Search Results (1,330)

Across four decades of AI deployment, the same six human challenges (trust calibration, reliance behavior, cognitive engagement, skill retention, accountability, and transparency) recur, yet fragmentation across research communities obscures this continuity and limits knowledge transfer. Functionally similar phenomena are repeatedly relabeled (a jangle fallacy): what aviation researchers call “automation complacency,” decision scientists call “algorithm appreciation,” and LLM researchers describe as “over-reliance.” This systematic review synthesizes 152 papers spanning aviation, healthcare, manufacturing/supply chain, and cross-domain contexts across three AI technology generations: decision support systems, autonomous systems, and large language model (LLM) agents. We introduce the Collaboration Convergence Framework (CCF), a 6 × 3 matrix with solution-maturity indicators that maps each challenge across generations. The framework shows that Gen 3 designers can transfer decades of evidence from automation and decision support research (particularly reliance calibration, cognitive forcing, and skill maintenance) rather than rediscovering them. Cross-generational synthesis also isolates three Gen 3 phenomena without direct precedent in earlier generations: epistemia (attributing genuine knowledge to LLMs based on surface fluency), attribution ambiguity in co-creation, and motivational withdrawal. We distill twelve transferable design principles and propose ten research directions, prioritizing skill-retention interventions and accountability frameworks. These findings carry direct sustainability implications aligned with Industry 5.0: protecting workforce capability under increasing automation (SDG 8), reducing duplicated research effort through cross-generational knowledge reuse (SDG 9), and supporting responsible deployment by treating collaboration risks as predictable rather than novel (SDG 12). The CCF provides conceptual infrastructure for cumulative learning across AI generations and industries. Full article

Decarbonizing the built environment depends not only on improving operational efficiency but also on how supply is formed along the construction chain. Carbon pricing may reshape that process through upstream material costs, financing conditions, and project timing, yet evidence on the timing and stability remains limited. This study examines how carbon-price shocks are transmitted to construction activity in China and whether this transmission changed after the launch of the national emissions trading system (ETS) in July 2021. Using monthly data from January 2014 to October 2025, the analysis first applies additive Bayesian network (ABN) structure learning to identify links among carbon-market conditions, material costs, finance, and construction activity and then estimates a time-varying structural vector autoregression (TVP-SVAR) to trace dynamic responses across regimes. The results show that carbon-price shocks mainly depress housing starts and area under construction at medium horizons, especially around 6–12 months, with stronger contraction around the 2021 transition and easing later. Allowance trading volume responds positively on impact, but this sensitivity weakens in the post-2021 period. Forecast error variance decompositions further show that carbon-price shocks become an important source of medium- and long-horizon fluctuations. At the 12-month horizon, they account for 18.7% and 18.4% of the forecast-error variance of housing starts in the pre- and post-2021 regimes, and 13.7% and 10.8% of that of trading volume. Overall, the findings point to a project-cycle channel through which carbon pricing reshapes built-environment supply formation, with implications for procurement, transition finance, and the evaluation of carbon-market effectiveness in construction. Full article

Visual explainable artificial intelligence (XAI) is an important mechanism for connecting analytically complex decision models with practitioners who must interpret and act upon their outputs in industrial supply chains. In facility localization problems, wafer foundries and other capital-intensive manufacturers must evaluate geographically dispersed candidate sites against multiple uncertain criteria. The ability to communicate fuzzy group decision-making (FGDM) outcomes in a transparent, interpretable form has direct operational relevance. The literature has introduced hanging gradient bar charts, gradient bidirectional scatterplots, and traceable aggregation charts as visual XAI instruments for semiconductor supply chain localization that show substantial reductions in interpretation error versus conventional plots. However, the quantitative assessment of explanation quality itself remains underdeveloped. To address such a gap, this research proposes a quantitative explainability quality index (XQI) that formalizes visual explanation quality in FGDM as a composite measurable construct. XQI integrates two complementary layers: (1) An objective explainability layer (OEI), consisting of normalized fuzzy interpretation deviation, response time, ranking fidelity, and interpretation accuracy, and (2) a subjective explainability layer (SEI), consisting of perceived understanding, perceived transparency, decision confidence, and cognitive load. Trust, acceptance, and decision quality are downstream outcome constructs rather than components of the index. A weighted linear combination of OEI and SEI produces a single index for systematic, reproducible comparison across competing visualization designs. A structural equation model is specified as a planned validation mechanism for examining how explanation quality may relate to trust, acceptance, and downstream decision quality. The proposed validation framework includes a semiconductor facility localization scenario, three visualization conditions, and a planned participant pool of 150–240 supply chain managers, engineers, and graduate students. The XQI framework transforms visual XAI from a descriptive communication aid into a testable decision-support construct, thereby addressing a key evaluation gap in the FGDM visualization literature. Full article

