heaviest pigs per pen were marketed on day 28, and the remaining pigs were marketed on day 42. No interactions (p > 0.10) were observed between the floor space allowance and phytase supplementation. The body weight, daily gain, and feed intake at the first marketing and for all pigs marketed were reduced (p ≤ 0.009) by space restriction, without affecting the gain-to-feed ratio. Space restriction increased serum protein and decreased urea N, and hyper-dosing phytase increased plasma inositol and serum glucose and decreased serum aspartate aminotransferase (p < 0.05). The results indicate that space restriction reduced the growth rate, feed intake, and body weight of late-finishing pigs, and that hyper-dosing phytase was not beneficial in improving growth performance regardless of space allowance. Full article

Online customer reviews contain rich signals about product value but are difficult to convert into strategy-ready evidence. This study proposes an end-to-end framework that maps review text to the Value Proposition Canvas (VPC) and quantifies alignment between user needs and product performance. Using customer reviews for three Samsung Galaxy Watch generations, an LLM extracts six dimensions (Customer Jobs, Pains, Gains, Feature Gaps, Emotions, Usage Context). Extracted phrases are embedded with a transformer model, clustered via K-means with data-driven k selection, and labeled by an LLM to form an interpretable taxonomy. Subsequently, the analysis derives frequency profiles, a gap density indicator, a context–gap matrix, and a composite Product–Market Fit (PMF) score that balances gain rate, gap rate, and coverage with sensitivity analysis to alternative weights. The findings show predominantly positive affect, with unmet needs concentrated in battery endurance and interaction stability. Productivity- and interaction-centric jobs attain the highest PMF score, while several monitoring-centric jobs are comparatively weaker. Significant cross-generation differences in job composition indicate evolving usage priorities across successive releases. The framework provides a scalable, reproducible path from unstructured VOC to decision support, enabling data-driven prioritization for product and UX management while advancing theory-grounded analysis of customer value. Full article

The paper manufacturing industry faces increasing challenges in balancing operational costs with service quality under uncertain market conditions. This research presents a bi-objective credibility-based expected value model for integrated production–distribution planning that simultaneously minimizes total costs and maximizes service-level performance. The model considers multiple paper grades, production facilities, warehouses, and customer zones while handling demand uncertainty through credibility theory. Three additional constraints are introduced: service time limitations, capacity expansion decisions, and quality assurance requirements. The Torabi–Hassini (TH) method is employed to solve the bi-objective optimization problem effectively. Computational experiments demonstrate the model’s capability to provide balanced trade-off solutions between cost efficiency and service quality, achieving service-level improvements of 8–13% with cost increases of 5–9% compared to cost-only optimization, and cost reductions of 10–15% compared to service-only optimization. The results show that the credibility-based expected value approach provides robust and practical solutions for paper manufacturing supply chain optimization. Full article

This study investigated how banks’ balance sheet fundamentals shape their credit growth using panel co-integration methods and two estimation methods—pooled mean group (PMG) and dynamic fixed effects (DFE). Both approaches yielded consistent core results. First, weaker asset quality, proxied by higher non-performing loans (NPLs), was strongly and negatively related to credit growth: PMG produced a large negative long-run coefficient, and DFE’s error-correction form confirmed a significant adverse effect, consistent with higher provisioning, thinner capital buffers, and lower risk-taking. Second, capitalization (equity to assets) supported long-run growth under PMG, while DFE—imposing common slopes—did not, suggesting heterogeneous capitalization effects across banks that PMG captured but DFE muted. Third, operating expense intensity showed a positive long-run association with credit growth in both models, consistent with expansionary spending accompanying durable lending rather than costs causing lending. Long-run effects for liquidity and market-risk sensitivity were weaker or mixed: liquidity’s role was imprecise, and market-risk sensitivity was positive in PMG but not significant in DFE, again pointing to cross-sectional heterogeneity. Error-correction terms were large, negative, and highly significant in both models, indicating rapid convergence—near full adjustment within one period, with slight overshooting in DFE. Short-run results showed that higher liquidity and temporary cost spikes dampened contemporaneous growth. Policy implications emphasize sustained oversight of asset quality and prudent capital planning to support long-run credit supply. Full article

