Search Results (136)

Digital transformation is central to circular economy (CE) strategies, yet the intersection between digital innovation and women’s entrepreneurship remains underexplored. We examine how IoT, AI, blockchain, data analytics and platform technologies are represented in CE-oriented management research and assess the visibility of gender-inclusive and women entrepreneurship perspectives. We merged Scopus and Web of Science records (2015–2025), removed duplicates, screened for relevance, and mapped themes and networks using bibliometrix (R) and VOSviewer. Digital-CE scholarship was found to rise after 2018, dominated by smart manufacturing, circular supply chains, digital product passports and blockchain traceability. Four clusters emerged: digital circular manufacturing, circular business model innovation, waste and resource management, and policy–social aspects. Gender-related terms appear in only 1.35% of the corpus, revealing a gap between academic research and EU policy priorities for inclusive digital and circular transitions. We integrate a gender-inclusive lens and outline an agenda positioning women entrepreneurs as critical yet overlooked actors in digital circular ecosystems. As a bibliometric review, this study maps scholarly attention rather than the prevalence of women-led circular ventures. Beyond mapping, we advance the paper’s primary contribution by proposing a governance-oriented synthesis that frames digital infrastructures as administrative mechanisms shaping who can participate in, benefit from, and influence digital circular ecosystems. Full article

Circular economy (CE) decouples value creation from virgin resource use and waste in the medical device sector, which faces stringent patient-safety, quality, and regulatory obligations. Green Additive Manufacturing (AM) offers a precise, digitally driven route to implement CE through dematerialization, on-demand localized production, topology optimization, and material circularity. In this study, a comprehensive CE framework is tailored to medical device manufacturing that integrates eco-design, material circularity, remanufacturing, and regulatory compliance across the product life cycle. Methods include an International Organization for Standardization (ISO) 14040/44-aligned life cycle assessment, process energy metering, sterilization-compatibility studies, mechanical/biocompatibility verification to relevant standards, and a techno-economic/circularity analysis with Monte Carlo uncertainty quantification. Three case studies are explored using bio-based PA11 (selective laser sintering), recycled polyethylene terephthalate glycol (fused deposition modeling), and low-volatile organic carbon biocompatible photopolymer (stereolithography): (1) a patient-specific wrist orthosis, (2) a dental surgical guide, and (3) a single-use catheter Y-connector. Results indicate 38–68% reductions in embodied greenhouse-gas emissions, 22–54% energy savings per functional unit, and up to 80% mass recapture through in-process powder/runner reuse while maintaining clinical performance and regulatory conformity. Design-for-circularity patterns (DfC) were created for DfDisassembly, DfSter, DfTraceability, DfUpgrade, and DfPowder-Loop and provide a governance architecture combining ISO 13485 QMS, ISO 10993 biological evaluation, the European Union’s Medical Device Regulation (Regulation (EU) 2017/745), and the United States Food and Drug Administration’s guidance on Additive Manufactured (3D-printed) medical devices, guidance with unique device identification for closed-loop returns. The paper concludes with an Industry 5.0 roadmap for hospital-proximate micro-factories, materials passports, and digital product passports enabling verified circular flows at scale. Full article

Agri-food supply chains are highly exposed to freshness deterioration, demand uncertainty, and information asymmetry. In practice, upstream suppliers may strategically misreport freshness-related information to influence downstream procurement decisions, which can amplify inefficiency and increase food loss and waste. This study develops an analytical framework that integrates (i) strategic freshness misreporting by an informed supplier, (ii) endogenous investment in blockchain-enabled traceability that improves information credibility at a cost, and (iii) contract design for supply chain coordination. We consider a two-echelon agri-food supply chain with stochastic demand and freshness-dependent valuation, and characterize equilibrium operational decisions under centralized and decentralized settings. The results reveal how misreporting reshapes optimal order quantities, wholesale prices, and profit allocation, and identify conditions under which misreporting increases expected waste and undermines sustainability performance. We then examine how traceability investment changes the incentives of both parties, leading to adoption thresholds and potential incentive misalignment under decentralization. Finally, we design revenue-sharing, cost-sharing, and combined contracts and derive parameter regions that coordinate the blockchain-enabled agri-food supply chain and generate Pareto improvements for both the supplier and the retailer. Numerical experiments illustrate the comparative statics and quantify the trade-offs among profitability, transparency, and waste reduction. Relative to existing blockchain-enabled agri-food supply chain models, the framework jointly endogenizes supplier misreporting of freshness, blockchain-based traceability investment, and contract parameters, thereby uncovering new adoption thresholds and coordination regions that tightly link transparency decisions to food loss and waste. The findings provide actionable guidance for using digital traceability and contract mechanisms to curb opportunism, enhance coordination, and support sustainable agri-food supply chains. Full article

