Search Results (4,007)

Blockchain technology (BCT) is often discussed as digital support for timber traceability in the context of the EU Deforestation-Free Products Regulation (EUDR), which requires operators and traders to demonstrate legality, deforestation-free production, geolocation at the forest parcel level, and verifiable supply chain documentation from 30 December 2026, with an extended timeline for micro, small, and medium-sized enterprises (SMEs) until 30 June 2027. This study assesses where BCT can realistically add value in timber supply chains under operational forestry conditions and identifies the necessary technical, organizational, and legal prerequisites. A combination of a targeted literature review and empirical input from experts in the forestry and timber industry, including guided expert web-conferencing interviews (n = 41), an online survey (n = 69 completed responses), and a transdisciplinary workshop (n = 18) was utilized to obtain a comprehensive overview of industry perspectives. Qualitative data from interviews and workshop sessions were analyzed using structured qualitative content analysis, while survey data were evaluated using descriptive statistics. The expected benefits are associated with the introduction of tamper-proof timber harvesting practices and cross-organizational verification mechanisms. To address the discrepancy between biological uncertainty and digital rigidity, the study proposes a dynamic allocation model adapted from the energy sector that distinguishes between fixed and variable wood capacities to automate logistical planning via smart contracts. However, respondents emphasize that practical obstacles, such as limited digital maturity in forestry, fragmented data infrastructures across the supply chain, and unresolved issues of data sovereignty hinder the implementation of BCT. BCT alone is unable to resolve the problem of weak physical-digital identity continuity, a phenomenon widely known as the oracle problem; however, coupling the ledger with physical or biological anchors (e.g., photo-optical, automated inkjet marking identification) can re-establish this physical–digital continuity and thereby resolve the oracle problem. The results demonstrate that blockchain acts most plausibly as a supporting component within hybrid traceability architectures that prioritize event-based authentication, off-chain data processing where appropriate, and integration with existing certification systems. The study highlights the necessity of defining distinct organizational roles and responsibilities while integrating user-centric digital solutions tailored specifically to small and medium-sized enterprises (SMEs). Full article

Firmware forms the persistent software layer controlling embedded and Internet-of-Things (IoT) devices, industrial controllers, automotive systems, and cyber-physical infrastructure. Vulnerabilities in firmware enable remote compromise, supply-chain attacks, and long-lived implants that survive operating-system reinstallation. This review synthesises 118 works published from 2014 to 2026—comprising 78 primary research studies; 23 surveys and systematisations of knowledge; and 17 benchmarks, tools, and background references—covering the full firmware reverse engineering (FRE) pipeline: physical acquisition (including fault injection and side-channel extraction), format analysis and unpacking, static analysis (binary code similarity detection, protocol reverse engineering, and patch diffing), dynamic analysis and hardware emulation, fuzzing-based vulnerability discovery, and artificial intelligence (AI) and large language model (LLM)-assisted analysis. Three additional dimensions are surveyed: digital twin-assisted firmware security testing; secure boot, trusted execution environment (TEE), and over-the-air (OTA) update security; and firmware rootkit and implant detection. Coverage spans two axes—the firmware class (Linux-based IoT, microcontroller-unit bare-metal, RTOS, UEFI/BIOS, PLC/ICS, and automotive ECU) and analysis depth (surface scanning to exploit-validated vulnerability chains). We identify ten structural gaps, including the absence of unified evaluation benchmarks, fragmented peripheral modelling, the scalability–fidelity trade-off in re-hosting, and insufficient grounding of LLM tools in firmware-specific realities. We conclude with six research directions for trustworthy, scalable, and infrastructure-aware firmware analysis. Full article

Digital human resource management (HRM) systems can expand employees’ access to information, development opportunities, and organisational services, but their employee-level implications remain insufficiently understood in manufacturing settings. This cross-sectional study examines whether perceived digital HRM accessibility is associated with organisational justice, psychological contract fulfilment, employee voice behaviour, and innovative work behaviour in Morocco’s automotive manufacturing sector. Survey data from 180 employees across five manufacturers were analysed using partial least squares structural equation modelling. Perceived accessibility was positively associated with organisational justice (β = 0.521, p < 0.001) and psychological contract fulfilment (β = 0.551, p < 0.001). Organisational justice was associated with voice (β = 0.339, p < 0.001), and psychological contract fulfilment was associated with innovative work behaviour (β = 0.439, p < 0.001). The specific indirect associations were β = 0.177 through justice and β = 0.242 through psychological contract fulfilment. For the justice–voice route, both the indirect and direct associations were statistically significant; for the psychological-contract–innovation route, only the indirect association was significant. The findings concern employee-level perceptions and behaviours; they do not establish objective digital inequality, causal effects, or supply-chain-level outcomes. Full article