Rising global demand for safe, high-quality foods has accelerated the development of rapid, sensitive, and cost-effective analytical technologies for detecting harmful substances and quality markers. Electrochemical sensors have emerged as promising tools for food safety monitoring due to their high sensitivity, fast response, portability, and affordability compared with conventional laboratory methods. This review highlights recent advances in nanostructured electrochemical sensors for detecting key food analytes, including antioxidants, mycotoxins, allergens, and flavor compounds in diverse food matrices. It examines advanced nanomaterials such as metal oxides, MXenes, doped carbon nitrides, and noble metal-decorated graphene, which enhance sensor performance through improved surface area, conductivity, and electrocatalytic activity. Integrated with screen-printed or glassy carbon electrodes, these materials achieve ultra-low detection limits, wide linear ranges, and strong selectivity in complex food systems. The review also explores next-generation applications such as NFC-enabled smart packaging for continuous, non-invasive monitoring across the supply chain. Emerging trends in miniaturization, multiplex sensing, and artificial intelligence are discussed, along with key challenges in translating laboratory innovations into practical commercial solutions for global food safety. Full article

Counterfeit and unsafe medicines pose significant risks to patient safety and undermine trust in healthcare systems. This paper presents ACTMeds, a blockchain-supported pharmaceutical traceability and recall platform that considers pharmaceutical supply chain requirements and public health operational needs relevant to the Australian Capital Territory (ACT). The system integrates Ethereum smart contracts, developed using Ganache, with a React-based web application providing regulator, operator, pharmacy, and auditor interfaces, alongside a public verification portal leveraging QR and GS1 barcodes. In addition, role-based access control is enforced across the medicine lifecycle, including manufacture, custody transfer, dispensing, and recall, with immutable on-chain events generated to support auditability and accountability. To balance transparency with confidentiality, the platform prototypes a zero-knowledge (ZK) recall mechanism in which regulators can cryptographically prove that recall conditions meet predefined policy requirements without disclosing sensitive incident details. Threat modeling was conducted using the STRIDE framework, and security evaluation combined static application security testing (Solhint and ESLint) and dynamic testing. The paper further discusses deployment options, cost considerations, ZK recall performance analysis, ethical implications, and future enhancements. Security testing validated the platform’s resilience, with no high-severity vulnerabilities identified and medium-severity issues related to HTTP security headers addressed. The results indicate that a regulator-led, privacy-preserving, tamper-evident ledger can improve medicine authenticity verification and recall responsiveness while maintaining compliance and data protection obligations. Full article

