This study examines factors associated with external auditors’ intention to engage in sustainability assurance in Vietnam, where sustainability reporting is expanding while assurance practice remains uneven. The research model is informed by institutional theory, self-efficacy theory, and the attitude-intention relationship in the Theory of Planned Behavior (TPB). Survey data from 317 external auditors working in independent audit firms were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that perceived regulatory and institutional pressure, perceived sustainability literacy, and sustainability assurance self-efficacy are positively associated with attitude toward sustainability assurance, whereas professional skepticism is not significantly associated with attitude. Perceived regulatory and institutional pressure, sustainability assurance self-efficacy, and attitude are positively associated with intention to engage. Mediation analysis shows significant indirect relationships through attitude for perceived regulatory and institutional pressure, perceived sustainability literacy, and sustainability assurance self-efficacy, but not for professional skepticism. The study extends sustainability assurance research by examining auditors’ individual-level readiness and distinguishing how institutional signals, perceived sustainability literacy, task-specific self-efficacy, and attitude relate to readiness to engage in sustainability assurance. The findings highlight the professional capacity needed to support the development of credible sustainability reporting and assurance in an emerging economy.
The institutional processes through which public debt audit findings are translated into corrective action remain insufficiently understood, particularly where fragmented administrative records and fiscal stress coexist with established debt-reporting practices. This study examines the evolution of public debt reporting in Ghana between 2016 and 2025 and traces the institutional response to a substantial discrepancy identified in the Auditor-General’s 2024 Whole-of-Government Accounts (WGA). A longitudinal embedded single-case study design was employed, combining systematic coding of Annual Public Debt Reports (APDRs) across eight disclosure domains with process tracing of the subsequent institutional response. Debt indicators were examined to contextualise the findings rather than to establish a causal relationship between audit intervention and fiscal outcomes. The analysis shows that annual debt reporting became an established practice, accompanied by broader disclosure of debt portfolio characteristics, costs, risks, guarantees, on-lending and contingent liabilities. Nevertheless, a GH¢138.91 billion difference was reported between the debt balance consolidated by the Controller and Accountant-General’s Department (CAGD) and the corresponding Ministry of Finance record. Subsequent parliamentary scrutiny indicated that a substantial part of this discrepancy arose from differences in consolidation boundaries, following which the institutions reconciled their figures. This sequence illustrates how an audit finding can progress through detection, disclosure, deliberation and correction, although limited publicly documented evidence was identified of sustained improvements in preventive controls. Meanwhile, Ghana’s debt-to-GDP ratio increased from 56.8% in 2016 to approximately 80% in 2020 before declining to 44.7% by the end of 2025, providing fiscal context without demonstrating that audit contributed to these changes. An Audit–Accountability Transmission Mechanism (AATM) is developed to distinguish the identification of audit findings from their institutional uptake and potential governance consequences. The framework highlights inter-agency reconciliation, parliamentary scrutiny and recommendation follow-up as critical mechanisms through which audit findings may be translated into corrective action and institutional accountability. The findings also demonstrate the importance of distinguishing discrepancies arising from different reporting boundaries from errors in underlying debt records. Effective public debt oversight therefore requires not only transparent reporting and independent scrutiny but also documented reconciliation procedures, traceable corrective actions and verifiable improvements in preventive controls.
Efficient logistics processes are essential to the operational performance of process-industry companies, where material receipt, warehousing, and internal distribution are closely connected with production continuity. However, evaluating these processes remains difficult because logistics performance depends on multiple criteria with different levels of importance, while conventional assessments often provide limited information about the relative efficiency of individual logistics units. This study investigates the efficiency of logistics activities through an integrated decision-analytics framework combining the Full Consistency Method (FUCOM) and Data Envelopment Analysis (DEA). FUCOM was used to determine the relative importance of the evaluation criteria, and DEA was applied to measure the technical efficiency of the logistics units. The framework was examined through a case study of the Modriča Oil Refinery, covering material receipt, warehousing, and the internal distribution of products to production facilities. The results showed clear differences in efficiency among the analyzed logistics segments and identified the processes that represented critical points within the logistics system. The sensitivity analysis further confirmed the stability of the evaluation results under changes in the criteria weights. These findings indicate that combining criterion weighting with efficiency measurement provides a structured basis for identifying operational weaknesses and setting improvement priorities. The proposed framework supports data-informed logistics decisions in the process industry and can be adapted to comparable industrial settings involving interconnected logistics activities.