The global pasta industry is increasingly challenged to reconcile consumer demand for convenience with the need to reduce environmental impacts across the food supply chain. This study presents a cradle-to-grave Product Environmental Footprint (PEF) assessment integrated with Monte Carlo stochastic simulations to evaluate four durum wheat (Triticum durum) semolina pasta systems: traditional dry pasta, fresh pasta, instant pasta in a rigid cup, and an eco-designed instant pasta in a flexible pouch. Systems were evaluated using a primary functional unit of 1 kg of commercial product and normalized to an isocaloric serving to account for variations in moisture content and preparation. When evaluated across the full cradle-to-grave system boundary, traditional dry pasta (1.91 ± 0.08 kg CO_2e/kg) and flexible-pouch instant pasta (1.72 ± 0.08 kg CO_2e/kg) achieve comparable, lowest overall impacts, while the rigid cup format (3.85 ± 0.17 kg CO_2e/kg) is heavily penalized by packaging mass intensity and transport inefficiency. Industrial starch pre-gelatinization creates a porous structure enabling rapid passive rehydration (0.90 kWh/kg domestic energy), which fully offsets factory thermal inputs (0.326 kWh/kg) and dramatically outperforms traditional stovetop boiling (2.40 kWh/kg). Crucially, replacing rigid cups with flexible pouches reduces total packaging material mass per kg of net pasta product by 72.5% (279.8 g/kg vs. 1016.2 g/kg), avoiding severe volumetric logistics penalties. Conversely, fresh pasta incurs the highest Climate Change impact (4.14 ± 0.17 kg CO_2e/kg) due to continuous cold-chain distribution and storage requirements. Overall, this work demonstrates that shifting thermal energy processing from domestic preparation to factory pre-gelatinization—when combined with ambient shelf stability and lightweight flexible packaging—provides a promising eco-design strategy to decarbonize convenience foods, subject to commercial validation of packaging barrier performance and consumer acceptance. Full article

In the aviation sector, spare parts management plays a critical role in mitigating aircraft downtime caused by stockouts while supporting the efficient and sustainable use of resources in maintenance operations. It involves a range of inventory control methodologies combined with spare parts demand forecasting, which is particularly challenging due to the stochastic nature of component failures. Beyond ensuring operational readiness, effective spare parts management can contribute to sustainability by reducing excess inventory, minimizing waste from obsolete components, and optimizing storage and transportation requirements within Maintenance, Repair, and Overhaul (MRO) systems. Accurate demand forecasting has the potential to enhance both supply chain resilience and environmental performance, as it may contribute to the mitigation of overproduction, stockouts, unnecessary and emergency transportation, and resource waste. This study provides a systematic review of recent approaches to spare parts forecasting and infers their contribution to sustainability in the aviation industry. A systematic review was conducted, including the identification, screening, and analysis of studies published between 2010 and 2025. The review of 15 selected studies highlights the growing relevance of aligning demand forecasting with spare parts management, enabling more efficient inventory decisions that improve aircraft availability while supporting resource efficiency and sustainability objectives in MRO operations. This study consolidates current knowledge on sustainable spare parts management practices in aviation and identifies key areas for future research in aviation supply chains. Full article