Background: Rare cancers combine low incidence with high biological heterogeneity and multi-institutional care trajectories. These features make single-center learning structurally incomplete and render pathway fragmentation a dominant driver of preventable harm, variability, and waste. In this context, care quality is best understood as a property of pathway integrity across routing, diagnostics (imaging/biopsy planning), multidisciplinary intent-setting, definitive treatment, and surveillance—rather than as a department-level attribute. Objective: To define a pragmatic, transferable operating blueprint for a rare-cancer Learning Health System (LHS) that turns routine care into continuous, auditable learning under explicit governance, while maintaining claims discipline and protecting measurement validity. Approach: We synthesize an implementation-oriented operating model using the Swiss Sarcoma Network (SSN) as an exemplar. The blueprint couples clinical governance (Integrated Practice Unit logic, hub-and-spoke routing, auditable multidisciplinary team decision systems) with an interoperable real-world-time data backbone designed for benchmarking, pathway mapping, and feedback. The operating logic is expressed as a closed-loop control cycle: capture → harmonize → benchmark → learn → implement → re-measure, with explicit owners, minimum requirements, and failure modes. Results/Blueprint: (i) The model specifies a minimal set of data primitives—time-stamped and traceable decision points covering baseline and tumor characteristics, pathway timing, treatment exposure, outcomes and complications, and feasible longitudinal PROMs and PREMs; (ii) a VBHC-ready, multi-domain measurement backbone spanning outcomes, harms, timeliness, function, process fidelity, and resource stewardship; and (iii) two non-negotiable validity guardrails: explicit applicability (“N/A”) rules and mandatory case-mix/complexity stratification. Implementation is treated as a governed step with defined workflow levers, fidelity criteria, balancing measures, and escalation thresholds to prevent “dashboard medicine” and surrogate-driven optimization. Conclusions: This perspective contributes an operating model—not a platform or single intervention—that enables credible improvement science and establishes prerequisites for downstream causal learning and minimum viable digital twins. By distinguishing enabling infrastructure from the governed clinical system as the primary intervention, the blueprint supports scalable, learnable excellence in rare-cancer care while protecting against gaming, inequity, and inference drift. Distinct from generic LHS or VBHC frameworks, this blueprint specifies validity gates required for rare-cancer benchmarking—explicit applicability (“N/A”) rules, denominator integrity/capture completeness disclosure, anti-gaming safeguards, and escalation governance. These elements are critical in rare cancers because small denominators, high heterogeneity, and multi-institutional pathways otherwise make benchmarking prone to artifacts and unsafe inferences. Full article

The food processing industry is undergoing a profound transformation with the integration of Artificial Intelligence (AI), evolving from traditional automation to intelligent, adaptive systems aligned with Industry 5.0 principles. This review examines AI’s role across the food value chain, including supply chain management, quality control, process optimization in key unit operations, and emerging areas. Recent advancements in machine learning (ML), computer vision, and predictive analytics have significantly improved detection in food processing, achieving accuracy exceeding 98%. These technologies have also contributed to energy savings of 15–20% and reduced waste through real-time process optimization and predictive maintenance. The integration of blockchain and Internet of Things (IoT) technologies further strengthens traceability and sustainability across the supply chain, while generative AI accelerates the development of novel food products. Despite these benefits, several challenges persist, including substantial implementation costs, heterogeneous data sources, ethical considerations related to workforce displacement, and the opaque, “black box” nature of many AI models. Moreover, the effectiveness of AI solutions remains context-dependent; some studies report only marginal improvements in dynamic or data-poor environments. Looking ahead, the sector is expected to embrace autonomous manufacturing, edge computing, and bio-computing, with projections indicating that the AI market in food processing could approach $90 billion by 2030. Full article