This study investigates the determinants of household intention to adopt solar photovoltaic (PV) systems in an island community using a stimulus organism response (SOR)-based framework informed by selected concepts from the Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM). Data were collected from 100 households in Pulau Tidung, Seribu Islands, Indonesia, using purposive sampling and analyzed through partial least squares structural equation modeling (PLS-SEM) to examine the effects of economic, environmental, social, regulatory, technical, and market stimuli on attitude and adoption intention. The results indicate that attitude toward solar PV exhibited the largest positive association with adoption intention (β = 0.827, p < 0.001), while economic stimulus was positively associated with attitude (β = 0.411, p = 0.018). Regulatory stimulus directly increases adoption intention (β = 0.349, p = 0.042), whereas technical barriers significantly reduce it (β = −0.306, p = 0.036). Environmental, social, and market stimuli do not exhibit statistically significant effects. The model explains 95.5% of the variance in adoption intention (R² = 0.955), indicating substantial explanatory power within the study context. These findings demonstrate that favorable attitudes, supportive regulatory conditions, and reduced technical barriers are central to strengthening household solar PV adoption intentions in island communities. Accordingly, policies should combine targeted economic incentives and regulatory support with accessible technical assistance and community-based implementation mechanisms to facilitate renewable energy uptake in geographically constrained areas.
Exposure to heavy metals during pregnancy poses significant risks to maternal and child health. This study aims to analyze trends in research on heavy metal exposure in pregnant women using bibliometric analysis and systematic review. A total of 125 publications from the Scopus database (1973–2023) were analyzed. The bibliometric analysis examined publication trends, geographical distribution, and researcher collaboration. A systematic review assessed statistical methods, focusing on advanced models like Bayesian Kernel Machine Regression (BKMR) and Weighted Quantile Sum (WQS) regression, as well as traditional methods like linear and logistic regression. The bibliometric analysis showed an increasing number of studies, with the United States leading in publications, followed by China and India. The systematic review found that advanced models such as BKMR and WQS regression are increasingly used to evaluate interactions between heavy metal mixtures and pregnancy outcomes. However, many studies still rely on traditional regression models, highlighting a gap in the adoption of more advanced techniques. The study highlights the particular analytical capabilities of advanced statistical models in examining complex interactions between heavy metal mixtures and pregnancy outcome in understanding complex interactions between heavy metal mixtures and pregnancy outcomes. It also points to the need for greater adoption of these methods to improve risk assessments and inform public health policies. In conclusion, advanced modeling techniques, particularly BKMR and WQS regression, are crucial for understanding the risks of heavy metal exposure during pregnancy and guiding public health interventions.
This study aims to systematically review the literature on CO₂ emissions, carbon intensity, and sustainable economic growth in the Western Balkans, with particular attention to macroeconomic, institutional, financial, industrial, sustainability, and energy-related factors. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, the review was conducted using the Scopus database and structured search strings covering CO₂ emissions, carbon intensity, macroeconomic drivers, energy transition, green finance, urbanization, industrial structure, and sustainable development. After identification, screening, eligibility assessment, and quality assessment, 30 studies were included in the final qualitative synthesis. The findings indicate that CO₂ emissions, carbon intensity, and sustainable economic growth in the Western Balkans are influenced by the interaction among economic growth, energy consumption, fossil-fuel dependence, renewable energy deployment, trade openness, financial development, institutional quality, urbanization, construction activity, carbon pricing, and European Union (EU) climate policy instruments such as the carbon border adjustment mechanism (CBAM). The energy structure emerges as a key determinant of both carbon intensity and CO₂ emissions in the Western Balkans. Continued reliance on coal and inefficient energy systems is associated with higher emissions, whereas renewable-energy deployment and green investment contribute to lower CO₂ emissions and improved carbon efficiency. At the same time, this systematic review identifies important regional differences in fossil-fuel dependence, exposure to carbon-related trade risks, urbanization pressures, construction activity, renewable-energy potential, green investment, and financial-sector transition risks across the Western Balkans. These differences indicate that the region does not follow a uniform decarbonization pathway. The study concludes that effective decarbonization requires an integrated policy framework combining renewable-energy development, stronger institutions, green finance, carbon-pricing mechanisms, sustainable urbanization, and industrial upgrading.