Background: Regenerative supply chain research seeks to move beyond minimal-harm sustainability toward forms of organizing that preserve, restore, and enhance social–ecological systems. However, existing work often explains regeneration through principles, capabilities, and governance arrangements while giving less attention to the uneven socioecological conditions and appropriative dependencies that shape supply-chain activity. Methods: This conceptual study uses an abductive close reading of Anna Lowenhaupt Tsing’s The Mushroom at the End of the World as a sole-source textual dataset. The analysis combines an immanent reading of the complete monograph with a theory-informed reading that places Tsing’s concepts in dialogue with regenerative supply-chain scholarship. Results: The study develops two linked theoretical shifts. First, it conceptualizes supply chains as patchy socioecological assemblages composed of firms, livelihoods, infrastructures, ecological processes, and disturbance histories that only partially cohere under managerial control. Second, it defines regenerative attunement as the ongoing, place-sensitive reconfiguration of supply-chain scale, timing, governance, and value distribution so that economic activity helps reproduce rather than merely appropriate socioecological capacities. Conclusions: These concepts extend regenerative supply-chain theory by clarifying the relationships among supply-chain structure, value appropriation, temporal plurality, and distributed governance, while providing directions for managerial diagnosis and future empirical research. Full article

The transition toward decentralized renewable energy systems creates monitoring problems that current digital infrastructures do not solve: sustainability claims are produced by the same actors they evaluate, environmental evidence is reported periodically rather than observed continuously, and the communities most affected by deployment cannot inspect the data used to represent their territories. Existing integrated platforms combine subsets of the blockchain, Internet of Things (IoT) sensing and life cycle assessment (LCA) at the data layer, but they do not organize that integration through an explicit governance structure. This paper contributes a cybernetic governance framework in which the Viable System Model (VSM) supplies the organizing structure of a blockchain–IoT–LCA monitoring architecture, so that sensing, distributed trust, strategic intelligence and participatory governance are recursively coupled rather than sequentially chained. The framework was developed and evaluated under the Design Science Research paradigm, and instantiated in the IMPACT Energy.CO platform across two technology routes, wind and solar, in La Guajira, Cesar, Atlántico and Magdalena, Colombia. Evaluation against six pre-declared criteria reports 45 executed test cases with a 100% pass rate, 90% unit and 87% integration code coverage, load tests up to 5000 concurrent users with zero errors and sub-second mean response, an operating hash-chained provenance layer issuing verifiable LCA certificates, 14 participatory validation workshops, 199 users trained and 166 technicians certified. We use traceability in a deliberately narrow sense throughout: the property whereby a committed record can be linked to the ingested data series, model version and computation that produced it, and its integrity and ordering checked by a party that does not trust the producer. It is provenance and integrity traceability from the point of ingestion onward, and it is not metrological traceability: the architecture cannot verify that an original sensor measurement corresponds to the physical quantity it purports to represent. We accordingly make explicit what the architecture does not guarantee: a ledger protects records after commitment but cannot certify measurement at the point of capture, and we present a threat model, a set of implemented controls and the residual risk that remains. This study contributes an architecture, a reproducible development and evaluation method, and a calibrated account of what verifiable environmental monitoring can and cannot deliver in contested Global-South territories. Full article

Claims of AI sovereignty are increasingly invoked but operational control remains uneven. Claims to control are made through national models, sovereign clouds, data localization mandates, and procurement rules; however, whether such claims translate into demonstrable control over how AI systems are run, inspected, and contested remains poorly understood. This paper introduces credible sovereignty, the gap between declared and demonstrable control in deployment, as a conceptual lens for analyzing AI governance to examine how this gap is opened and closed across infrastructure, data, and model supply chains. Using a PRISMA-guided social-science corpus and machine learning-based BERTopic modeling, validated through topic diversity and topic separation diagnostics and triangulated through close reading, the analysis identifies four governance logics through which sovereignty is contested: data infrastructure and legitimacy frameworks; techno-bloc diplomacy and infrastructure politics; European regulatory sovereignty; and community-driven sovereignty in the Global South. Across these logics, sovereignty is enacted less through national capabilities than through proxy mechanisms—certification regimes, procurement clauses, cloud governance, and deployment architectures—each carrying trade-offs between autonomy, dependence, and accountability. Rereading the corpus through an Antecedents–Decisions–Outcomes lens yields a testable research agenda: antecedents that push actors toward sovereignty seeking; design and governance choices that translate ambition into implementation; and outcomes—resilience, inclusion, accountability—against which sovereign AI programs should be assessed. This paper reframes sovereignty as a layered operational capability rather than a discursive claim and links computational synthesis to a normative construct that applies across jurisdictions and scales. Full article