The rapid increase in e-waste has become a significant global concern, influenced by swift technological advancements, shorter product lifecycles, and rising consumer demand. This situation leads to considerable environmental and health hazards, primarily due to the presence of toxic materials, energy demands, and the inadvertent loss of valuable resources when waste is not adequately managed. This review synthesises contemporary theories related to sustainable e-waste management, featuring concepts such as principles of the circular economy, energy efficiency and innovative recycling technologies. The review explores a range of actions, including regulatory strategies, mechanical pre-treatment methods, focusing on reagent-free recovery techniques, and the utilisation of digital solutions to enhance traceability and operational efficiency. The findings indicate substantial improvements in formal e-waste collection rates in areas with strong legislative frameworks, enhanced metal recovery efficiencies through refined hydrometallurgical and pyrometallurgical techniques and minimised environmental footprints through reagent-free and energy-conserving practices. The review emphasises the importance of viewing e-waste recycling not just as a waste management issue but as a fundamental element of resource security and sustainable industrial practices. By assessing recent developments, this work advocates for closed-loop recycling as an essential driver in the global shift towards a resilient, low-carbon, energy-efficient and circular economy. Full article

Sustainability in the agri-food sector has become a cornerstone of global efforts to combat climate change, ensure food security through climate-smart agriculture, and strengthen economic resilience. Sustainability reporting within agri-food systems has gained increasing regulatory significance with the introduction of mandatory frameworks such as the Turkish Sustainability Reporting Standards (TSRSs). This article searches for the sustainability reports of agri-business firms listed in BIST in Turkey. Although TSRS reporting is not yet mandatory for the agribusiness sector, this study examines the first TSRS-aligned sustainability reports published by eight agri-food companies, excluding the retail sector. The analysis assesses how effectively these reports address sector-specific environmental and social challenges defined in the GRI 13 Agriculture, Aquaculture and Fishing Sector Standard and their alignment with the United Nations Sustainable Development Goals (SDGs). Using a structured content analysis approach, disclosure patterns were examined at both thematic and company levels. The findings indicate that TSRS-aligned reports place strong emphasis on environmental and climate-related disclosures, particularly emissions, climate adaptation and resilience, water management, and waste. In contrast, agro-ecological and land-based impacts—such as soil health, pesticide use, and ecosystem conversion—are weakly addressed. Economic disclosures are predominantly framed around climate-related financial risks and supply chain traceability, while social reporting focuses mainly on occupational health and safety, employment practices, and food safety, with limited attention to labor and equity issues across the broader value chain. Company-level results reveal marked heterogeneity, with internationally active firms demonstrating deeper alignment with GRI 13 requirements. From an SDG alignment perspective, high levels of coverage are observed across all companies for SDG 13 (Climate Action), SDG 12 (Responsible Consumption and Production), and SDG 6 (Clean Water and Sanitation). By contrast, SDGs critical to agro-ecological integrity and social equity—namely SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 10 (Reduced Inequalities), and SDG 15 (Life on Land)—are weakly represented or entirely absent. Overall, the results suggest that while TSRS-aligned reporting enhances transparency in climate-related domains, it achieves only selective alignment with the SDG agenda. This underscores the need for a stronger integration of sector-specific sustainability priorities into mandatory sustainability reporting frameworks. Full article

Occupational exposure to sharps waste represents a critical challenge for public health systems, directly affecting healthcare workers’ safety, institutional costs, and environmental sustainability. This study aimed to analyze sharps waste management practices and to structure improvement actions for biosafety governance in Brazilian Emergency Care Units (ECUs) through the application of the Lean Six Sigma (LSS) and DMAIC method (Define, Measure, Analyze, Improve, and Control). A single multiple-case study was conducted across three public units in different regions of Brazil, combining direct observation, regulatory checklists based on ANVISA Resolution No. 222/2018 (RDC), and cause–and–effect (5M) analysis. The diagnostic phase identified recurrent nonconformities in labeling, documentation, and internal transport routes, primarily due to managerial and behavioral gaps. Based on these findings, the DMAIC framework supported the development of a low-cost, evidence-based action plan that outlined proposed interventions, including visual checklists, standardized internal routes, and key performance indicators (KPIs), intended to strengthen biosafety traceability and occupational safety. The se proposed actions are expected to support continuous learning, staff engagement, and a culture of shared responsibility for safe practices. Overall, the study provides a structured basis for future implementation and empirical validation of continuous improvement initiatives, aimed at enhancing public health governance and occupational safety in resource-constrained healthcare environments. Full article