Abrupt maritime-energy disruption can generate system-wide production losses before firms and policymakers can adjust. Existing assessments usually emphasize direct exposure or long-run equilibrium responses, which makes them less suitable for short-run risk assessment in energy-dependent production systems. We develop a threshold-cascade framework that combines dual-track dependence topology, edge-level inventories, smooth operability bands, and a separate price-validation step to identify the blockade intensity at which a localized chokepoint shock becomes systemic production loss. The framework is evaluated against the March 2021 Suez blockage and the 2022 Russia–Ukraine producer-price episode, and then applied to a 2026 Strait of Hormuz stress scenario using the Organisation for Economic Co-operation and Development (OECD) Inter-Country Input-Output (ICIO) tables, 2025 edition, with the 2022 benchmark year. Under the baseline 150-day horizon, terminal loss first reaches 50% at about 32% blockade intensity, with a broader calibrated threshold band of 32–46%. Losses spread beyond the point of origin and become concentrated in East and Southeast Asian manufacturing supply chains and in downstream consumer markets after inventories at connected hubs are depleted. Policy experiments show that single-channel interventions shift the threshold only modestly, whereas an integrated package that relaxes logistics, inventories, and upstream scarcity moves the threshold to about 46% in this calibration. The analysis targets the weeks-to-months interval before substitution, contract renegotiation, and broader market adjustments dominate. Within that interval, the model identifies when buffers fail, how production losses spread, and which intervention packages delay systemic disruption. Full article

Background: Drug shortages represent a growing challenge to healthcare systems worldwide, affecting treatment continuity and patient outcomes. This study assessed the burden and perceived impact of drug shortages from both healthcare professionals’ and patients’ perspectives in a Saudi tertiary hospital. Methods: A cross-sectional survey was conducted in April 2025 at King Abdulaziz Medical City, Riyadh, Saudi Arabia. Convenience sampling was used to recruit healthcare professionals with at least two years of experience and adult outpatients. Structured questionnaires assessed shortage frequency, affected drug classes, perceived impacts, and management practices. The findings were descriptively analyzed and compared with the Saudi Food and Drug Authority (SFDA) national shortage data for the corresponding 12-month period. Results: A total of 230 healthcare professionals and 243 patients participated. Among healthcare professionals, 89.1% reported experiencing at least one drug shortage, with 38.3% encountering shortages more than ten times annually. Anti-infectives (36.5%) and analgesics (35.7%) were the most frequently reported classes. The most common response was prescribing alternative medications (77.4%), with 55.3% perceived as adequately effective and 30.8% as less effective. Delayed care was the most frequently reported consequence (44.0%). Among patients, 30.9% reported experiencing shortages, 46.7% reported some degree of health impact, and 28.1% incurred additional costs. Awareness and utilization of the SFDA reporting system were low in both groups. Comparison with SFDA data revealed discrepancies between hospital-reported and nationally reported shortages. Conclusions: Drug shortages were frequently reported and associated with perceived clinical and economic consequences. Gaps between hospital experiences and national reporting highlight limitations in current surveillance systems. Strengthening reporting mechanisms, communication, and supply chain coordination may improve the management of drug shortages. Full article

Purpose: Access to assistive technology (AT) is a fundamental human right and a critical component of Universal Health Coverage (UHC). In the Middle East and North Africa (MENA) region, the scarcity of trained professionals remains a significant barrier to AT service provision. This study evaluates the effectiveness and perceived usefulness of the Assistive Technology Training Program (ATTP), a specialized continuing education initiative designed to build workforce capacity among rehabilitation and healthcare professionals. Methods: A convergent mixed methods design was used to analyze quantitative pre/post-test scores and qualitative focus group open-ended responses. Quantitative data were gathered from 386 participants across 11 MENA countries using a pre- and post-test assessment of AT knowledge. Qualitative utility and participant satisfaction were assessed through a 5-point Likert scale survey evaluating content relevance, trainer expertise, and facilities. Association tests (ANOVA and t-tests) were conducted to identify factors influencing knowledge gain. Results: Participants demonstrated a statistically significant improvement in AT knowledge, with the overall mean score increasing from 3.67 ± 1.13 to 7.50 ± 1.25 (p < 0.001). High levels of satisfaction were reported, with 92% of participants rating the training as “Very Good” or “Excellent” regarding its relevance to clinical needs. Association tests revealed that professional background (p < 0.001), employment status (p = 0.0017), level of education (p = 0.011), and prior training experience (p = 0.026) were significant factors in the magnitude of improvement, although all subgroups achieved significant learning gains. Qualitative thematic analysis per the focus group discussions using the WHO-GATE 5 P framework identified three major themes: (1) Structural Challenges: Issues with Products and Provision point toward a need for better infrastructure and localized supply chains. (2) Human Capital: Personnel barriers emphasize that training shouldn’t just be for professionals, but should extend to caregivers as well. (3) Systemic and Social Change: Policy and People focus on the “soft” side of AT moving toward user-involved guidelines and fighting social stigma to ensure rights are upheld. Conclusions: The ATTP is an impactful educational intervention that significantly enhances the foundational competencies of healthcare professionals in the MENA region. By addressing knowledge gaps and fostering practical skills, the program serves as a preliminary model that demonstrates potential for building regional capacity and supporting the United Nations’ Sustainable Development Goal (SDG) #3 related to health and wellbeing and SDG #4 related to quality education and lifelong learning opportunities for all. Further research is required to evaluate its long-term scalability and clinical impact. Full article

