Search Results (914)

Plastic recycling is critical to transitioning toward a circular economy (CE), yet traceability systems for recycled plastics remain unevenly adopted. While effective traceability supports transparency, compliance, and supply chain accountability, its implementation is shaped not only by technological readiness but also by organisational behaviours and strategic priorities. This study explores how traceability adoption is influenced by company size, internal CE strategy, and perceptions of cost, risk, and regulatory demand. A survey of 65 Australian industry stakeholders reveals that 76% of companies with a CE strategy have implemented traceability systems, compared to 42% without. Larger firms report higher adoption rates than small and medium enterprises, largely due to resource advantages and differing interpretations of traceability’s value. Key barriers include high perceived costs, lack of standardised frameworks, and scepticism toward digital tools. Conversely, motivations such as reputational benefits, regulatory alignment, and inter-organisational trust were identified as enablers, alongside emerging technologies like blockchain and chemical tracers. The findings underscore the role of organisational context in shaping traceability practices and highlight the need for tailored interventions. Recommendations include financial incentives, harmonised standards, and sector-specific guidance that address not only technical gaps but behavioural and structural factors limiting uptake. Positioning traceability as an integrated organisational strategy may accelerate its adoption and support broader circular economy outcomes across the plastics value chain. Full article

Background: The COVID-19 pandemic led to an unprecedented global health and economic crisis, and vaccination emerged as a critical intervention to control the spread of the virus and mitigate its impact on health systems and economies. Despite the rapid development and deployment of vaccines, the financial commitments required for these vaccination programs are substantial, necessitating a comprehensive understanding of the associated costs to inform future public health strategies and resource allocation. Method: This analysis estimates the global, regional, and national economic costs of COVID-19 vaccination across 234 countries and regions in the period 2020–2023, consisting of vaccine procurement costs and administration costs. Result: As of 31 December 2023, the global costs of COVID-19 vaccination programs were estimated at USD 246.2 billion, with vaccine procurement accounting for approximately USD 140.2 billion and administration costs totaling USD 96.4 billion. Globally, a cumulative total of 136.9 billion doses of COVID-19 vaccines had been administered. Factoring in an estimated wastage rate of 10%, it is projected that approximately 150.6 billion doses were used. On a global scale, the average number of vaccine doses administered per capita was estimated at 1.73. The mean cost per capita was USD 17.70 (95% CI: USD 15.84–19.56) for vaccine procurement and USD 12.16 (95% CI: USD 10.29–14.02) for administration, resulting in a total average cost of USD 29.85 (95% CI: USD 26.33–33.37) per capita. Significant disparities in costs were observed across income groups and regions. High-income countries incurred a notably higher average cost per capita of USD 76.90 (95% CI: USD 72.38–81.41) in contrast to low-income countries, where the per capita cost was USD 7.20 (95% CI: USD 5.38–9.02). For middle-income countries, the average per capita costs were USD 15.02 (95% CI: USD 10.64–19.40) in lower-middle-income countries and USD 28.21 (95% CI: USD 23.60–32.83) in upper-middle-income countries. Regionally, the Americas (AMR) reported the highest total cost at USD 70.8 billion, with an average per capita cost of USD 65.23 (95% CI: USD 56.18–74.28). The Western Pacific Region (WPR) followed with a total cost of USD 63.9 billion and an average per capita cost of USD 31.93 (95% CI: USD 20.35–43.51). Conversely, the African Region (AFR) had the lowest total spending at USD 10.8 billion and a per capita cost of USD 8.85 (95% CI: USD 5.34–12.37), reflecting both lower vaccine procurement and administration costs. The European Region (EUR) recorded a high average per capita cost of USD 53.36 (95% CI: USD 46.79–59.94), with procurement costs at USD 31.28 (95% CI: USD 27.41–35.14) and administration costs of USD 22.09 (95% CI: USD 19.31–24.87). Conclusions: The global rollout of COVID-19 vaccination revealed substantial variation in cost structures across income groups. Procurement costs imposed greater burdens on low- and lower-middle-income countries, whereas delivery and administration costs dominated in higher-income settings. These disparities highlight persistent fiscal inequities and emphasize the need for stronger international coordination and cost transparency to enhance equity, efficiency, and preparedness in future vaccination efforts. Full article

