Search Results (2,157)

The increasing vulnerability of global food systems—exacerbated by the pandemic, climate change, and disruptions to international supply chains—has highlighted the importance of local food production for sustainability, food security, and rural resilience. At the same time, the LOHAS (Lifestyles of Health and Sustainability) value system is gaining prominence, shaping consumer demand for locally produced, environmentally responsible, and health-oriented products. While the existing literature predominantly addresses LOHAS consumers and local food systems as separate research domains, limited empirical attention has been paid to the value-based alignment between LOHAS principles and local food producers, particularly from a territorial and place-based perspective. This study seeks to address this gap by examining how LOHAS value dimensions are reflected in the self-identification and operational practices of local food producers, and by analyzing how such value alignment may be interpreted as contributing to the sustainability and resilience of territorially embedded rural production systems. From a systems perspective, LOHAS-related value alignment may be interpreted as a potential coordination mechanism that may contribute to strengthening feedback loops between producers and consumers and may enhance the adaptive capacity of short food supply chains as socio-ecological systems. The empirical analysis draws on an online survey conducted in the second quarter of 2024 among 73 local producers operating in Zala and Vas counties in Western Hungary. Factor analysis and cluster analysis were applied to identify underlying value structures and producer typologies. The results reveal two distinct producer clusters, one of which exhibits a strong alignment with LOHAS values. Producers within this cluster place particular emphasis on sustainability, environmental responsibility, health consciousness, and authenticity, alongside a pronounced commitment to local embeddedness and community-oriented practices. Overall, the findings demonstrate that LOHAS-related values are not confined to the consumer side but are increasingly embedded in territorially grounded local production models. This value alignment may contribute to strengthening short food supply chains rooted in specific geographical contexts, thereby contributing to the long-term socio-economic and environmental sustainability of rural regions. Full article

The cosmetic industry represents a major sector of the global economy and is expected to significantly grow in the coming years. To enhance consumer acceptance and address increasing sustainability concerns, cosmetic companies are actively seeking innovative solutions to mitigate their environmental, economic, and social impacts. In accordance with this, several scientific studies focus on the development, scale-up, and life cycle assessment of sustainable cosmetic products, especially those derived from side streams in accordance with circular economy principles. Various reviews have addressed this topic; however, they typically cover one or two of these dimensions, providing only a partial perspective. In particular, existing studies mainly analyze the types of side streams used and the resulting products, often lacking a comprehensive framework that can effectively support the translation of these approaches into industrial-scale production. The aim of the present review is to address this gap by providing a comprehensive analysis of the maturity level of development, scale-up processes, and life cycle assessment of cosmetic products based on agro-industrial side streams. This analysis is intended to support companies in the transition towards more sustainable practices by reducing carbon footprint and limiting the intensive extraction of virgin raw materials. The different approaches and methodologies proposed for the development and scale-up of sustainable cosmetic products from agro-industrial side streams are also analyzed, considering whether life cycle assessment has been performed. Furthermore, the most suitable business models will be selected as innovative and sustainable value chains capable of generating economic benefits, fostering local development, and enhancing resource efficiency and supply security. Full article

Background: Supply chain management (SCM) research has expanded across the Middle East and North Africa (MENA), yet the field remains fragmented. Limited synthesis exists on how regional conditions shape research themes, theories, and methods. Methods: This study applies the PRISMA 2020 protocol to review SCM articles indexed in Scopus and Web of Science from January 2000 to March 2025. After screening and eligibility assessment, 512 peer-reviewed studies were retained. Bibliometric mapping and thematic coding were used to identify publication trends, research streams, theoretical lenses, and methodological patterns. Results: SCM research increased sharply after 2015, reflecting national diversification agendas, logistics reform, digitalization, and exposure to global supply chain disruptions. Three dominant streams were identified: resilience, sustainability, and digital transformation. Research output is concentrated in Saudi Arabia and the United Arab Emirates, while cross-country comparative studies remain scarce. Empirical studies rely mainly on cross-sectional surveys and SEM-based analysis, with limited longitudinal, qualitative, mixed-method, and comparative work across the region. Conclusions: The study develops an integrative SCM capability framework linking regional structural conditions, capability development, and supply chain outcomes. The findings support managers and policymakers seeking resilient, sustainable, and digitally enabled supply chains, and define clear future research priorities for the MENA region. Full article