At the European level, potato cultivation is highly polarized. In Western Europe (Germany, France, the Netherlands, Belgium, Denmark), yields are high, agricultural technology is advanced, and production systems ensure stability and competitiveness. In contrast, in Eastern and Southern Europe (including Romania, Poland, Italy, and Spain), yields are considerably lower due to the use of outdated agricultural practices, a low degree of mechanization, and increased exposure to adverse climatic factors. In Romania, potato cultivation is marked by significant territorial disparities and structural imbalances, influenced by land fragmentation, agro-pedoclimatic variability, and the lack of capital necessary for investments in modern technologies and irrigation systems. This study analyzes these regional disparities in relation to the country’s real agricultural potential and quantifies the economic impact of its failure to realize it. The methodology applied is based on descriptive statistical analysis of data at the county and regional level for the period 2003–2024, including minimum, maximum, average, and standard deviations of yields. These were integrated into a production function that correlates cultivated areas with average prices, highlighting major intra-regional differences and significant economic consequences at the national level. The results indicate a double crisis: a drastic reduction in the areas cultivated with potatoes (from 196,000 ha in 2017 to 76,000 ha in 2024) and consistently low yields (12,000–18,000 kg/ha), which led to the collapse of total production (from 3.1 million tons in 2017 to under 1 million tons in 2024). As a result, Romania registers a productivity three to four times lower than the reference Western European countries. Moreover, Romania has moved from being a net exporter to a net importer of potatoes, with the food self-sufficiency indicator decreasing from 100.3% in 2017 to 48.1% in 2023. Although domestic production could theoretically cover consumption needs, structural problems regarding yields, the sharp reduction in cultivated areas, and distribution deficiencies have seriously affected the balance of the domestic market. While per capita consumption has remained relatively constant, the decline in production has led, after 2021, to an increasing dependence on imports. These trends highlight the need for urgent structural reforms, technological modernization, and targeted agricultural policies to increase productivity and restore food security in the Romanian potato crop system. Full article

Street greening is widely recognized as influencing resident well-being and housing prices, and street-view imagery provides a fine-grained data source for quantifying urban microenvironments. However, existing research predominantly relies on single indicators such as the Green View Index (GVI) and overall green coverage/volume lacking a systematic analysis of how the hierarchical structure of trees, shrubs, and grass relates to housing prices. This study examines the high-density block context of Tianjin’s six urban districts. Using the Street Greening Space Structure (SGSS) dataset to construct greening structure configurations, we integrate housing-price data, neighborhood attributes, and 13,280 street-view images from the study area. We quantify how “visibility and hierarchical ratios” are capitalized on in the housing market and identify auditable threshold ranges and contextual gating. We propose an urban–forest structural system centered on visibility and hierarchical ratios that links street-level observability to ecosystem services. Employing an integrated framework combining Geographical-XGBoost (G-XGBoost) and SHapley Additive exPlanations (SHAP), we move beyond average effects to reveal structural detail and contextual heterogeneity in capitalization. Our findings indicate that tree visibility G_TVI is the most robust and readily capitalized price signal: when G_TVI increases from approximately 0.06 to 0.12–0.16, housing prices rise by about 8%–10%. Hierarchical structure is crucial: balanced tree–shrub ratios and moderate shrub–grass ratios translate “visible green” into functional green. Capitalization effects are environmentally conditioned—more pronounced along corridors with high centrality and accessibility—and are likewise common in dense East Asian metropolises (e.g., Beijing, Shanghai, Seoul, and Tokyo) and rapidly motorizing cities (e.g., Bangkok and Jakarta). These patterns suggest parametric prescriptions that prioritize canopy-corridor continuity and keep ratios within actionable threshold bands. We translate these findings into urban greening strategies that prioritize canopy continuity, under-canopy permeability, and maintainability, providing sustainability-oriented, parameterized guidance for converting urban greening structure into ecological capital for sustainable cities. Full article

Background/Objectives: Nutrition during the reproductive years shapes women’s immediate health, fertility, pregnancy outcomes, and long-term offspring well-being. This position paper narratively synthesizes and critically appraises evidence on how dietary patterns, macro-/micronutrients, and supplementation influence women’s health, female fertility, and reproductive outcomes, to inform practical recommendations. Methods: We narratively reviewed recent reviews, cohort studies, clinical trials, and public-health guidance on macronutrients, key micronutrients, dietary patterns (with emphasis on the Mediterranean diet), ultra-processed food (UPF) intake, and targeted supplementation relevant to menstrual, metabolic, cardiovascular, skeletal, and reproductive outcomes. Results: Balanced, diverse diets rich in whole and minimally processed foods support hormonal regulation, ovulatory function, healthy gestation, and chronic-disease risk reduction. Priority nutrients include iron, folate, calcium, vitamin D, zinc, vitamin B12, and long-chain omega-3s (DHA), with supplementation considered when dietary intake or bioavailability is inadequate. Evidence consistently links Mediterranean-style eating to improved metabolic health, insulin sensitivity, IVF success, lower gestational diabetes risk, and favorable neonatal outcomes. High UPF consumption is associated with poorer diet quality, inflammation, adverse pregnancy outcomes, and potential reproductive impairment, warranting a reduction in favor of nutrient-dense foods. Diet also influences cardiovascular and bone health through effects on lipids, glycemia, blood pressure, and mineral/vitamin status, with fiber-rich carbohydrates, unsaturated fats (notably olive oil), and adequate calcium–vitamin D emerging as central levers. Conclusions: For women of childbearing age, a Mediterranean-aligned, minimally processed dietary pattern—tailored to individual needs and complemented by prudent use of folate, iron, vitamin D, calcium, B12, and DHA when indicated—offers robust benefits across reproductive, metabolic, cardiovascular, and skeletal domains. Public-health actions should improve access to healthy foods, curb UPF marketing, and embed personalized nutrition counseling in routine care; further longitudinal research from preconception through postpartum is needed. Full article