In recent years, interest in artificial intelligence has grown significantly, particularly in the development of advanced computational models for supply chain decision-making. Inventory management is one of the areas in which intelligent algorithms can support demand forecasting, replenishment, stock control, and operational optimization under uncertainty. This study presents an updated systematic literature review of intelligent algorithms applied to inventory management. The review followed PRISMA 2020 guidelines and combined database searches in Scopus, ScienceDirect, Web of Science, IEEE Xplore, SpringerLink, Taylor & Francis, and complementary manual searching. The original search covering January 2020 to December 2024 was updated in July 2026 to include studies published or available online up to June 2026. After applying strict eligibility criteria, 37 primary studies with quantitative evidence were included. The updated corpus confirms the predominance of deep learning, reinforcement learning, and hybrid intelligent models, while also showing the recent emergence of Transformer-based, graph neural network, multi-agent reinforcement learning, and prescriptive analytics approaches. The most frequent application areas were inventory control, inventory optimization, replenishment decision-making, and demand forecasting. Reported improvements were mainly associated with cost efficiency, service level, stockout reduction, and system performance; however, the magnitude of improvement varied across algorithms, data sources, sectors, and simulation or real-world settings. Overall, intelligent algorithms represent a relevant tool for improving inventory management, but their adoption requires careful validation, transparent reporting, and alignment with the operational context. Full article

This study presents an integrated approach for sustainable food supply chain design by evaluating how sourcing geography and logistics network structure influence Global Warming Potential (GWP) in a multi-echelon Mexican cold chain integrating Life Cycle Assessment (LCA) and Linear Programming (LP) network optimization. Three soy products are evaluated: edamame from China, tofu from the U.S., and textured vegetable protein (TVP) modeled as a soy-based alternative. Results are calculated using a cradle-to-retailer system boundary, normalized to 100 g of delivered protein. Four network configurations are evaluated, varying sourcing geography, port selection, and warehouse allocation. Distribution-stage emissions are minimized through LP optimization, while upstream emissions are incorporated as exogenous LCA parameters. Sourcing geography, distribution-network design, and protein density significantly affect GWP per functional unit, with domestic sourcing yielding the lowest impacts for all products and network configurations. Tofu under the baseline configuration exhibits the highest GWP (1.2236 kg CO₂e/100 g protein), whereas TVP with domestic sourcing exhibits the lowest (0.1146 kg CO₂e/100 g protein), representing a 90.64% difference. The integrated approach provides a decision-support framework for lower-emission sourcing and distribution in emerging-economy food supply chains. Full article

To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation. Full article

Maritime transport is a major component of global supply chains, but reducing its atmospheric emissions remains essential to improving the environmental sustainability of shipping. This study analyzes onboard emission data reported for the MV Ilshin Green Iris under real-world operating conditions to assess how fuel selection affects the direct-emission performance of a dual-fuel marine propulsion system. The vessel is equipped with a MAN B&W 6G50ME-C9.5-GI engine employing high-pressure dual-fuel (HPDF) technology. A quantitative comparison between heavy fuel oil (HFO) and liquefied natural gas (LNG) was performed at 50% of the maximum continuous rating (MCR). At 50% MCR, LNG reduced CO₂ emissions by 27.0%, NOx emissions by 20.7%, and CO emissions by 18.2% relative to HFO, while PM showed an indicative reduction of approximately 69%; its precise magnitude remains uncertain because a complete PM uncertainty budget was unavailable. Over the 900 s measurement period, the estimated reduction in CO₂ mass was 154 kg. During LNG operation, the specific CH₄ emission at 50% MCR was approximately 0.6 g/kWh. Using a 100-year global warming potential of 29.8 for fossil CH₄, this corresponds to approximately 17.9 g CO₂-eq/kWh, equivalent to about 10.5% of the direct CO₂ reduction between HFO and LNG at this operating point. The results are representative of the analyzed stabilized operating point rather than of the vessel’s complete operational profile. The main contribution of this study is a structured matched-load analysis of HFO and LNG emissions from the same HPDF marine engine. The analysis combines measurement-derived specific emissions with energy-based mass estimates, methane-related limitations, data-quality considerations, and regulatory and sustainability implications. Because both fuels were evaluated in the same engine at the same 50% MCR operating point, the study provides a consistent basis for assessing fuel-related differences within the limits of the available dataset. Full article

