Search Results (4,059)

As global supply chains face increasing pressure to reconcile economic efficiency, environmental responsibility, and ethical transparency, emerging digital technologies offer unprecedented opportunities for sustainable transformation. This article examines this dynamic in the context of the Moroccan industrial sector, with particular reference to blockchain and digital twin technologies. The study employs a rigorous mixed-methods design, combining an in-depth qualitative exploration with 30 industry professionals and a Partial Least Squares Structural Equation Modeling (PLS-SEM) model based on survey data from 125 Moroccan manufacturing firms. The findings highlight the synergistic contribution of blockchain and digital twins in enabling circular, low-carbon, and resilient supply chains. Blockchain adoption strengthens environmental impact traceability, data reliability, and responsible governance, while digital twin systems enhance eco-efficiency through real-time modeling and predictive flow simulation. Circular integration emerges as a critical enabler, significantly amplifying the positive effects of both technologies by aligning physical and informational flows within closed-loop processes. With its strong empirical grounding and contextual relevance to an emerging economy, this research provides actionable insights for policymakers, industrial managers, and supply chain practitioners committed to accelerating the sustainable transformation of production systems. It also offers a renewed understanding of how digitalization and circularity jointly support environmental performance within industrial ecosystems. Full article

The development of renewable energy has emerged as a cornerstone of sustainable economic transformation, offering a pathway to reduce carbon dependence and enhance long-term energy security. As a result, this study examines the influence of supply chain digitalization, economic growth, and environmental stringency policies on renewable energy consumption (REC) across 33 OECD countries from 2000 to 2021. Using the Method of Moments Quantile Regression (MMQR) approach, the research provides robust, distribution-sensitive insights into how these factors shape renewable energy dynamics. In addition to the main variables, financial development and economic globalization were included as control variables to capture broader macroeconomic effects. The empirical results reveal that supply chain digitalization exerts a negative and consistent influence on REC across all quantiles, suggesting that technological advancement within supply chains may still be heavily dependent on non-renewable energy inputs. Conversely, environmental stringency policies demonstrate a positive and significant impact on REC at all quantiles, indicating that stricter environmental regulations effectively drive the transition toward cleaner energy sources. However, the effect of economic growth varies across quantiles, reflecting a nonlinear relationship—fostering renewable energy use in some instances while increasing conventional energy demand in others. Among the control variables, economic globalization enhances REC, implying that greater international integration facilitates technology transfer and access to green innovations. In contrast, financial development negatively affects REC, suggesting that current financial systems may still prioritize fossil fuel investments. Overall, the study emphasizes the need to align digital transformation strategies, financial reforms, and policy frameworks to strengthen renewable energy development and ensure a sustainable, low-carbon future across OECD nations. Full article

Reflection on sustainable economic models, such as the civil economy, has led to the development of alternative food supply chains grounded in ethical values and practices. From this perspective, the Food Village model was proposed to meet stakeholders’ needs, overcome the limitations of Alternative Food Networks, and scale up. In this study, a Discrete Choice Experiment on hypothetical Food Village participation scenarios was combined with the Portrait Values Questionnaire to analyse preferences for the model’s attributes in relation to personal values. The results indicate that consumers appreciate the ethical and territorial characteristics of Food Village, such as local and organic products and cooperative governance, as long as convenience is guaranteed (product variety, flexible hours). Furthermore, they prefer moderate forms of participation, while excessively burdensome involvement reduces their willingness to participate. Individual values influence preferences: values of “self-transcendence” and conservation are associated with greater willingness, while those of “self-affirmation” correlate with lower adherence to Food Village. This evidence suggests implications for policy and scalability: initiatives like Food Village, if supported by public incentives and flexible participatory schemes, can contribute to more sustainable food systems at scale. Full article

AI technologies are increasingly applied to optimize operations in both port and urban logistics systems, yet integration across the full maritime city chain remains limited. The objective of this study is to assess, using a simulation-based experiment, the impact of an AI-orchestrated control policy on the performance of port–city logistics relative to a baseline scheduler. The study proposes an AI-orchestrated approach that connects autonomous ships, smart ports, central warehouses, and multimodal urban networks via a shared cloud control layer. This approach is designed to enable real-time, cross-domain coordination using federated sensing and adaptive control policies. To evaluate its impact, a simulation-based experiment was conducted comparing a traditional scheduler with an AI-orchestrated policy across 20 paired runs under identical conditions. The orchestrator dynamically coordinated container dispatching, vehicle assignment, and gate operations based on capacity-aware logic. Results show that the AI policy substantially reduced the total completion time, lowered truck idle time and estimated emissions, and improved system throughput and predictability without modifying physical resources. These findings support the expectation that integrated, data-driven decision-making can significantly enhance logistics performance and sustainability in port–city contexts. The study provides a replicable pathway from conceptual architecture to quantifiable evidence and lays the groundwork for future extensions involving learning controllers, richer environmental modeling, and real-world deployment in digitally connected logistics corridors. Full article