The green economy has become an economic necessity and a cultural discourse due to the rapid global movement towards sustainability. This paper discusses the representation of green economy in Qatar and Malaysia, two countries with different political and cultural background but similar ambitions to attain sustainable development on social media. Through the application of qualitative techniques, namely thematic analysis and critical discourse analysis, the re-search analyzed Twitter, Facebook, Instagram, and LinkedIn posts discussing sustainability, renewable energy, and green innovation by using hashtags and stories on the topic. The results indicate that four major themes exist in both settings, and they are sustainability as national pride and identity, corporate–government branding of green efforts, grassroot and citizen involvement, and conflicts around contradictions and skepticism. Green economy in Qatar is constructed as a symbol of prestige and international presence, which is directly connected to the Qatar National Vision 2030, and popularized at the state and corporate levels. Big projects, financial solutions like green bonds, and sustainable infrastructure are mentioned in narratives and criticism is afforded little space. The environmental sustainability is part of cultural representation and collective accountability, grassroots mobilization, youth activism, and defiance of official and corporate language in Malaysia. A dynamic and critical digital discourse is often criticized by the citizens when they face perceived greenwashing. The research adds to the theoretical knowledge of understanding of framing theory that civic space plays a role in the development of sustainability discourses and the importance of critical discourse analysis in studying power relations in environmental discourse. In practice, the study recommends that Qatar should engage its citizens in more than just symbolic branding; Malaysia should enhance transparency and consistency of its policies to curb the skepticism of its people. In general, the paper highlights the fact that social media is not simply a medium of communication but rather a controversial field on which the definitions of sustainability are actively discussed. Full article

Background/Objectives: Lung cancer (NSCLC), which accounts for approximately 85% of lung cancers, exhibits marked heterogeneity that complicates molecular characterization and treatment selection. Recent advances in deep learning (DL) have enabled the extraction of genomic-related morphological features directly from routine Hematoxylin and Eosin (H&E) histopathology, offering a potential complement to Next-Generation Sequencing (NGS) for precision oncology. This review aimed to evaluate how DL models have been applied to predict molecular alterations in NSCLC using H&E-stained slides. Methods: A systematic search following PRISMA 2020 guidelines was conducted across PubMed, Scopus, and Web of Science to identify studies published up to March 2025 that used DL models for mutation prediction in NSCLC. Eligible studies were screened, and data on model architectures, datasets, and performance metrics were extracted. Results: Sixteen studies met inclusion criteria. Most employed convolutional neural networks trained on publicly available datasets such as The Cancer Genome Atlas (TCGA) to infer key mutations including EGFR, KRAS, and TP53. Reported areas under the curve ranged from 0.65 to 0.95, demonstrating variable but promising predictive capability. Conclusions: DL-based histopathology shows strong potential for linking tissue morphology to molecular signatures in NSCLC. However, methodological heterogeneity, small sample sizes, and limited external validation constrain reproducibility and generalizability. Standardized protocols, larger multicenter cohorts, and transparent validation are needed before these models can be translated into clinical practice. Full article

Large language model (LLM)-based virtual patient (VP) simulations are emerging to complement traditional medical and nursing education by enabling safe, repeatable, and context-rich clinical practice. This review synthesizes recent developments from 2023 to 2025, mapping implementation approaches, data practices, evaluation methods, and cross-cutting challenges across forty studies. Six implementation categories are identified: scenario generation; prompt-driven VPs; feedback-integrated automated scoring; realism- and adaptability-enhanced systems; knowledge-driven and multi-agent hybrids; and mental health-oriented systems. The analysis summarizes dataset usage (including knowledge sources and governance) and evaluation frameworks, and it introduces quantitative indicators for reproducible assessment. Persistent challenges include factual accuracy, role consistency, emotional realism, and ethical and legal accountability. Overall, LLM-based VP systems show growing potential to extend simulation-based learning, but stronger evidence from multi-site controlled studies, standardized metrics, transparent reporting (model versions, prompts), and robust data governance is needed to establish educational validity and generalizability. Full article