The purpose of the article is to present the influences and their weights on the price formation of agricultural and food products in Slovenia. The influences are defined by the ratios of input and output prices and quantities of raw materials, semi-finished products, and products within the food systems of individual stakeholders in the theoretical design of price difference construction, the definition of individual stakeholders’ costs, and the assessment of the dynamics of price and quantity fluctuations from the annual average. The analysis is based on the specified econometric model bases on the Ridge formulation, which represent an analytical model of the price formation in the agri-food chains in Slovenia. The results determine and explain the weight of the impacts based on composite independent variables (based on the calculation of the relationships between individual variables with respect to the mutual responsiveness of changes–elasticity of behaviour) which were defined using available data collected in accordance with the Law on Agriculture in the Republic of Slovenia. Several new independent variables were developed to explain the effects of the independent variable representing the difference in the price of agricultural and food product between the beginning and the end in the analyzed food supply chain. The discussion connects practical actions that address three important future development components of agriculture: strengthening accessibility, competitiveness, and the stability of the position of Slovenian agriculture within the EU. Full article

Low-carbon service outsourcing creates a governance problem in which manufacturers must address hidden emission-reduction capability before contracting and hidden effort after contracting. Consumer low-carbon preference does not automatically translate into market returns, because consumers rely on information disclosure, certification, carbon labeling, and traceability to perceive actual emission-reduction performance. This study develops a principal–agent model for a low-carbon service supply chain composed of a manufacturer and a low-carbon service provider. The baseline model examines screening and effort incentives under dual information asymmetry, the extended static model introduces heterogeneous consumer preferences and information perception, and the dynamic model incorporates consumer trust evolution. The results show that menu contracts enable manufacturers to distinguish service-provider types and induce emission-reduction effort, but truthful self-selection requires information rent. Consumer low-carbon preference strengthens incentive intensity only when disclosure converts actual emission-reduction performance into perceived low-carbon value. Disclosure investment improves the market return of emission-reduction effort, but its effectiveness is constrained by disclosure cost, provider risk aversion, and output uncertainty. Consumer low-carbon trust converges to a steady state supported by sustained emission-reduction effort and credible disclosure. The conclusions apply primarily to low-carbon service outsourcing settings in which provider capability and effort are difficult to observe and market response depends on consumers’ perception of low-carbon information. This study extends principal–agent analysis to low-carbon service supply chains and shows that effective low-carbon governance depends on the coordination of contract incentives, information disclosure, and trust accumulation. Full article