As the largest exporter in the global solid tire market, Sri Lanka’s natural rubber supply chain plays a critical role in global production, yet its social dimension remains largely unaddressed. Our study aims to assess the social performance of a Sri Lankan natural rubber supply chain in solid tire manufacturing using social life cycle assessment (S-LCA) in a cradle-to-gate approach. Study adapts “More Good and Less Bad” method which captures both positive and negative social impacts, addressing traditional S-LCAs’ focus on negative impacts solely. It applies to updated methodological sheets to distinguish “good” and “bad” social conditions across subcategories based on baseline compliance. Social impacts were quantified using a Social Performance Index (SPI), calculated by multiplying social performance levels by working hours at the organizational level, comprising SPI_good for good social impacts and SPI_bad for bad social impacts. Data was collected through stakeholder interviews, with working hours calculated using a “working hour model”. Results showed mixed social performance across 39 subcategories, identifying six social hotspots: promoting social responsibility (27.67% less bad, 72.32% more good), wealth distribution (26.87% less bad, 73.13% more good), commitment to sustainability issues (100% less bad), social benefits (100% less bad), safe and healthy living conditions (100% less bad), and hours of work (88.74% less bad, 11.26% more good). Full article

To achieve more precise and regionally adaptive emission control, this study develops a dual-control framework that simultaneously constrains both total carbon emissions and pollutant concentration levels. Regional environmental heterogeneity is incorporated into the dispatch of generating units to balance emission reduction and operational efficiency. Based on this concept, a regional carbon emission allowance allocation model is constructed by integrating ecological pollutant concentration thresholds. A multi-source Gaussian plume dispersion model is further developed to characterize the spatial and temporal distribution of pollutants from coal-fired power units. These pollutant concentration constraints are embedded into an environmental–economic dispatch model of a coupled electricity–hydrogen–carbon system supported by hybrid storage. By optimizing resource use and minimizing environmental damage at the energy-supply stage, the proposed model provides a low-carbon foundation for the entire industrial production cycle. This approach aligns with the sustainable development paradigm by integrating precision environmental management with circular economy principles. Simulation results reveal that incorporating pollutant concentration control can effectively reduce localized environmental pressure while maintaining overall system economy, highlighting the importance of region-specific environmental capacity in enhancing the overall environmental friendliness of the industrial chain. Full article

Background: In this new era, marked by increasing environmental concerns, geopolitical crises, and global disruptions, traditional efficiency-focused supply chains have shown significant vulnerabilities. As a result, the shift toward new strategies to maintain sustainability has become more crucial. Meanwhile, to withstand disruptions, supply chains must develop robustness and resilience. More recently, attention has turned toward viability to enable sustainable supply chain operations over the long term under uncertainty. Methods: This study conducts a systematic literature review (SLR) to explore the links between green supply chain management (GSCM), supply chain resilience (SCRES), and supply chain viability (SCV), guided by the PRISMA framework and structured using the PICO approach as a high-level scoping tool. We reviewed 70 peer-reviewed journal articles published between 2010 and 2024. Result: The study identified widely adopted green practices and explored their impact on supply chain resilience and sustainable performance. Many studies address GSCM, SCRES, and SCV either separately or in pairs, but few integrate all three dimensions. GSCM fosters resilience, and when the three aspects are combined, they serve as the cornerstones of viable supply chains. However, their potential contribution to supply chain viability is still unexplored. Conclusions: These insights provide useful guidance for creating supply chains that balance long-term continuity, disruption-readiness, and environmental goals. They also suggest a future research agenda to better align these three priorities. Full article

Strengthening their supply chain resilience constitutes a strategic priority for Chinese enterprises to respond to evolving globalization patterns and sustain long-term competitiveness in an increasingly sustainability-oriented market. This research systematically measures enterprise supply chain resilience by analyzing panel data from Chinese listed firms (2010–2022) through the tri-dimensional constructs of resistance capacity, recovery resilience, and adaptive creativity. Regression analyses demonstrate that digital transformation significantly improves enterprise supply chain resilience, exhibiting dual-threshold characteristics in nonlinear relationships. Mediation tests reveal that information sharing and resource integration capabilities serve as the critical transmission channels. Digital transformation demonstrates strong predictive validity for both the resistance capacity and adaptive creativity of supply chains. The seemingly paradoxical findings on enterprise operational efficiency highlight the need for a more layered and dynamic understanding of its underlying mechanisms. The positive impact of digital transformation on supply chain resilience demonstrates heterogeneity across state-owned versus non-state-owned enterprises, regions, and industry types. The findings offer actionable insights for orchestrating digital transformation initiatives and designing tiered supply chain resilience frameworks that support enterprises’ sustainability goals. Full article

