Search Results (618)

This study examines the impact of ESG disclosure, leverage, and profitability on firm value, measured by Tobin’s Q, among 67 non-financial Tadawul-listed companies in Saudi Arabia over the period 2015–2024. ESG disclosure is captured through a manual content-analysis index that scores the proportion of expected environmental, social, and governance items reported by each firm. The study further investigates whether board independence moderates these relationships while controlling for liquidity, firm size, current ratio, capital expenditure, and board size. Methodologically, the study employs the two-step system generalized method of moments (system GMM) estimator, which addresses dynamic persistence, endogeneity, and unobserved heterogeneity. The findings reveal that ESG disclosure has a positive and significant effect on firm value, indicating that the Saudi market increasingly rewards firms that provide broader sustainability-related information. Profitability also exerts a positive influence on Tobin’s Q, while leverage has a negative and significant effect, suggesting that higher debt weakens market valuation. Among the moderating effects, board independence significantly reduces the negative impact of leverage on firm value, although it does not significantly strengthen the positive ESG disclosure–firm value relationship. The results also show that liquidity, firm size, capital expenditure, and board size positively influence firm value. The study’s novelty lies in being the first, to our knowledge, to integrate ESG disclosure, financial structure, profitability, and board independence within a single dynamic firm-value framework over a decade-long panel that brackets the Saudi Exchange’s 2021 ESG disclosure guideline. In doing so, it advances emerging-market ESG research by showing that, under Saudi Arabia’s largely voluntary disclosure regime and concentrated-ownership structure, board independence operates primarily as a risk-monitoring mechanism rather than as an amplifier of disclosure value. The findings imply that regulators should strengthen and progressively mandate ESG reporting frameworks, that investors should treat ESG transparency as value-relevant information, and that firms should view ESG transparency and prudent governance as strategic tools for enhancing market value in line with Vision 2030. Full article

The paper investigates tourists’ willingness to pay (WTP) an increased tourist tax to support the development of accessible tourism. To achieve the research objective, a structured survey was conducted among 452 tourists who spent their holidays in the Ukrainian Carpathians. It has been confirmed that the WTP a higher tourist tax that varies significantly depending on the possible direction of its use. It has been established that in the context of a humanitarian crisis, social inclusion is a more powerful factor of tax loyalty than a traditional environmental programme. A statistically significant relationship was found between WTP an increased tourist tax for the development of accessible tourism and several factors, including respondents’ level of education, income level, frequency of tourist trips over the past five years, current trip expenditure, and perceived accessibility of infrastructure. Consumers’ willingness to voluntarily pay a tourist tax for a specific purpose may suggest that higher tax rates would be publicly acceptable, potentially generating financial resources to support the development of accessible tourism. Full article

During the stage of high-quality economic development, the synergy between advancing county industrial structure and employment growth has become a key issue in county governance. Although existing studies confirm that industrial structure has both creation and substitution effects on employment, few have adopted a configurational perspective to reveal how combinations of multiple factors can jointly promote both advanced county industrial structure and employment growth, thereby achieving industry-employment synergy. From the perspective of inclusive growth, this study incorporates six factors-economic level, financial level, innovation level, human capital, fiscal expenditure, and agricultural resources-into a unified analytical framework under the dimensions of efficiency and equity. Using a mixed method that combines dynamic QCA and regression analysis, and taking 1128 Chinese counties as the sample, this study explores configurational pathways that can simultaneously achieve advanced county industrial structure and inclusive employment growth. The findings are as follows: (1) Four configurational pathways lead to advanced county industrial structure: market-driven with efficiency priority (C1), endowment-substituted with factor concentration (C2), endowment-dependent with efficiency-equity coordination (C3), and talent–innovation dual-driven with government assistance (C4). (2) These four pathways differ in their effectiveness in promoting industry–employment synergy. Configurations C1, C2, and C3 achieve coordinated development of county industry and employment, whereas configuration C4 promotes advanced county industrial structure but inhibits employment growth. The conclusions reveal multiple equivalent pathways for synergistically enhancing county industry and employment, providing a basis for local governments to formulate context-specific industry–employment coordination policies. Full article