This entry examines how wage-setting institutions (WSIs) shape wages across advanced economies. It focuses on four core mechanisms—minimum wages, collective bargaining, wage coordination, and wage centralization—drawing on theoretical insights, empirical evidence, and cross-country comparisons. The analysis shows that minimum wages safeguard low-paid workers but have heterogeneous employment effects depending on their level and enforcement. Collective bargaining raises average wages and compresses wage inequality, though it can reduce flexibility and create insider–outsider dynamics. Wage coordination stabilizes wage growth, prevents inflationary spirals, and fosters equity, while wage centralization promotes solidarity wages and macroeconomic discipline but may limit adaptability. Using The Organization for Economic Co-operation and Development (OECD) and Institutional Characteristics of Trade Unions, Wage Setting, State Intervention and Social Pacts (ICTWSS) data, the study highlights institutional diversity, ranging from coordinated Nordic models to fragmented liberal systems, and identifies trends toward “organized decentralization”. Policy implications suggest that WSIs should be viewed not as rigidities but as adaptable frameworks that can balance efficiency, equity, and stability when carefully designed. The conclusion emphasizes that the future of wage-setting lies in leveraging institutional complementarities to respond to globalization, technological change, and shifting labor market conditions. Full article

Accurate stock price forecasting is crucial for supporting informed investment decisions, effective risk management, and the identification of profitable market opportunities. Financial time series present considerable challenges for prediction due to their complex, nonlinear dynamics and sensitivity to a wide range of economic factors. Although various statistical methods have been developed to model the multidimensional relationships inherent in such datasets, advancements in big data technologies have greatly facilitated the recording, analysis, and interpretation of large-scale financial data, thereby accelerating the adoption of deep learning (DL) algorithms in this domain. In the present study, RNN-, LSTM-, and GRU-based models were developed to forecast the closing prices of two airline stocks, with hyperparameter optimization conducted via the Bayesian optimization algorithm. The dataset consisted of daily closing prices of THYAO and PGSUS stocks obtained from Yahoo Finance. Comparative analysis demonstrated that the GRU model yielded the highest accuracy for THYAO stock price prediction, achieving a MAPE of 3.05% and an RMSE of 3.195, whereas for PGSUS, the model achieved a MAPE of 3.97% and an RMSE of 3.232. Beyond its empirical contribution, this study also emphasizes the conceptual relevance of symmetry in financial forecasting. The proposed deep learning framework captures the balanced relationships and nonlinear interactions inherent in stock market behavior, reflecting both symmetry and asymmetry in market responses to economic factors. Full article

This study addresses the critical challenge of designing retirement savings systems that effectively balance liquidity needs and long-term accumulation in contexts characterized by high unemployment and labor market instability, with a focus on South Africa. Traditional pension schemes often assume uninterrupted careers and stable incomes, assumptions frequently violated in low- and middle-income countries, leading to inadequate retirement security and consumption volatility during working life. Motivated by this gap, we develop a stochastic two-pot retirement savings model that explicitly integrates labor market uncertainty using a Markov chain-based Monte Carlo simulation. The model allocates annual contributions between an accessible savings pot and a locked retirement pot, with individuals optimizing consumption and withdrawal decisions to maximize expected lifetime utility under Constant Relative Risk Aversion (CRRA) preferences. Our findings, derived from calibration to South African labor data, reveal that high unemployment and career uncertainty significantly increase the welfare-maximizing preference for liquidity. This result challenges conventional policies prescribing fixed contribution allocations, such as the one-third/two-thirds split in the new two-pot system, and underscores the importance of flexible retirement savings designs. We conclude that tailoring pension design to labor market realities can enhance both retirement security and welfare in volatile economies. Full article