Universal accessibility remains a critical challenge for effective public transport and urban equity. This study addresses the need for operational prioritisation tools by proposing a robust hybrid methodology to rank interventions at urban mobility nodes. The approach combines the Analytic Hierarchy Process (AHP) for integrating expert and participatory criteria weighting with four Multi-Criteria Decision-Making (MCDM) techniques (TOPSIS, VIKOR, COPRAS, and ARAS) to ensure solution reliability. Empirical validation, conducted on 30 bus stops in Segovia, Spain, confirmed the methodological soundness, evidenced by near-perfect correlations (ρ = 0.99) among the compromise and additive ratio models (TOPSIS–VIKOR and COPRAS–ARAS) and stability across over 85% of sensitivity simulations. The findings validate that the methodology effectively guides resource allocation towards interventions yielding maximum social impact and demonstrate its transferability to complex urban supply chain contexts, such as logistics microhubs. Ultimately, this replicable and adaptable model supports the transition towards more equitable, resilient urban systems, aligning directly with Sustainable Development Goal 11 (Sustainable Cities and Communities). Full article

In the context of environmental challenges and digital transformation, artificial intelligence (AI) plays a key role in promoting sustainable development within Industry 4.0 and the emerging paradigm of Industry 5.0. This study systematically reviewed the literature (2015–2025) from Scopus and Web of Science on the connections between AI, circular economy, industrial paradigms, and the Sustainable Development Goals (SDGs), with a particular focus on supply chains and SDG 12—responsible consumption and production. The majority of research emphasizes managerial aspects, the application of machine learning and robotics, as well as waste reduction, resource optimization, and circular economy practices within supply chain and production–consumption systems. Geographical analysis shows that larger economies serve as central research hubs, while some countries that are not among the most populous often achieve the highest average citations per document. Temporal keyword trends indicate a shift in research focus from operational efficiency in traditional supply chains (optimization) toward supply chain digitalization (artificial intelligence) and sustainability (circular economy). Keyword trends reveal four thematic clusters: supply chain digitalization, agritech, smart industry, and sustainability. The study highlights future research directions, including integrating circular economy with managerial and technical approaches, linking Industry 5.0 with SDG 12, and applying advanced AI in sustainable industrial practices. The increasing attention to ethical and social dimensions underscores the need for AI solutions that are both technologically advanced and sustainability oriented. Full article

Grounded in the United Nations Sustainable Development Goal 4 (SDG4), specifically addressing the urgent need to increase relevant skills for decent work (Target 4.4) while ensuring inclusive access and quality (Targets 4.3, 4.5, 4.c), this study develops a province-level indicator system for the “talent chain” and “industry chain” and integrates entropy-weighted composite evaluation, a coupling coordination model, correlation tests, and mismatch typology classification to systematically assess the alignment between higher education talent formation and industrial demand across 31 Chinese provinces during 2000–2022. The analysis aims to characterize China’s phase-specific progress in SDG4-consistent development at the education–industry interface and to provide a theoretical and empirical basis for improving graduate job matching. The results show that (1) overall talent–industry matching improved steadily from 2000 to 2022, yet pronounced regional disparities persist, with eastern provinces generally outperforming central and western regions; (2) educational quality and structural inputs—such as faculty capacity, per-student expenditure, and the composition of human capital—are the primary drivers of talent-chain performance, whereas expansion-oriented indicators exhibit limited marginal contributions, implying that sustainable graduate job matching hinges more on quality upgrading and supply-structure optimization than on quantitative expansion alone; (3) industry-chain advancement is jointly driven by industrial scale, structural upgrading, and employment absorptive capacity, with the tertiary sector playing a particularly prominent role in shaping demand for higher-skilled labor; and (4) a divergence in driving mechanisms—quality- and structure-oriented on the education side versus scale- and structure-oriented on the industry side—combined with regional heterogeneity produces stage-specific mismatch typologies, suggesting remaining scope for structural alignment between higher education systems and industrial upgrading. Overall, strengthening regional coordination, integration, quality, and upgrading drives synergistic development, advancing SDG 4 targets by validating that quality-driven education reform is the key lever for sustainable employment in China. Full article