The global transition toward renewable energy and decarbonization is intrinsically linked to the management of critical materials. Rare Earth Elements (REEs) are no exception, as they play a strategic role at the center of climate goals. Therefore, this review provides a comprehensive assessment of the REE landscape, explicitly addressing the proposed Demand-Sustainability-Risk Nexus (DSR-Nexus), which integrates technological demand, environmental sustainability, and geopolitical supply risks. A systematic review based on PRISMA methodology was conducted to analyze scientific contributions published between 2015 and 2026, revealing a significant research imbalance. By 2025, while 87% of works focus on resource availability, production, and recycling, only 1.4% address the global supply chain and its geopolitical implications. Key findings highlight that China’s dominance in mining, processing, and refining capacities, accounting for 69.5%, 92%, and 94%, respectively, creates structural vulnerabilities for future environmental goals. In contrast, emerging producers such as Malaysia and the United States are expected to contribute 9% and 8% of refining capacity, respectively. Furthermore, this review discusses environmental trade-offs, including high energy intensity, water consumption, and radioactive byproducts. It also examines mitigation strategies, such as recycling, urban mining, and material substitution. Ultimately, achieving a resilient energy transition requires expanding supply, strengthening circular strategies, and international cooperation. Full article

Illegal, unreported, and unregulated (IUU) fishing activities have become one of the most critical challenges facing the global fish industry, particularly in developing countries, with the economic impact of fish fraud reaching billions of dollars annually. A major contributor to this problem is the limitation of conventional fish supply chain systems, which lack secure data sharing among stakeholders, fail to provide trusted product information to consumers, and offer insufficient transparency for regulatory authorities. These shortcomings facilitate fraud and weaken trust and oversight across the supply chain. Blockchain technology has demonstrated strong capability to address key cybersecurity challenges by enhancing traceability, transparency, and tamper-resistant data integrity across distributed supply chain stakeholders. In this paper, we present an enterprise-oriented prototype of a secure, permissioned blockchain-based fish supply chain system designed to enable trusted data sharing and end-to-end traceability across multi-stakeholder environments. Building upon our prior work in Ethereum-based seafood quality monitoring, this study contributes: (1) a modular, consortium-grade architecture implemented using Hyperledger Fabric and containerized via Docker, supporting scalable organizational participation; (2) formal UML-based system modeling of supply chain actors, assets, and lifecycle transitions; and (3) custom chaincode logic that enforces ownership transfer workflows and regulatory compliance policies. In addition, the architecture is designed as agent-ready, exposing standardized APIs that enable future integration of autonomous AI-driven client applications for proactive supply chain orchestration. By leveraging a private, permissioned network model, the functional prototype demonstrates the feasibility of improving data veracity and providing a practical foundation for mitigating fraud and enhancing regulatory oversight in the global fish industry. Full article

Backgrounds: Ports are critical nodes in global logistics and supply chains, yet their operations generate substantial environmental and social externalities. Existing evaluation frameworks have limited capability to address uncertainty, ambiguity, and expert hesitation. Moreover, prior studies frequently examine isolated performance dimensions, overlooking the interconnected roles of port authorities as landlords, regulators, operators, and community stakeholders. Methods: This study proposes an integrated evaluation framework using the Intuitionistic Fuzzy Analytical Hierarchy Process (IF-AHP) to assess environmentally sustainable port performance under uncertain decision environments. By incorporating membership, non-membership, and hesitation degrees, the approach improves the robustness of expert judgments and applies a dual consistency check to reduce bias. Empirical data are obtained from Malaysian port management professionals, enabling the development of a comprehensive framework that includes four main functions and twenty sub-functions. Results: Results reveal that the landlord function holds the highest priority, while operational sustainability dimensions receive the greatest emphasis, with a global weight of approximately 0.105. In contrast, community engagement and social initiatives are assigned relatively lower importance. Conclusions: The IF-AHP framework offers an uncertainty-aware tool that prioritizes sustainability functions, especially environmental mitigation and energy efficiency, enabling informed resource allocation, strategic planning, and policy formulation for balanced, sustainable port overall performance. Full article