Objective: To evaluate the impact of urban–rural health insurance integration on the health outcomes and financial burden of rural older adults. Methods: Utilizing panel data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2013 to 2018, we employed a staggered difference-in-differences model coupled with propensity score matching (PSM-DID) for rigorous causal identification. Results: The policy significantly reduced out-of-pocket medical expenditures for rural households by approximately 5.6% (p = 0.034). Concurrently, significant improvements were observed in both physical health (a 0.092-point reduction in ADL impairment scores) and mental health (a 0.725-point reduction in CES-D depression scores). Mechanism analyses revealed that the integration did not significantly increase the probability of outpatient or inpatient visits—thereby ruling out supplier-induced demand and moral hazard—while effectively reducing the incidence of catastrophic health expenditure by 1.9% (p = 0.004). Heterogeneity analyses indicated that while the financial relief was universally distributed across varying educational levels, the policy dividends were predominantly captured by the younger-old demographic. Notably, the reduction in financial burden was not statistically significant for the oldest-old cohort (aged 75 and older). Conclusions: The urban–rural health insurance integration has achieved a dual dividend of financial protection and health enhancement without triggering the overutilization of medical services. Nevertheless, the unmet care expenses for older adults with severe disabilities underscore the urgent necessity for a secondary safety net, such as long-term care insurance. Full article

Cordyceps militaris is a high-value medicinal mushroom with growing demand in functional-food and nutraceutical markets, yet practical frameworks for small-scale, family-operated cultivation remain limited. This study presents an integrated technical and economic feasibility analysis of small-scale Cordyceps production under two scenarios: a one-room setup (Scenario 1) and a two-room configuration with a shared processing area and staggered scheduling (Scenario 2). Both use consistent biological, operational, and market assumptions with no hired labor, and the analysis covers capital expenditure (CapEx), operating costs (OpEx), profitability, payback, and break-even thresholds, complemented by sensitivity analysis of parameters such as biological efficiency and contamination rates. Both scenarios were technically and financially viable. Scenario 1 achieved a net present value (NPV) of $1761, an internal rate of return (IRR) of 10%, a 4.7-year discounted payback, and a 133% five-year return on investment (ROI); Scenario 2 attained an NPV of $85,437, a 66% IRR, a 1.6-year payback, and a 366% ROI. Because gross margins were consistent across scales, the expansion’s advantage stemmed from more efficient CapEx amortization rather than improved unit profitability. Cordyceps cultivation emerges as a viable family-operated, small-scale enterprise that can diversify family income, generate supplementary or primary earnings, and support urban and rural livelihoods. Full article

This paper documents a fundamental sectoral divergence in capital–employment relationships using UK quarterly data (2014Q1–2024Q4, N = 44). While manufacturing automation studies consistently find negative employment effects, we show that information-intensive service sectors (SIC J: Information and Communication; K: Financial and Insurance; M: Professional/Scientific/Technical) exhibit robust positive co-movement between capital formation and employment. Structural vector autoregression analysis reveals persistent positive employment responses following capital shocks, with effects peaking at 5–6 quarters and remaining significant through 10 quarters. This pattern holds across eight alternative specifications with varying lag structure, variable ordering, and subsample periods. Granger causality tests reveal bidirectional temporal relationships (capital → employment: F = 3.932, p = 0.028; employment → capital: F = 5.659, p = 0.007), indicating joint determination from anticipated demand growth rather than unidirectional technology-driven dynamics. This finding—while complicating causal interpretation—strengthens the contribution by providing honest empirical characterization of coordination mechanisms in information-intensive sectors. Our capital formation proxy measures all investment in AI-intensive sectors (buildings, equipment, conventional IT, emerging AI systems) rather than AI expenditure specifically, creating measurement ambiguity we acknowledge transparently. The sectoral focus (J+K+M sectors with 22–34% AI adoption rates exceeding the 15% economy-wide average) provides indicative evidence that patterns relate to advanced technology deployment, but measurement breadth prevents definitive AI-specific conclusions. The contribution lies not in establishing AI-specific causality—which aggregate time-series methods cannot achieve—but in documenting robust sectoral heterogeneity using methodology comparable to manufacturing displacement studies. The positive association in information-intensive services contrasts sharply with manufacturing’s negative relationship, suggesting technology–employment dynamics vary fundamentally across sectors with different task structures. Three limitations constrain interpretation: (i) recursive identification cannot definitively rule out common demand shocks, (ii) the 44-quarter sample provides limited statistical power for precise magnitude estimation, and (iii) external validity to other countries, time periods, or service sectors remains uncertain. The findings motivate sector-specific rather than economy-wide technology policy approaches, recognizing that extrapolating manufacturing evidence to service-dominated economies may systematically mischaracterize employment dynamics. Full article