This study investigates the influence of pressure groups on the structure of the Greek economy, emphasizing their function as intermediaries between civil society and policymaking institutions. The significance of this research lies in revealing how organized interests—operating in an environment of informal and weakly regulated lobbying—shape sectoral dynamics and policy outcomes. The central hypothesis is that sectors represented by strong and well-organized pressure groups, such as manufacturing, tourism, and public administration, exhibit higher and more stable shares of Gross Value Added (GVA) due to their lobbying capacity and institutional access. To test this hypothesis, the paper integrates qualitative institutional analysis with a quantitative econometric model based on sectoral data from 2013 to 2023. The descriptive results indicate patterns consistent with the hypothesis that organized pressure groups are associated with sectoral resilience and performance. Nevertheless, the findings also suggest that excessive or unregulated influence may distort economic allocation and weaken transparency. The study concludes that establishing clearer oversight and accountability mechanisms is essential to ensure that the role of pressure groups supports democratic integrity and balanced economic development. Full article

The world is far from meeting the goals of the Paris Agreement of limiting the rise of global temperature to below 1.5 °C, with dire consequences for Small Island Developing States (SIDS) in particular. If SIDS are to address their climate vulnerabilities through policy-induced resilience building, they need to have a robust governance framework in place that coherently addresses climate change adaptation and disaster risk reduction. What would such a governance framework look like? To address this question, we carried out a systematic literature review of papers published between 1992 and 2023. Our review reveals that the governance around climate change adaptation and disaster risk reduction is relatively weak in SIDS. However, the analysis of barriers and enablers unveils the contours of a proposed three-tiered governance framework, the application of which needs to be contextualised: Tier 1 comprises three key pillars: Policy Planning, Institutional Arrangements, and Laws and Regulations; Tier 2 identifies the principles of transparency, accountability, equity, legitimacy, and subsidiarity; the core pillars and the principles are nested within a broader Tier 3 comprising democratic processes (rule of law), religious and cultural values, and political commitment. In order for SIDS to fight the existential threat of climate change, the proposed framework will allow SIDS to better understand their climate governance framework and deliver low-carbon, climate resilient development within the broader ambit of sustainable development. This framework also addresses the weakness in previous studies, which consider dimensions, principles, and enabling an environment of good governance on equal footing. We illustrate this framework using the analogy of the lotus flower. Full article

Buildings account for approximately one-third of global energy usage and associated carbon emissions, making energy benchmarking a crucial tool for advancing decarbonization. Current benchmarking studies have often been limited to mainly the annual scale, relied heavily on simulation-based approaches, or employed regression methods that fail to capture the complexity of diverse building stock. These limitations hinder the interpretability, generalizability, and actionable value of existing models. This study introduces a hybrid AI framework for building energy benchmarking across two time scales—annual and monthly. The framework integrates supervised learning models, including white- and gray-box models, to predict annual and monthly energy consumption, combined with unsupervised learning through neural network-based Self-Organizing Maps (SOM), to classify heterogeneous building stocks. The supervised models provide interpretable and accurate predictions at both aggregated annual and fine-grained monthly levels. The model is trained using a six-year dataset from Washington, D.C., incorporating multiple building attributes and high-resolution weather data. Additionally, the generalizability and robustness have been validated via the real-world dataset from a different climate zone in Pittsburgh, PA. Followed by unsupervised learning models, the SOM clustering preserves topological relationships in high-dimensional data, enabling more nuanced classification compared to centroid-based methods. Results demonstrate that the hybrid approach significantly improves predictive accuracy compared to conventional regression methods, with the proposed model achieving over 80% $R^2$ at the annual scale and robust performance across seasonal monthly predictions. White-box sensitivity highlights that building type and energy use patterns are the most influential variables, while the gray-box analysis using SHAP values further reveals that Energy Star^® rating, Natural Gas (%), and Electricity Use (%) are the three most influential predictors, contributing mean SHAP values of 8.69, 8.46, and 6.47, respectively. SOM results reveal that categorized buildings within the same cluster often share similar energy-use patterns—underscoring the value of data-driven classification. The proposed hybrid framework provides policymakers, building managers, and designers with a scalable, transparent, and transferable tool for identifying energy-saving opportunities, prioritizing retrofit strategies, and accelerating progress toward net-zero carbon buildings. Full article