Rooftop photovoltaic (PV) systems are a practical option for Baghdad, but their performance depends on module technology, mounting strategy, row spacing, and near-shading. This study integrates SketchUp/Skelion and PVsyst to evaluate grid-connected rooftop PV systems on the College of Education building at Mustansiriyah University, Baghdad. Seventeen configurations were simulated using monocrystalline and heterojunction (HJT) modules, fixed, seasonal, and two-axis mounting strategies, portrait and landscape layouts, row spacings of 0, 0.5, and 1.0 m, and practical losses including soiling, aging, unavailability, and auxiliary consumption. The objective was to combine a realistic 3D rooftop model with PVsyst near-shading analysis and compare technical, economic, and environmental performance. HJT modules outperformed comparable monocrystalline cases under Baghdad's hot conditions because of their lower power temperature coefficient. The two-axis HJT case achieved the highest annual energy production (272,308 kWh/yr), while the seasonal HJT case achieved the highest performance ratio (85.22%). The fixed landscape HJT system provided a strong practical balance, producing 244,305 kWh/yr and 1,871 kWh/kWp/yr with a performance ratio of 85.19%. Under the stated 25-year economic assumptions, its discounted levelized cost of energy (LCOE) was 0.0291 USD/kWh, with a simple payback period (PBP) of 3.1 years. Increasing row spacing improves specific yield by reducing self-shading, but total rooftop output decreases because fewer rows fit on the roof. Over the 25-year study period, the simulated systems avoid approximately 1,840.6–4,043.8 tCO$_2$ relative to grid electricity. Overall, the fixed landscape HJT arrangement is a practical candidate for rooftop PV deployment in Baghdad and similar hot, dry urban environments.
The fruit-processing agroindustry plays a strategic role in reducing post-harvest losses and enhancing agricultural value creation in developing countries. However, small and medium-sized enterprises (SMEs) in this sector face multidimensional operational challenges, necessitating a holistic and structural evaluation of their performance system rather than fragmented, financially oriented assessments. This study aimed to analyze the multidimensional performance and uncover the hierarchical interdependencies of performance indicators within fruit-processing agroindustry SMEs. The methodology employed a sequential mixed-method design integrating the balanced scorecard (BSC) and interpretive structural modeling (ISM) combined with cross-impact matrix multiplication applied to classification (MICMAC, from the French “matrice d’impacts croisés multiplication appliquée à un classement”) analysis. The framework evaluated two representative product typologies in Malang Raya, Indonesia: a dry-processing case (fruit chips) and a liquid-processing case (fruit juice). The comparative BSC results revealed distinct performance profiles; the dry-processing case demonstrated stronger financial performance, whereas the liquid-processing case excelled in customer satisfaction and asset turnover. Concurrently, both typologies exhibited a significant drop in quality control, characterized by negative scores on the number of defective products, driven by scaling production volume over capacity boundaries. The ISM analysis structured these cross-perspective metrics into a robust nine-level hierarchy, identifying the number of machines as the ultimate foundational driver possessing the highest driving power (DP) of 17 and minimal dependence power (D). The MICMAC matrix further isolated eight independent driving variables, nine dependent outcome variables, and two autonomous variables, with no linkage variables present. These findings indicate that long-term enterprise competitiveness is structurally anchored to basic machinery availability and workforce competency development rather than downstream marketing actions. Theoretically, this study extends the BSC into a structurally informed paradigm by mapping structural influence pathways under resource constraints. Practically, it provides managers and extension institutions with a systematic diagnostic sequence to prioritize infrastructure investments over uniformly distributed improvement efforts.
Lightweight personal thermal-management systems are attractive for outdoor heat exposure where space cooling is unavailable. A low-power, solar-assisted garment with dual forced-air ventilation was fabricated and tested outdoors on a single day (08:00–16:00; $n$ = 9 nominal hourly observations, eight elapsed one-hour intervals) at ambient temperatures of 32.5–43.1 ℃, relative humidity of 20–34%, and solar irradiance of 420–950 W/m$^2$. The apparent fan-OFF/fan-ON garment-temperature contrast, $\Delta T_{\text{g}}=T_{\text{OFF}}-T_{\text{ON}}$, was positive at all nine observations, with a mean of 3.89 ± 0.97 ℃ and a maximum of 5.0 ℃ at 14:00. Based on the reported combined airflow and $\Delta T_{\text{g}}$, the estimated sensible cooling rate was $\dot{Q}_{\text{s,est}}$ = 38.43–99.52 W (nine-point mean 75.08 W), and the ventilation cooling performance ratio was VCPR = $\dot{Q}_{\text{s, est}}/P_{\text{fan}}$ = 13.72–35.54 (nine-point mean 26.81); these are engineering screening estimates rather than calorimetric measurements or refrigeration coefficient of performance (COP) values. Trapezoidal integration over the eight elapsed one-hour intervals gave a fan-energy demand of 22.40 Wh, a photovoltaic (PV) panels contribution of 13.08 Wh, and an auxiliary-energy requirement of 9.33 Wh. The PV contribution therefore accounted for 58.4% of the fan-energy demand during the test period. Single-day associations with the ambient conditions are reported descriptively, without causal interpretation. The results provide proof-of-concept evidence of a consistent apparent garment-temperature contrast and a quantified partial PV load offset under the hot-dry conditions tested, and they define an 11.19 Wh storage target for autonomous daytime operation.
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