This study presents a forecast-driven Advanced Forecasting Model (AFM) and Virtual Power Plant (VPP) framework for a hybrid renewable energy system comprising utility-scale solar PV, wind generation, and a Battery Energy Storage System. Long Short-Term Memory neural networks provide real-time short-term forecasts to dynamically schedule power flows based on battery state-of-charge, grid import limits, and system constraints. Solar irradiance forecasting achieved MAE = 10.674 W/m², RMSE = 16.348 W/m², and MAPE = 14.18%, while wind speed forecasting achieved MAE = 0.880 m/s, RMSE = 1.115 m/s, and MAPE = 22.01%. Two dispatch scenarios were evaluated over a 72 h window: a reactive baseline and the proposed AFM/VPP strategy. The AFM reduced total grid imports by 57.48% (1466.34 MWh to 623.47 MWh), increased renewable utilization, and minimized curtailment. Financial analysis indicates an accelerated break-even (Year 6 vs. Year 9), a higher net present value, and cumulative 20-year profits exceeding R26.01 billion despite marginally higher capital expenditure. Emissions analysis shows annual CO₂ reductions from 123,680 t to 61,841 t, yielding 1.236 million tons of avoided emissions over 20 years. These results confirm that forecast-driven dispatch enhances operational efficiency, economic performance, and environmental sustainability, establishing a scalable approach for VPP operation in renewable-rich energy systems. Full article

Introduction: Musculoskeletal conditions impose a substantial economic burden on the United States (U.S.) healthcare system, but contemporary national estimates of condition-specific spending for common orthopaedic conditions remain limited. This study utilized the 2023 Medical Expenditure Panel Survey (MEPS) to estimate the national prevalence, condition-specific expenditures, and payer distribution for treated knee injuries and shoulder disorders. Methods: Adults with treated knee injuries or shoulder disorders were identified using ICD-10-CM codes from the MEPS Medical Conditions File. Condition-specific expenditures were estimated by linking diagnoses to medical events and payments using the MEPS Condition–Event Link File. Expenditures were aggregated across inpatient, outpatient, office-based, emergency, home health, and prescribed medicine categories. Survey-weighted analyses were used to estimate national prevalence, mean expenditures, service-level spending patterns, and payer distributions. Survey-weighted Gamma generalized linear models with log link were used to examine patient characteristics associated with expenditures among the U.S. civilian noninstitutionalized population with positive condition-specific spending. Results: The analysis identified 2.55 million adults with treated knee injuries and 2.58 million adults with treated shoulder disorders. Mean annual condition-specific expenditures per person were higher for knee injuries ($10,552; 95% CI: $6128–$14,975) than for shoulder disorders ($4310; 95% CI: $3337–$5283). Knee injury expenditures were concentrated in inpatient and home health care, whereas shoulder disorder expenditures were concentrated in outpatient and office-based care. Private insurance, Medicare, out-of-pocket payments, and Worker’s Compensation each contributed to the financial burden, with payer distributions varying by condition. In adjusted models, fair/poor self-rated health and female sex were associated with higher knee injury expenditures, while no covariates were statistically significant for shoulder disorder expenditures. Conclusions: Treated knee injuries and shoulder disorders showed distinct condition-specific expenditure profiles across care settings and payer sources. These findings provide contemporary national benchmarks for orthopaedic spending and may support future research, utilization monitoring, and value-based reimbursement planning. Full article

The regulatory framework in the United Kingdom plays a vital role in promoting investor trust and transparency by mandating that enterprises disclose their social and environmental impacts. This makes the UK an appropriate setting for this study. This research examined how sustainable finance influences investor trust in the London Stock Exchange. The study employed purposive sampling along with specified inclusion and exclusion criteria to assess 17 years of data (2007–2023) from 334 non-financial institutions obtained from Thomson Reuters Eikon DataStream. To mitigate cross-sectional dependence and endogeneity concerns in the data, several estimation methods were used, including the Common Correlated Effects Mean Group (CCEMG), fixed effects with Driscoll-Kraay standard errors, and the Generalized Method of Moments (GMM). The findings revealed that corporate emission reduction policies, environmental expenditures, and green bond issuances had a positive and significant impact on investor trust. Additionally, the moderating effect of regulatory quality on emission reduction policies further enhanced investor trust. Based on these findings, companies are encouraged to strengthen their environmental practices by implementing robust emission reduction policies, increasing environmental investments, and issuing green bonds to support sustainable projects. These efforts should be clearly communicated to investors to highlight the company’s commitment to sustainability and corporate responsibility. Full article