Meat serves as a prime medium for the growth of foodborne pathogens due to its rich protein content and high water activity, contributing significantly to the global burden of foodborne illnesses. This review synthesizes current advances in meat-borne bacterial pathogen detection with particular emphasis on emerging artificial intelligence (AI)-enabled applications. Major pathogens of concern, including Salmonella, Listeria monocytogenes, Escherichia coli, Campylobacter, Clostridium, and Staphylococcus aureus, are examined in relation to their relevance across the meat supply chain. Recent progress in biosensors (clustered regularly interspaced short palindromic repeats), CRISPR-based assays, isothermal amplification, and metagenomics is evaluated alongside the growing role of AI in automating signal interpretation, enhancing image-based diagnostics, and supporting early contamination prediction. AI-based systems have proved 96.4–104% recovery and 100% bacterial capture ability. Embedding AI methods in a wet lab demands technical and logical modeling, as well as learning and calibration decorum. Nonetheless, AI readiness and full-scale application for meat-borne pathogens surveillance are on the way. Furthermore, additional focus is aligned on meat-borne bacterial pathogen genomic databases, i.e., (NCBI Pathogen Detection, EnteroBase, VFDB, ComBase, and GenBank), which serve as critical training resources for AI models for outbreak tracking, virulence profiling, and antimicrobial resistance (AMR) prediction. By integrating molecular methods, genomic surveillance, and AI-driven analytics, this review presents a framework for strengthening meat safety systems. This will improve early detection capabilities and support data-driven public health interventions in the future. Full article

Surface protection and functional modification of aircraft-certified aluminum alloys are essential for corrosion resistance, durability, and long-term airworthiness. At the same time, increasingly restrictive environmental regulations motivate the development of alternatives to legacy wet-chemical surface treatments. This study presents an integrated assessment of ultrafast femtosecond laser surface texturing as a surface functionalization approach for Aluminum 6061 alloys within an aerospace manufacturing and sustainability context. Ultrashort-pulse laser processing enables controlled micro- and nano-scale surface topographical modification with limited thermal impact, allowing adjustment of wettability and surface functionality while preserving bulk material integrity. As a dry and contactless process, femtosecond laser treatment eliminates the use of hazardous chemicals, reduces consumable inputs, and generates minimal secondary waste. A streamlined cradle-to-gate life cycle assessment conducted in accordance with ISO 14040/14044 indicates a lower global-warming potential per functional unit compared with conventional surface treatments, including anodization, plasma-assisted coatings, and organic coating systems. Complementary qualitative analyses addressing environmental health and safety, supply-chain risk, and ESG alignment indicate potential advantages related to occupational safety, regulatory compliance, waste management, and end-of-life recyclability. The investigation is performed on planar Aluminum 6061 reference surfaces with a treated area of 25 mm², providing a controlled laboratory-scale basis for analyzing process behavior, functional surface modification, and associated environmental metrics. Within this defined scope, the results support further evaluation of femtosecond laser surface texturing as a surface engineering option for future aerospace manufacturing. Full article

The global seafood industry faces persistent challenges related to product quality, safety, and authenticity, driven by complex supply chains, increasing demand, and the perishable nature of aquatic products. Traditional analytical methods often fall short in providing rapid, comprehensive, and non-destructive insights into the intricate biochemical changes occurring in seafood. ¹H Nuclear Magnetic Resonance (¹H NMR) spectroscopy has emerged as a powerful and versatile tool for metabolomics, offering a holistic view of the low-molecular-mass compounds (metabolites) present in biological samples. The present study applied ¹H NMR for chemical fingerprint identification in mullets (Mugil liza) from Brazil. Dorsal muscle samples were taken from the fish during summer, autumn, and winter. The procedure involved freeze-drying the muscle tissue, thereafter extracting polar metabolites using designated solvents (methanol, water, and chloroform), and analyzing them using a 600 MHz spectrometer. As a result, 23 metabolites related to degradation biomarkers, essential metabolites, energy expenditure, and muscle structure were identified. The statistical analysis demonstrated a distinct separation between the geographical origins (RJ vs. SC), mostly influenced by variations in the concentrations of lactate, histidine, threonine, phenylalanine, and ornithine. Factors like fish size and seasonal variations did not markedly affect the overall metabolic profile, underscoring the reliability of these chemicals as stable origin indicators. The Principal Component Analysis identified two distinct groups of metabolites, establishing a profile for each geographical origin. The developed protocol can be applied to the processes of geographical identification. Thus, the ¹H NMR tool was efficient in determining metabolites that can be considered biomarkers in analyses for seafood traceability. Full article