The utilization of coal-based solid waste materials (CSW) in road engineering is an important pathway for reducing stockpiling pressure, mitigating environmental risks, and promoting resource recycling. However, their large-scale diffusion is still constrained by residual engineering risk, misaligned cost and risk allocation between upstream and downstream actors, and imperfect regulatory and incentive mechanisms. To address these issues, this study develops a tripartite evolutionary game model involving the regulator, the waste producer, and the waste utilizer. The model incorporates pretreatment investment, residual engineering risk, government rewards and penalties, and green collaborative benefits to examine the evolutionary dynamics of the three parties and the stability of the system under different conditions. The results show that deep pretreatment by waste producers is a key prerequisite for the diffusion of CSW materials, as it reduces material instability and downstream engineering risk and increases the utilizer’s willingness to adopt such materials. The effects of rewards and penalties are differentiated across actors: effective penalties play a stronger role in constraining low-cost disposal by waste producers, whereas rewards are more effective in encouraging adoption by waste utilizers. The interaction analysis further shows that residual engineering risk significantly constrains the positive effect of green collaborative benefits, indicating that benefit enhancement cannot substitute for risk governance. In addition, the total amount of green collaborative benefits and their release and distribution structure jointly affect behavioral convergence and system stability. The system is more likely to evolve toward a stable state characterized by deep pretreatment, active adoption, and routine regulation when benefit sharing is consistent with the costs and risks borne by each party. Based on these findings, this study suggests that differentiated policy design is needed, including stronger source pretreatment and quality control, a coordinated reward–penalty mechanism for different actors, more targeted incentives and acceptance requirements for waste utilizers, and an improved governance framework featuring quality standards, full-process traceability, and risk warning mechanisms. These measures are essential for promoting the stable and large-scale utilization of CSW materials in road engineering. By translating model results into staged regulatory, quality-control, and supply-chain actions, the findings also support broader sustainable development goals, including responsible consumption and production, resilient infrastructure, climate action, and ecosystem protection. Full article

Avibacterium paragallinarum (A. paragallinarum) is the primary causative agent of infectious coryza in chickens. Infection often leads to growth retardation in broilers and a 10% reduction in egg production, reaching over 40% in laying hens. The problem is particularly severe under intensive farming conditions, significantly jeopardizing global poultry health and farming profitability. From a ‘One Health’ perspective, this not only disrupts the stability of the food supply chain, but also increases antibiotic usage due to disease prevention and control needs, thereby aggravating antimicrobial resistance (AMR) and posing a global public health challenge. This review systematically summarizes advances in the pathogenesis of A. paragallinarum and the protective immunity induced by subunit vaccines. It focuses on the infection mechanisms of A. paragallinarum, emphasizing its colonization strategies in the infraorbital sinus and nasal epithelium of chickens, and analyzes the roles of key virulence factors such as hemagglutinin and capsule in adhesion, colonization, and immune evasion. We integrate the tissue-specific pathogenesis of A. paragallinarum with the role of respiratory commensal microbiota in facilitating infection, providing an in-depth analysis of the bacterium’s key immune evasion strategies, thus offering novel insights into host–pathogen-microbiome interactions. Concurrently, to the best of our knowledge, this review provides the first comprehensive overview of current developments in subunit vaccines and their immunoprotective properties, with special attention to limitations in eliciting mucosal immune responses. By delving into the pathogen-host interaction mechanisms, this review aims to inform the optimization of subunit vaccine design and immunization strategies. Ultimately, it seeks to establish a theoretical basis and practical framework for precise control of A. paragallinarum. Full article

Background: Humanitarian campaigns are more popular with more initiatives organized than ever by public and private bodies. Simultaneously, more peculiar challenges, such as zero-waste and transparency, are required compared to traditional supply chains. This work investigates the current technological landscape for shaping the next generation of humanitarian aid management systems, focusing on algorithmic and operational aspects, matching them to a new architecture for a target-platform, called AidTech. Methods: The methodology follows a systematic literature coverage, identifying cross-disciplinary trends from operations research, computer science and sustainable logistics. We examine the convergence of optimization, artificial intelligence, and blockchain-enabled traceability toward efficient and transparent humanitarian logistics. The employed methods include adaptive scheduling, resource allocation algorithms and privacy–preserving collaboration for meeting special constraints imposed by the humanitarian scope. Results: The findings focus on the architectural perspective of humanitarian supply chains and highlight that modern humanitarian infrastructures will increasingly rely on hybrid optimization methods integrating graph theory, dynamic routing under stochastic demand, multi-criteria decision analysis and distributed ledger technologies. Conclusions: We conclude that these paradigms, when combined under a unified cyber–physical architecture, e.g., AidTech, can substantially improve responsiveness, equity and sustainability in crisis management, further shaping future humanitarian logistics. Full article