The rapid transition toward electrified mobility and climate neutrality has prioritized the structural and environmental optimization of battery electric vehicle (BEV) subsystems. While vehicle lightweighting enhances operational efficiency, the production phase of structural enclosures and battery cells frequently introduces severe environmental and economic impacts and supply chain vulnerabilities. This study presents a comprehensive cradle-to-gate environmental life cycle assessment (LCA), life cycle costing (LCC), and semi-quantitative social assessment of alternative battery housing materials and battery cell architectures. To achieve a functionally accurate comparison, alternative materials, including a novel recyclable thermoplastic acrylic sheet molding compound (SMC), commercial thermoset SMCs, aluminum (AlMg₃), and stainless steel, are evaluated using an analytical stiffness- and strength-equivalent methodology across three real-world geometric demonstrators. Simultaneously, lithium iron phosphate (LFP) liquid electrolyte prismatic cells and solid-state polymer pouch cells are assessed. Material-level results indicate that, while aluminum minimizes the structural mass, primary aluminum manufacturing exhibits the highest global warming potential and processing costs. Conversely, Polytec SMC and Elium SMC achieve the lowest environmental impacts alongside competitive total production costs. At the cell level, prismatic LFP architectures display superior environmental performance compared to solid-state pouch cells, which suffer from energy-intensive processing and lower volumetric capacity normalization. Demonstrator-level aggregation reveals that the electrochemical cells heavily dominate the environmental and economic footprint of the complete assembly, with the housing accounting for less than 5% of the total global warming potential (GWP) and 1% of the total costs. The social assessment reveals moderate and comparable performance across all systems, with slight advantages for thermoplastic composite-based configurations in terms of circularity potential and innovation perception. Overall, the study highlights the critical importance of the cell architecture and manufacturing processes in determining battery system sustainability, while demonstrating the relevance of lightweight composite housings in reducing the structural mass with a minimal environmental penalty. Full article

The study addresses the design and development of a unified corporate information system for multimodal transport and logistics companies engaged in maritime and railway transportation. Analysis of the existing literature revealed the absence of a coherent methodological framework for the design of corporate information systems tailored to the specific operational characteristics of multimodal transport and logistics enterprises. To bridge this gap, a design methodology for corporate information system databases is proposed, intended for subsequent deployment in companies operating multimodal supply chains. The development of the unified corporate information system was guided by the principle of “total costs,” which requires that the decision-maker—when selecting transport modes, methods of transportation, carriers, routing, and auxiliary intermediaries (insurer, stevedore, bank, and customs broker)—address the problem as an integrated whole rather than optimizing individual components in isolation. The study encompasses information modeling of the business processes of multimodal transport and logistics companies, construction of an optimal model of the transport process for maritime and railway transportation using integrated computer automated manufacturing definition (IDEF) and structured analysis and design technique (SADT) modeling, and the design of a multilevel unified database structure for the coordination of different transport modes. A decision-making and support system has been developed for managing the operational activities of a multimodal transport and logistics company engaged in maritime and railway transportation. The proposed unified corporate information system enables the replacement of task resolution by local optimization criteria applied separately to each transport mode—such as freight cost and delivery time—with a single global optimization criterion for the multimodal supply chain. Full article

With the continued advancement of low-carbon campus transformation and the increasing penetration of renewable energy, campus integrated energy systems have become key infrastructure for green campus development. However, the highly random nature of student behavior causes dynamic fluctuations in electricity, heating, and cooling loads, creating major challenges for real-time supply-demand balance and economic system scheduling. To address this problem, this paper takes student behavior uncertainty as the core disturbance factor and proposes a flexible architecture-driven autonomous adaptation and multi-energy complementary optimization strategy. A closed-loop operation paradigm of signal–response–complementarity–regulation is established, in which dynamic electricity price signals, comfort-oriented guidance, and campus functional energy-zone division are combined to form a multi-level autonomous response chain. To improve solution efficiency, the electromagnetic wave propagation algorithm is further enhanced, and a Multi-Objective Electromagnetic Wave Propagation Algorithm (MEMWPA) is developed. Wave-impedance matching and energy-flux-density feedback mechanisms are introduced to strengthen convergence performance in complex multi-objective optimization problems. Comparative case studies show that the proposed strategy can effectively smooth the net load curve, reduce the campus peak load by 26.73%, and increase the load factor by 14.533 percentage points, thereby improving both operational flexibility and energy efficiency. Full article