Globalization refers to the increasing density of economic, social, and technological interconnections on a global scale. In the healthcare industry, it simultaneously accelerates innovation and increases systemic vulnerabilities. This study aims to review and conceptually synthesise the main channels of impact: (1) pharmaceuticals, clinical development, and regulation; (2) supply chains and resilience; (3) service mobility (health tourism); (4) human resources and competencies; (5) digitalization, artificial intelligence (AI), and data governance; (6) ethics, law, and public policy; and (7) sustainability and climate change. The COVID-19 pandemic highlighted the risks associated with global interdependencies, particularly in supply chains, while also demonstrating the innovation-accelerating effects of knowledge sharing and international cooperation. Particular attention is given to artificial intelligence and digital health, which open up new potential for efficiency and quality improvement from research and development through diagnostics to healthcare organization, while simultaneously intensifying concerns related to data protection, cyber security, and liability. Telemedicine, platform-based systems, and real-world data may contribute to addressing the care needs of ageing societies, but only when supported by appropriate competencies and sound data governance. As global data flows intensify, the importance of data protection, bias mitigation, transparency, and accountability correspondingly increases. Through the cultural channels of globalization, health-conscious lifestyles and complementary approaches are also spreading, which we address in a brief, separate subsection. The guidelines of international organizations foster standardization; however, due to differences in local capacities and institutional environments, the effects are not homogeneous. In conclusion, the study emphasises the dual nature of globalization; it expands access and accelerates innovation, while at the same time creating new vulnerabilities—in supply chains, labour mobility, and data security—and, together with climate-related risks, generating complex adaptive pressures for the healthcare industry. Full article

Dry ports are becoming increasingly important elements of port–hinterland transport systems, particularly as maritime gateways face rising congestion, infrastructure pressure, and coordination challenges within global supply chains. As international trade expands and logistics networks grow more complex, inland terminals are progressively evolving into integrated intermodal platforms that support more efficient freight distribution between seaports and their hinterlands. This study presents a PRISMA-based systematic review of research on dry port–seaport systems covering the period 1980–2025. Following a structured screening and selection procedure, peer-reviewed publications were identified and analyzed to examine conceptual developments, thematic orientations, geographical scope, and decision-making perspectives within the field. Particular attention is given to the growing relevance of digital transformation, including artificial intelligence and machine learning, in shaping future dry port operations and network design. By synthesizing existing contributions and identifying research gaps, this review provides a consolidated understanding of the evolution of dry port research and outlines key directions for advancing sustainable, resilient, and data-driven port–hinterland systems. Full article

The effective closure of the Strait of Hormuz on 28 February 2026 disrupted approximately 20 million barrels (bbl) per day of crude oil transit, constituting the largest supply shock in global oil market history. This study quantifies the resulting economic losses under three blockade-duration scenarios and evaluates the Northern Sea Route (NSR) as a partial mitigation mechanism through a novel framework integrating sustainable supply chain resilience (SSCR), the Triple Bottom Line (TBL), and the United Nations Sustainable Development Goals (SDGs). A 3 × 3 scenario matrix crossing three blockade durations with three NSR utilization levels estimates global and country-level impacts using data from the International Energy Agency (IEA), the International Monetary Fund (IMF), and the Centre for High North Logistics (CHNL). Even under maximum feasible NSR utilization, net environmentally adjustment mitigation offsets only 1.1–3.6% of total global losses, demonstrating that the Northern Sea Route functions as marginal insurance rather than a viable substitute for Hormuz-dependent supply chains. Global Gross Domestic Product (GDP) losses range from USD 330 billion to USD 2.2 trillion, with South Korea (68–70% Middle East crude dependency) and Japan (approximately 95%) disproportionately affected. After TBL environmentally adjustment monetizing CO₂, black-carbon, and icebreaker costs, the NSR mitigates 1.1–3.6% of total losses, functioning as insurance rather than substitution. The SDG assessment reveals a fundamental trade-off: the NSR offsets energy-security losses (SDGs 7, 9) but worsens climate and marine outcomes (SDGs 13, 14). Theoretically, this study proposes “alternative maritime route availability” as a conceptual extension of supply chain resilience (SCRes) capabilities and outlines a sustainability-adjusted resilience score (SARS) framework that, pending further validation, could serve as a replicable assessment tool. These findings underscore that accelerating the energy transition remains the most effective long-term response to chokepoint vulnerability. Full article