The sustainable recovery of rare earth elements (REE-Y) from electronic waste is critical for clean-energy technologies. Yet, the commercial viability of recovering REE-Y from shredder residue char (SR-char) remains underexplored. Because recovery processes are heavily influenced by operational costs, evaluating economic feasibility alongside metallurgical performance is essential. This study assesses a hybrid physical–chemical process using SR-char, integrating particle size classification and dry magnetic separation with optimized hydrochloric acid leaching. A first-order gross-profit screening model was also developed to evaluate the direct reagent economics of the proposed process. This framework calculates Revenue minus Acid and Neutralization Costs only, excluding capital expenditures (CapEx), labor, utilities, downstream separation losses, and the cost of the magnetic separation step. Results show that magnetic separation at 8000 G pre-concentrated REE-Y to >1800 g/t, and subsequent 10 M HCl leaching (60 °C, 3 h) yielded extractions of ~2000 g/t in the 500–1000 µm fraction. However, the profit model showed that maximizing extraction in the presence of high concentrations of other metals, such as Fe, Ca, and Al, results in net financial losses due to excessive reagent and neutralization costs. We conclude that physical pre-concentration to reduce non-target metal content is a critical commercial prerequisite. This targeted approach reframes the optimization criterion from metallurgical yield maximization to economic feasibility, providing a transferable screening framework for evaluating other complex secondary REE-Y resources where impurity-driven reagent consumption dominates process economics. Full article

Background: In the era of digital transformation, public health systems increasingly rely on digital technologies to improve accessibility, efficiency, and patient outcomes. However, policymakers face significant challenges in allocating limited resources across competing digital health investments characterized by uncertainty and dynamic impacts. Methods: This study introduces the Adaptive Impact–Cost Optimization Theory (AICOT), a hybrid framework integrating fuzzy logic and genetic algorithms to optimize digital health investment portfolios. The model defines the Investment Priority Score (IPS) as a function of cost, expected impact, and implementation feasibility, enabling structured evaluation under uncertainty. A fuzzy inference system with centroid-based defuzzification is used to convert qualitative assessments into quantitative scores, while optimization techniques identify optimal portfolios across different fiscal scenarios. The empirical analysis covers 15 OECD countries (2018–2024) using publicly available datasets. Sensitivity analyses assess robustness under inflation, cost shocks, and changing system priorities. Results: The findings show that blended investment strategies combining routine digital health tools with pandemic-oriented infrastructures yield the highest resilience-adjusted efficiency. Results remain stable across sensitivity scenarios, with pandemic surveillance consistently ranking as a top priority even under increased cost conditions. The model effectively captures cross-country heterogeneity, demonstrating adaptability to different levels of digital maturity. Conclusions: AICOT provides a transparent and policy-relevant decision-support framework that improves resource allocation efficiency and reduces unnecessary expenditures. These contributions support long-term financial sustainability and align with global health objectives, including Universal Health Coverage and Sustainable Development Goal 3 (Good Health and Well-being). Full article

This paper examines how value-added tax (VAT) reforms affected recorded point-of-sale (POS) spending in Saudi Arabia’s restaurant, café, and food service sector during a period of rapid payment digitalization. Two policy shocks are analyzed: the introduction of a 5% VAT in January 2018 and the increase to 15% in July 2020. Using monthly official POS data from January 2016 to January 2024, the study applies an interrupted time-series framework. Baseline estimates are obtained using Generalized Least Squares (GLS) with AR (1) correction. In contrast, seasonal SARIMAX and Error Correction Model (ECM) specifications are used as robustness checks and to distinguish short-run from long-run dynamics. Controls include food and beverage price indices, headline inflation, and COVID-19 disruptions. Results show statistically significant positive level shifts in recorded POS sales after both VAT reforms, with larger measured effects after the 2020 increase. However, the evidence suggests that these changes primarily reflect formalization of transactions, migration toward electronic payments, improved reporting compliance, and intertemporal expenditure timing rather than persistent growth in real demand. Post-reform trend coefficients indicate gradual normalization in subsequent months. ECM estimates suggest that approximately 56% of short-run disequilibrium is corrected within one month. Findings are robust across alternative specifications. The paper contributes new evidence from the Gulf region by showing that retail transaction indicators may overstate real consumption responses when tax reforms coincide with rapid financial digitalization. From a sustainability perspective, the findings highlight the role of digital financial systems and modern tax administration in improving economic transparency, strengthening fiscal sustainability, enhancing formal-sector integration, and supporting the institutional transformation objectives of Saudi Vision 2030. The results imply that fiscal-policy evaluations should jointly account for tax administration reforms and changes in payment technology. Full article