To align with disaster monitoring and sustainable risk assessment, the low-carbon transition of fisheries necessitates comprehensive carbon emission management throughout the supply chain. As China advances supply-side structural reform, transitioning from traditional to low-carbon fisheries is vital for the green development of the industry and its associated sectors. This study employs input–output models and LMDI decomposition to examine the trends and drivers of embodied carbon emissions within China’s fishery production system from 2010 to 2019. By constructing a cross-sectoral full-emission accounting system, the research calculates total direct and indirect emissions, exploring how accounting scopes influence regional responsibility and reduction strategies. Empirical results indicate that while China’s aquatic trade and processing have steadily developed, the sector remains dominated by low-value-added primary products. This structure highlights vast potential for deep processing development amidst shifting global dietary habits. Factor decomposition reveals that economic and technological development are the primary drivers of carbon emissions. Notably, technological progress within fisheries emerges as the most significant factor, playing a pivotal role in both driving and potentially mitigating emissions. Consequently, to effectively lower carbon intensity, the study concludes that restructuring the fishery industry is crucial. Promoting low-carbon development and enhancing the R&D of green technologies are essential strategies to navigate the dual challenges of industrial upgrading and environmental protection. Full article

Source plasma centers sustain hematology therapeutics by safeguarding testing, traceability, and cold-chain integrity before fractionation. Despite regulatory requirements (21 CFR 606/640; EU Directive 2005/62/EC), published pre-operational validation frameworks demonstrating deviation-readiness before first collections remain sparse. We conducted a simulation-based pre-operational validation of an electronic quality management system (eQMS) with an Incident → Deviation → Corrective Action and Preventive Action (CAPA) pathway at a new source plasma center, performing 20 chairside mock runs, 3 freezer-alarm drills, and a document-control stress test. Primary endpoints were anomaly rate, alarm-response time relative to a 15 min service-level agreement (SLA), and deviation-closure SLA compliance. Analyses were descriptive and designed to demonstrate system functionality, not long-term process stability. Minor anomalies occurred in 6/20 mock runs (30.0%; 95% CI 11.9–54.3); no major/critical events were observed (0/20; 95% CI 0–16.8). Deviation-closure SLAs were met in 6/6 tests (100%; 95% CI 54.1–100). Alarm-response times averaged 7.0 min (SD 1.0; range 6–8 min; 95% CI 4.5–9.5), and all drills met the 15 min vendor SLA, illustrating a preliminary readiness margin (Cpu ≈ 2.7) rather than a statistically stable capability estimate. Simulation-based pre-operational validation produced inspection-ready documentation and quantitative acceptance criteria aligned to U.S./EU expectations, supporting reproducible multi-site deployment. By protecting cold-chain integrity and traceability before first collections, the validated QMS helps preserve supply reliability for plasma-derived therapeutics central to hematology care and establishes the measurement infrastructure for post-operational performance validation. Full article

Background: Sustainable operations and management are imperative in many sectors, including aquaculture, to adapt to the increasing complexity and unprecedented challenges across the supply chain. Although research in sustainable supply chain management (SSCM) has grown significantly, it remains inadequate for fully addressing the distinct challenges of the aquaculture supply chain (ASC). Therefore, this paper aims to introduce the concept of the sustainable management of the aquaculture supply chain (SMASC) and identify research gaps for future research directions. Methods: This study conducts a systematic literature review using the Web of Science and Scopus databases to retrieve peer-reviewed articles published between 2000 and 2025. A total of 116 articles were subjected to an in-depth content analysis, leading to the conceptualization of SMASC. Results: The findings indicate that ASC exhibits considerable heterogeneity in structure and performance measures, reflecting the inherent diversity of species and culture systems. The proposed conceptual framework provides a coherent understanding of SMASC by extending generic SSCM to incorporate distinctive characteristics of aquaculture, while systematically identifying the core pillars and their interrelationships. Conclusions: The SMASC framework establishes a unified theoretical foundation for the comprehensive management of ASCs, offering conceptual and practical insights for both researchers and practitioners. Full article

Small and medium-sized enterprises (SMEs) play a central role in employment and regional economic development, yet they are highly vulnerable to shocks such as pandemics, energy price spikes, and supply chain disruptions. Scenario modelling, stress testing, and digital twins are used to assess resilience, yet most applications focus on large firms in single-country settings. This article develops a model to stress test the resilience of Slovenian SMEs, calibrated with parameters and mechanisms derived from South African SME resilience studies. A system dynamics model with stocks for cash, inventory, and productive capacity is specified and subjected to demand, supply, financial, and compound shock scenarios, with and without resilience measures such as liquidity buffers, customer and supplier diversification, and basic digital planning capabilities. Results indicate non-linear tipping points where small reductions in liquidity sharply increase the likelihood of distress, and show that combinations of liquidity, diversification, and collaborative supply chain practices reduce the depth and duration of output losses. The study demonstrates how evidence from an African context can inform resilience strategies in a small European economy and provides a transparent, portable modelling architecture that can be adapted to other settings. Implications are discussed for SME managers and for policies supporting sustainable, resilient enterprise ecosystems. Full article