Indigenous communities in northern Canada experience severe household food insecurity rates ranging from 21.8% to 70%. However, the relationship between national-level economic and environmental indicators and Indigenous Community Well-being (ICWB) remains inadequately understood. This study examines national-level correlates of ICWB from 1991 to 2021, analyzing relationships between ICWB scores and agricultural production volumes (canola, corn, wheat, soybeans), their commodity prices, and greenhouse gas (GHG) emissions, with a particular focus on the role of traditional food systems. The study uses data from the Government of Canada, Statistics Canada, and Environment Canada, supplemented by secondary literature on Indigenous traditional food systems. Three documented mechanisms provide a framework for interpreting how national indicators may affect northern communities: commodity price transmission through integrated markets, federal policy responses calibrated to national economic data, and supply chain dependencies linking southern production to northern availability. Correlation analysis reveals significant positive associations between ICWB and production volumes of canola, corn, and soybeans, as well as the prices of wheat, corn, canola, and soybeans. Regression analysis that accounts for temporal trends reveals that soybean and canola prices are negatively associated with ICWB, indicating that increasing prices may reduce community well-being, potentially reflecting increased economic pressure or reduced affordability. GHG emissions correlate positively with ICWB, likely reflecting confounding by economic development rather than direct environmental benefits. These national-level correlates have potential implications for northern Indigenous food security and well-being through recognized transmission mechanisms. The paradoxical positive correlation between rising commodity prices and ICWB is consistent with an adaptive response: as market food costs increase, communities may strengthen traditional food harvesting and local production, though higher equipment and resource prices may constrain these efforts, making food sovereignty enhancement a complex challenge. Findings suggest that northern communities participate in national economic systems through price, policy, and supply chain pathways, but may yet retain adaptive capacity through traditional food systems if persistent multi-stage supports are provided. Policy implications include indexing northern food subsidies to commodity price volatility, prioritizing funding for Indigenous-led food sovereignty initiatives that integrate traditional knowledge with modern techniques, and investing in infrastructure to reduce supply chain vulnerabilities. Future research should examine community-specific responses to national economic patterns and identify local factors that strengthen nature-led traditional food systems in northern Indigenous contexts. Full article

Global supply chain disruptions, most acutely demonstrated during the COVID-19 pandemic, have exposed fundamental tensions between efficiency-oriented design and the adaptive capacity required for resilience. This paper addresses a critical gap in the existing literature: the absence of an integrative, operationalisable framework that treats sustainability and resilience as mutually reinforcing strategic objectives rather than competing trade-offs. Employing a systematic literature review guided by PRISMA protocols, complemented by comparative analysis of documented organisational responses across multiple sectors and commodity markets, the study identifies four primary pathways through which sustainability investments generate resilience: structural diversification, information and visibility, social capital and trust, and adaptive capabilities. The principal finding is that sustainability practices, particularly those enhancing supply network visibility, structural diversification, and workforce stability, create option value that becomes strategically decisive during periods of disruption. A decision intelligence framework is proposed that translates these insights into three managerial tools: a sustainability–resilience assessment matrix, a disruption scenario analysis tool, and a capability development roadmap. The framework challenges the prevailing trade-off assumption by demonstrating that efficiency, sustainability, and resilience can function as complementary dimensions of supply chain performance. Findings carry particular relevance for commodity-dependent supply chains, where price volatility, trade structure rigidity, and resource concentration constitute persistent sources of systemic disruption. Theoretical contributions include the integration of supply chain resilience theory, sustainable operations management, and decision science under deep uncertainty. Full article