In recent years, public discourse on pesticide impacts has increasingly recognized institutional and structural racism as key drivers of health disparities in Black, Indigenous, and People of Color (BIPOC) communities. While pesticides are vital for crop protection from causing yield losses, extensive research highlights their adverse effects on environmental quality and human health. These impacts disproportionately burden BIPOC populations, making pesticides a major environmental justice (EJ) concern like many other environmental pollutants. Despite progress in understanding these effects and advancing EJ, significant technical, social, and policy gaps remain. The objective of this review is to systematically examine critical gaps in technical, social, and policy dimensions, as well as the environmental and human health impacts of pesticide exposure on BIPOC communities in the United States, through the lens of environmental justice. This review synthesizes 128 sources peer-reviewed articles, books, reports on pesticides, EJ, and BIPOC communities in the U.S. Key findings reveal uneven distribution of pesticide-related health and environmental burdens along racial, ethnic, and socioeconomic lines. Non-Hispanic Blacks and Mexican Americans exhibit higher pesticide biomarkers and greater exposure risks than non-Hispanic Whites. Structural racism and classism, rooted in historical systems, perpetuate these inequities, compounded by regulatory failures and power imbalances. In addition, the EPA has flagged 31 pesticide manufacturing facilities for “Significant Violations” of key environmental laws, including the Clean Air Act, Clean Water Act, and Resource Conservation and Recovery Act. These systemic issues underscore urgent needs for transparency, accountability, and equitable policy reform. An EJ framework exposes critical knowledge gaps and calls for structural changes to ensure equal protection and responsive policies for the most affected communities. Full article

This systematic review examines how sustainability is utilized by government institutions in reporting and tracking social and environmental impacts. As a result of the Prisma 2020 guidelines, we examined 84 papers published between 2009 and December 2024 and identified four key themes: sustainability reporting procedures, social re-management, incorporating sustainability into decision-making, and stakeholder engagement. The findings suggest significant reporting gaps in the public sector and the need for better systems and practices. This study emphasizes both theoretical and practical consequences, and it recommends strengthening transparency and responsibility, evolving the role of sustainability accounting in public institutions. It also identifies critical areas to address in future research, ensuring the alignment of public sector objectives. This study—by including difficulties in reporting and visualizing how accounting practices can be developed toward sustainability—contributes findings on sustainability can be used to improve governance and accountability in the public sector. However, a limitation is that this review only relies on the Web of Science (WoS) database, which can affect the comprehensiveness of our findings. Potential omissions of relevant databases, such as Scopus or Google Scholar, should be noted, and future research could be enhanced with the addition of a wider range of resources for more comprehensive analysis. Full article

This study explores the impact of environmental accounting practices on corporate environmental performance in Greek enterprises. Grounded in environmental management accounting (EMA), strategic management theory, Stakeholder Theory, and Institutional Theory, it employs a quantitative analysis of data collected via a Likert-type questionnaire in 2024. The focus lies in GRI-based indicators, green technologies, environmental investments, and reporting mechanisms. While international standards such as ISO 14001 and EMAS are considered conceptually, they are not empirically assessed. Data were analyzed using IBM SPSS Statistics (version 29.0) and SmartPLS (version 4.0). The results show that organizations implementing structured environmental accounting systems experience enhanced environmental performance, including greater transparency, regulatory compliance, and innovation capacity. This study fills a gap in the Greek context and emphasizes the strategic role of environmental accounting in advancing sustainability and competitiveness. Full article