Licorice (Glycyrrhiza glabra) is a perennial herb traditionally valued for its aromatic and therapeutic properties. In recent years, however, growing attention has shifted toward the technical and environmental potential of the plant’s industrial by-products, particularly the fibrous material left after extraction. This review integrates botanical knowledge with engineering and industrial perspectives, highlighting the role of licorice fiber in advancing sustainable innovation. The natural fiber obtained from licorice roots exhibits notable physical and mechanical qualities, including lightness, biodegradability, and compatibility with bio-based polymer matrices. These attributes make it a promising candidate for biocomposites used in green building and other sectors of the circular economy. Developing efficient recovery processes requires collaboration across disciplines, combining expertise in plant science, materials engineering, and industrial technology. The article also examines the economic and regulatory context driving the transition toward more circular and traceable production models. Increasing interest from companies, research institutions, and public bodies in valorizing licorice fiber and its derivatives is opening new market opportunities. Potential applications extend to agroindustry, eco-friendly cosmetics, bioeconomy, and sustainable construction. By linking botanical insights with innovative waste management strategies, licorice emerges as a resource capable of supporting integrated, competitive, and environmentally responsible industrial practices. Full article

Post-disaster reconstruction remains largely excluded from circular-economy approaches. This gap is particularly evident in earthquake-affected inner territories, where reconstruction is constrained by severe logistical challenges—especially in relation to rubble management—and where debris is often composed of materials closely tied to local building cultures and community identities. In these contexts, rebuilding still predominantly follows linear, emergency-driven models that treat rubble primarily as waste. This study introduces Rubble as a Material Bank (RMB), a digital–material framework that reconceptualises earthquake rubble as a traceable and programmable resource for circular reconstruction. RMB defines a rubble-to-component chain that integrates material characterisation, data-driven management, robotic fabrication, and reversible architectural design. Selected downstream segments of this chain are experimentally validated through the TRAP project, developed within the European TARGET-X programme. The experimentation focuses on extrusion-based fabrication of dry-assembled wall components using rubble-derived aggregates. The results indicate that digitally governed workflows can enable material reuse, while also revealing technical and regulatory constraints that currently limit large-scale implementation. Full article

Background: Digital technologies are increasingly integrated into circular supply chains (CSCs) to enhance resource efficiency and extend product lifecycles. However, the practical adoption of intelligent circular supply chains (iCSCs) remains underexplored. Methods: This study provides a comprehensive review of how digital technologies enable circular practices across industries. It systematically reviews 95 peer-reviewed articles from WoS and Scopus, identifying 107 real-world iCSC cases. The cases are categorized by (1) digital enablers including AI, Big Data, Blockchain, IoT, Digital Twin, Additive Manufacturing, Cloud Platforms, and Cyber-Physical Systems; (2) alignment with Circular Economy (CE); (3) sector-specific circular practices; and (4) mapping implementations to the EU Circular Economy Action Plan (CEAP). This study develops a conceptual model illustrating how digital technologies support data-driven decision-making, automation, and circular transitions. Results: The analysis shows IoT, Blockchain, and AI as the most frequently applied technologies, facilitating collaboration, traceability, sustainability, and cost efficiency. “Reduce” and “Recycle” dominate among CE strategies, while circular transition pathways such as sustainable design, waste prevention, and digital platforms link policy to practice. Conclusions: By integrating systematic evidence with a holistic framework, this work provides actionable insights, identifies key implementation gaps, and lays a foundation for advancing iCSCs in research and practice. Full article

Achieving sustainable development in the low-carbon transition requires securing critical raw materials (CRMs) while reducing environmental burdens and strengthening industrial resilience (SDGs 7, 9, 12, 13). This review synthesizes 2016–2025 evidence on how the European Union’s policy package—the Critical Raw Materials Act (CRMA), the Batteries Regulation, the Ecodesign for Sustainable Products Regulation (ESPR) with Digital Product Passports (DPPs), and the recast Waste Shipments Regulation (WSR)—shapes markets for secondary supply in battery-relevant metals such as lithium, cobalt, nickel, copper, aluminum, and rare earths. We apply a structured scoping review protocol to map the state of the art across policy instruments (EPR, ecodesign/DPP, recycled content mandates, recovery targets, shipment controls) and value chain stages (collection, preprocessing, refining, manufacturing). The analysis highlights benefits, including clearer investment signals, improved traceability, and emerging opportunities for industrial symbiosis, but also identifies drawbacks such as heterogeneous standards, compliance costs, and trade frictions. Evidence gaps remain, especially in causal ex post assessments, price pass-through, and interoperability of MRV/DPP systems. The paper contributes by (i) providing an integrative framework linking policy instruments, value chain stages, and investment signals for secondary CRM supply, and (ii) outlining a research agenda for rigorous ex post evaluation, improved MRV/DPP data architectures, and better alignment between EU trade rules, circularity, and a just energy transition. Full article