Against the backdrop of global economic digital transformation and the rapid flow of creative factors, innovation spaces, as the key carriers of inventive activities, drive high-quality development in urban agglomerations. This study develops a three-dimensional framework of “Spatial Structure–Factor Synergy–Institutional Drivers” to uncover the evolution of innovation spaces and industrial shifts in the Beijing–Tianjin–Hebei urban agglomeration, China. Methodologically, spatial econometric techniques were applied to capture both the overall concentration and spatial disparities of innovation. Spatial Gini and variation coefficients measured innovation clustering, while standard deviation ellipses and location entropy identified spatial linkages among high-tech innovation clusters. Geographically weighted regression models explored spatial heterogeneity in influencing factors, and a policy intensity index was constructed to assess the effectiveness of differentiated policy interventions in optimizing innovation resources. Key findings include the following: (1) Innovation spaces are spatially polarized in a “core–periphery” pattern, yet require cross-regional collaboration. Concurrently, high-tech industries demonstrate a gradient structure: central cities leading in R&D, sub-central cities driving industrial applications, and node cities achieving specialized development through industrial transfer. (2) The driving mechanisms exhibit significant spatial heterogeneity: economic density shows diminishing returns in core areas, whereas R&D investment and ecological quality demonstrate increasingly positive effects, with foreign investment’s role evolving positively post-institutional reforms. (3) Regional innovation synergy has formed a preliminary framework, but strengthening sustainable policy mechanisms remains pivotal to advancing market-driven coordination and dismantling administrative barriers. These findings underscore the importance of integrated policy reforms for achieving balanced and high-quality innovation development in administratively coordinated urban agglomerations like BTH. Full article

Farmland abandonment poses a significant threat to China’s food security by contributing to inefficient land use. Utilizing remote sensing data and the multiple cropping index extraction method, this study extracts abandonment cropland information and analyzes its spatiotemporal patterns across China, with its findings validated against the “China Rural Revitalization Survey” (CRRS) data. The results indicate that since the 21st century, China’s cropland abandonment rate has fluctuated around 5.86%, affecting an average of 7.6 million hectares annually. Spatially, cropland abandonment is more severe in southern China, with hotspots clustered around 25° N and 30° N latitudes. This southward shift exacerbates the spatial mismatch between water resources and cropland. Furthermore, abandonment is particularly pronounced in grain production—marketing balance areas and main marketing areas, intensifying pressure on national food self-sufficiency. Slope and fragmentation also drive abandonment, with steeper (>15°) and more fragmented plots showing higher susceptibility. These complex patterns are uncovered through the study’s systematic innovations—a dual-indicator quantification method, a multi-source validation framework, a dynamic spatiotemporal atlas, and a novel interpretation of abandonment multifunctionality, which also positions farmland reuse as a buffer against unemployment risks. We thus recommend addressing land fragmentation as a core strategy, through high-standard farmland construction, innovative contract rights certification, and expanded agricultural socialized services to promote moderate-scale farming. Finally, we urge the adoption of region-specific and category-based recultivation approaches, supported by clear governance priorities. Full article

Sustainable development, which integrates economic progress with environmental stewardship to serve societal needs, seeks a balanced approach to resource utilization and intergenerational equity. Implementing carbon policies to limit emissions in production is an effective measure that also puts pressure on the supply chain’s profitability. Meanwhile, the emergence of the price reference effect affects consumers’ behavior and the decisions of supply chain members. This study constructs a dual-channel supply chain model under three carbon policy scenarios within a manufacturer-led Stackelberg game framework. The model is solved analytically to examine equilibrium outcomes and investigate the influence of channel competition, the price reference effect, and carbon policies on profitability and carbon emissions across different scenarios. The results are as follows. (1) As consumers’ online channel preference increases, manufacturers’ profits turn from falling to rising, especially under a lower carbon tax (higher carbon quota), with profit growing earlier. (2) A stronger price reference effect encourages higher emission reduction efforts, selling prices, and profits in smaller markets. However, this effect can reduce prices and profits due to increased competition and pricing pressure in larger markets. (3) The influence of carbon tax and emission quota on emission reduction and price depends on the initial carbon emission of the product, and their interaction has different impacts on total profits at different initial emission levels. (4) Within the mixed policy, the supply chain can obtain better economic and environmental benefits at a specific range of basic market demand. This study provides valuable references for formulating tactics to cope with low-carbon demand and price reference effects, as well as for developing effective environmental protection policies. Full article