This paper examines the interrelationship between Corporate Governance (CG), Internal Control System (ICS), and Organizational Performance (OP), with a particular focus on the effectiveness of the ICS in relation to the quality of its components. Drawing on recent literature and empirical evidence, the study demonstrates that strong governance frameworks—characterized by board independence, effective audit committees, and proactive risk management—are closely linked to robust internal control environments. Together, these mechanisms enhance transparency, reduce risks, and foster stakeholder trust. The analysis further highlights that governance and internal control are evolving beyond compliance, increasingly serving as strategic levers for creating sustainable value. The findings underscore important implications for practitioners and policymakers. Organizations are encouraged to strengthen internal controls, invest in audit and risk management capacity, and embed ethical and sustainability considerations into governance structures. Regulators, in turn, should support frameworks that promote both accountability and innovation. Overall, the study contributes to a deeper understanding of how governance and control mechanisms can secure organizational resilience and drive long-term performance in a rapidly changing business environment. Full article

This study conducts a bibliometric analysis of the scientific literature on digital, automated, and AI-assisted accounting systems. The data include documents listed in the Web of Science and Scopus databases. The analysis identifies the main authors, countries/territories, sources, and thematic trends. The results reveal that the scientific output within this research field has increased since 2018, emphasising the integration of artificial intelligence (AI), robotic process automation, and blockchain technologies in accounting. The findings also suggest that automation enhances efficiency, accuracy, and reliability while also raising concerns about ethics, cybersecurity, and job displacement. This study evaluates the accounting research from early discussions on information systems and automation to current topics such as digital transformation, sustainability, and intelligent decision-making. Furthermore, it contributes to the understanding of the scientific development of digital accounting and addresses future research directions involving AI and machine learning for predictive analytics and fraud detection, blockchain for secure and transparent accounting systems, sustainability through the integration of ESG reporting, and interdisciplinary collaboration between accounting, computer science, and business management to develop intelligent financial systems. The findings provide insights for academics and practitioners aiming to understand the ongoing digital transformation of accounting systems. Full article

Background/Objectives: India’s private healthcare sector remains fragmented, with weak primary care, uneven secondary services, and tertiary care accessible to few. Fee-for-service payments and indemnity-style insurance distort prices and fragment accountability. This paper develops a conceptual, theory-driven framework for integrating financing and delivery so that prices reflect social opportunity costs and competition rewards value rather than volume. Methods: A comparative synthesis of international integration models covering Israel, the United States, Spain, Brazil, and the United Kingdom was undertaken. Each exemplar was analysed for ownership form, market maturity, and regulatory capacity, and interpreted using four strategic management theories: Contingency theory, the Resource-based view, Dynamic capabilities, and Institutional theory. These perspectives were combined to construct a contingency-based typology tailored to India’s mixed health system. Results: Two state-contingent integration pathways emerged. Hospital-first vertical integration suits hospital-dense, high-growth states such as Tamil Nadu and Delhi, where capital and regulatory depth permit managed-care scaling. Primary-care-first reverse integration is preferable in resource-constrained contexts such as Bihar and Chhattisgarh, leveraging community trust and lower capital intensity. Conclusions: Achieving universal health coverage in India requires regulatory conditions, such as ownership flexibility, solvency oversight, risk adjustment, and transparent outcomes reporting, to enable accountable payer–provider organisations to form. The framework extends contingency theory to mixed health systems and offers a transferable blueprint for emerging markets seeking sustainable, integrated managed care. Full article

Background/Objectives: This systematic review explores the evolving landscape of ethical dilemmas and legal responsibilities in hospital-based patient care, with particular attention to how they intersect with institutional safety. Drawing from 40 studies published within the last decade and supplemented by seminal theoretical works, the review examines clinical, technological, legal, and policy-driven challenges that compromise ethical clarity and organisational accountability. Methods: Methods included a structured literature search across major academic databases, guided by inclusion and exclusion criteria aligned with PRISMA guidelines and a quality appraisal ensuring inclusion of only medium- and high-quality studies. Results: Findings reveal that ethical complexity has shifted from individual decision-making to system-level vulnerabilities, particularly in contexts involving artificial intelligence (AI), data governance, consent procedures, and end-of-life care. Moreover, hospitals often lack sufficient protocols for disclosure, cross-border telemedicine accountability, and ethically responsive infrastructure. The results support a growing call for ethics-by-design approaches, where ethical reflexivity is embedded into institutional processes and digital systems. Conclusions: Overall, ethical resilience in hospital care depends not only on clinical training but on proactive organisational structures that support transparency, equity, and patient dignity. Full article