Food loss and waste (FLW) is a chronic problem across food systems worldwide, with meat being one of the most resource-intensive and perishable categories. The perishable character of meat, combined with complex cold chain requirements and consumer behavior, makes the sector particularly sensitive to inefficiencies and loss across all stages from production to consumption. This review synthesizes the latest advancements in new preservation technologies and supply chain efficiency strategies to minimize meat wastage and also outlines current challenges and future directions. New preservation technologies, such as high-pressure processing, cold plasma, pulsed electric fields, and modified atmosphere packaging, have substantial potential to extend shelf life while preserving nutritional and sensory quality. Active and intelligent packaging, bio-preservatives, and nanomaterials act as complementary solutions to enhance safety and quality control. At the same time, blockchain, IoT sensors, AI, and predictive analytics-driven digitalization of the supply chain are opening new opportunities in traceability, demand forecasting, and cold chain management. Nevertheless, regulatory uncertainty, high capital investment requirements, heterogeneity among meat types, and consumer hesitancy towards novel technologies remain significant barriers. Furthermore, the scalability of advanced solutions is limited in emerging nations due to digital inequalities. Convergent approaches that combine technical innovation with policy harmonization, stakeholder capacity building, and consumer education are essential to address these challenges. System-level strategies based on circular economy principles can further reduce meat loss and waste, while enabling by-product valorization and improving climate resilience. By integrating preservation innovations and digital tools within the framework of UN Sustainable Development Goal 12.3, the meat sector can make meaningful progress towards sustainable food systems, improved food safety, and enhanced environmental outcomes. Full article

The textile sector provides essential goods, yet it remains environmentally and socially intensive, driven by high water use, pesticide dependent monocropping, chemical pollution during processing, and growing waste streams. This review examines credible pathways to sustainability by integrating emerging plant-based fibres from hemp, abaca, stinging nettle, and pineapple leaf fibre. These underutilised crops combine favourable agronomic profiles with competitive mechanical performance and are gaining momentum as the demand for demonstrably sustainable textiles increases. However, conventional fibre identification methods, including microscopy and spectroscopy, often lose reliability after wet processing and in blended fabrics, creating opportunities for mislabelling, greenwashing, and weak certification. We synthesise how advanced molecular approaches, including DNA fingerprinting, species-specific assays, and metagenomic tools, can support the authentication of fibre identity and provenance and enable linkage to Digital Product Passports. We also critically assess environmental Life Cycle Assessment (LCA) and social assessment frameworks, including S-LCA and SO-LCA, as complementary methodologies to quantify climate burden, water use, labour conditions, and supply chain risks. We argue that aligning fibre innovation with molecular traceability and harmonised life cycle evidence is essential to replace generic sustainability claims with verifiable metrics, strengthen policy and certification, and accelerate transparent, circular, and socially responsible textile value chains. Key research priorities include validated marker panels and reference libraries for non-cotton fibres, expanded region-specific LCA inventories and end-of-life scenarios, scalable fibre-to-fibre recycling routes, and practical operationalisation of SO-LCA across diverse enterprises. Full article

Background: In the era of rapid digital transformation, efficient food logistics (FL) is critical for sustainability and competitiveness. Maintaining food quality, minimizing waste, and optimizing costs are complex challenges that advanced digital technologies aim to address, particularly amid growing e-commerce and last-mile delivery demands. This underscores the need for a structured, quantitative evaluation of technological solutions to ensure operational reliability, efficiency, and sustainability. Methods: This study employs a Multi-Criteria Decision Making (MCDM) model combining Criterion Impact LOSs (CILOS) and Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA) to evaluate key FL technologies: IoT, blockchain, Big Data analytics, automation and robotics, and cloud/edge computing. Nine evaluation criteria relevant to logistics providers were used, covering operational efficiency, flexibility, sustainability, food safety, data reliability, KPI support, scalability, costs, and implementation speed. CILOS determined criteria weights by considering interdependencies, and MOOSRA ranked technologies by benefits-to-costs ratios. Sensitivity analysis validated result robustness. Results: Automation and robotics ranked highest for enhancing efficiency, reducing errors, and improving handling and safety. Blockchain was second, supporting traceability and data security. Big Data analytics was third, enabling demand prediction and inventory optimization. IoT ranked fourth, providing real-time monitoring, while cloud/edge computing ranked fifth due to indirect operational impact. Conclusions: The CILOS–MOOSRA model enables transparent, structured evaluation, integrating quantitative metrics with logistics providers’ priorities. Results highlight technologies that enhance efficiency, reliability, and sustainability while revealing integration challenges, providing a strategic foundation for digital transformation in FL. Full article