High levels of photovoltaic penetration and synchronous generator decommissioning are weakening grid strength and increasing voltage support requirements, yet most studies still assess support technologies primarily based on technical performance rather than full lifecycle utility value. The key gap is the absence of a consistent framework that links technical performance to lifecycle cost, tariff impact and investment outcomes across competing technologies. This study addresses that gap by developing a transparent utility-oriented assessment framework to compare Static Var Compensator (SVC), Static Synchronous Compensator (STATCOM), Synchronous Condenser (SC) and grid-forming BESS (BESS-GFM) options in a weak high-PV penetration network. Quasi-dynamic simulations on an IEEE 9-bus system were used to quantify technical benefits, which were then converted into lifecycle financial metrics within a total expenditure (TOTEX)-based model and combined with practical decision criteria through multi-criteria decision analysis (MCDA). The results show that while all four technologies improve system performance, their overall value differs once cost, tariff impact, risk and flexibility are considered. Under the adopted assumptions, STATCOM provides the best overall balance and ranks highest. Full article

Energy poverty poses a critical threat to global sustainable development by undermining household well-being and deepening social inequality. This study draws on data from 17,778 households across six waves of the China Family Panel Studies (CFPS) from 2012 to 2022 to examine the dynamics, determinants, and predictive patterns of household energy poverty in China. Our study also enhances and optimises the four-quadrant classification framework within the Low-Income, High-Cost (LIHC) framework, which jointly evaluates income and energy expenditure using dynamic thresholds. This approach enables us to identify not only households experiencing energy poverty but also those facing heightened vulnerability. In the sample, 7.96% were classified as energy-poor, 29.10% as at risk of energy poverty, 24.14% as at risk of income poverty, and 38.81% as not at risk, indicating that the number of households facing hidden risks far exceeds that of households identified as poor using traditional binary diagnostic methods. Next, we implement a Bayesian-optimised Extreme Gradient Boosting (XGBoost) model to improve predictive accuracy. Thus, the trained model achieved a prediction accuracy of 78%. We employ Shapley Additive exPlanations (SHAP) analysis to interpret the relative importance and interaction of explanatory variables. Our findings reveal three key patterns. First, households at risk of energy insecurity substantially outnumber those already in energy poverty, indicating a large latent vulnerable population that conventional measures often overlook. Second, housing conditions and energy expenditures remain the dominant structural drivers of energy poverty; however, financial pressures related to healthcare, education, and other non-energy expenditures increasingly intensify vulnerability. Third, Bayesian optimisation significantly enhances the model’s capacity to capture nonlinear relationships and complex household heterogeneity. By integrating dynamic measurement with interpretable machine learning, this study advances methodological approaches to energy poverty assessment and provides robust empirical evidence for early-warning systems, differentiated governance strategies, and targeted policy design in the context of China’s energy transition. Full article

Although climate adaptation has become increasingly visible in agricultural policy across OECD countries, it remains unclear to what extent this orientation is reflected in agricultural support through more sustainability-oriented instruments. This study examines whether climate adaptation capacity conditions the relationship between drought stress and the climate orientation of agricultural support. Using a balanced panel of 11 OECD policy units over 2005–2023 (N = 209), we estimate two-way fixed-effects models interacting a three-pillar Adaptation Capacity Index (ACI), governance, risk management, and financial/implementation capacity, with the 12-month Standardized Precipitation–Evapotranspiration Index (SPEI-12). Adaptation capacity does not display a systematic association with the climate-aligned share of agricultural support under average conditions but becomes more consequential under drought conditions. Under severe drought, a one-unit increase in overall capacity is associated with a 0.73 percentage-point increase in the climate-aligned support share (p < 0.01). Governance capacity displays a more gradual marginal-effect profile, whereas risk management and financial/implementation capacity exhibit stronger non-linear patterns concentrated at higher levels of institutional maturity. In lower-capacity contexts, drought conditions are not associated with a stronger climate-aligned support share, suggesting more limited adaptation-oriented adjustment within the support system. Overall, the findings suggest that the climate orientation of agricultural support depends not only on expenditure composition itself, but also on the institutional capacity context through which climatic stress is translated into policy adjustment. Full article