Against the backdrop of global energy landscape restructuring, the advancement of the “dual-carbon” goals, and escalating external uncertainties, coal, as the “ballast stone” of China’s new energy system, faces new challenges in terms of supply chain stability and security. Therefore, scientifically assessing China’s coal supply chain resilience (CSCR) is of significant theoretical and practical importance for systematically identifying its supply vulnerabilities and ensuring energy supply security under extreme conditions. In the paper, we construct a composite evaluation indicator system using national statistical data from 2010 to 2024. We operationalize resilience across the following four capacities: resistance, absorption, recovery, and adaptive capacity. Annual resilience levels are measured using an integrated framework. This framework combines an improved entropy weight method, TOPSIS, and gray relational analysis (GRA). We then use the indicator contribution degree and obstacle degree models to identify the most influential factors. The results indicate that China’s CSCR followed a fluctuating upward, W-shaped trajectory during 2010–2024, with a marked acceleration after 2020. Resistance and absorption capacities display pronounced volatility. Recovery and adaptation capacities improve steadily. The dominant obstacle factors include the share of intelligent coal production capacity, labor productivity per employee, the scale of workforce security, and the working-capital turnover ratio. These findings provide empirical evidence and policy-relevant insights for strengthening China’s CSCR and reinforcing national energy security. Full article

Ensuring the quality, reliability, and efficiency of cold chain logistics for thermolabile pharmaceutical products, particularly vaccines, remains a critical challenge in global health supply chains. These biologics require stringent temperature control throughout storage, transport, and distribution to preserve their efficacy. Persistent issues such as maintaining product integrity, accurately forecasting vaccine demand, and fostering trust among stakeholders often result in inefficiencies, waste, and public mistrust. This study proposes an intelligent digital management framework specifically designed for vaccine cold chains, integrating blockchain, the Internet of Things (IoT), and machine learning (ML) to address these challenges in a holistic and sustainable manner. The main innovation of the study lies in combining secure traceability, real-time cold chain monitoring, and predictive decision support within a unified vaccine cold chain management framework rather than treating these functions as isolated technological solutions. Using WHO immunization coverage data and vaccine-related review data, the framework supports vaccine demand forecasting through the Informer model and stakeholder trust assessment through BERT-based sentiment analysis. In the sentiment analysis task, the BERT model achieved ~80% accuracy on dominant sentiment classes, with a weighted F1-score of 0.6974, demonstrating strong performance on imbalanced datasets. By minimizing vaccine spoilage and enabling more accurate demand planning, the system reduces excess production and distribution, thus lowering resource consumption, carbon emissions, and financial waste. Moreover, trust-informed analytics support better alignment of supply with actual community needs, fostering equity and resilience in vaccine distribution. While this framework has been validated through simulations and experimental evaluation, further real-world testing is needed to assess long-term stability and stakeholder adoption. Nonetheless, it provides a scalable and adaptive foundation for advancing sustainability and transparency in pharmaceutical cold chains. Full article

Disruptions caused by disasters, pandemics, and systemic crises have increased the complexity and vulnerability of global supply chains, highlighting the need for advanced analytical approaches to risk and resilience management. In this context, artificial intelligence (AI) has emerged as a promising analytical capability for improving risk assessment and decision-making in disrupted supply chains. The study follows PRISMA 2020 reporting guidelines adapted for bibliometric research and presents a bibliometric and knowledge-mapping analysis of artificial intelligence applications in disaster supply chain risk and resilience management. Using the Web of Science Core Collection, a dataset of 288 peer-reviewed publications was analyzed through keyword co-occurrence, bibliographic coupling, citation analysis, and collaboration network mapping. The findings indicate a rapidly expanding research field in which AI supports predictive risk assessment, real-time monitoring, and resilience-oriented decision-making in disaster-prone supply networks. The analysis identifies dominant thematic clusters, emerging research directions, and opportunities for integrating AI-enabled analytics into supply chain risk management frameworks. The mapped literature also suggests secondary interpretive implications for financial risk exposure and supply chain finance, rather than indicating a separately operationalized finance-specific bibliometric subfield. To enhance interpretive depth, an AI-assisted analytical layer was applied to refine thematic clusters and detect emerging trends. However, this layer operates as a complementary interpretive tool and is subject to methodological limitations, including sensitivity to keyword semantics, dependence on bibliometric outputs, and potential interpretive bias in AI-assisted thematic labeling. Consequently, the AI-assisted analysis is used to support, rather than replace, bibliometric findings. Overall, this study contributes to the emerging literature on artificial intelligence in disaster supply chain risk management and highlights future research opportunities, including improved methodological integration and enhanced analytical transparency in AI-assisted bibliometric research. Full article