Search Results (7,248)

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

Background: Long-acting monoclonal antibodies have become an important strategy for preventing respiratory syncytial virus (RSV) disease in infants. Nirsevimab is the first product for which substantial post-licensure implementation data are available, whereas real-world evidence on clesrovimab remains limited. Although nirsevimab has demonstrated high efficacy, its uptake varies considerably across countries, healthcare systems, delivery settings, and population subgroups. This World Association for Infectious Diseases and Immunological Disorders (WAidid) consensus document examines the policy, organizational, economic, and equity-related determinants that shape real-world implementation of long-acting monoclonal antibodies for infant RSV prevention. Methods: This study was conducted as a structured narrative review and WAidid expert consensus document. A structured literature search was performed in PubMed and Embase for English-language publications relevant to nirsevimab uptake and implementation, complemented by targeted review of surveillance reports, policy documents, and public health guidance from the ECDC, UKHSA, and CDC, as well as reference lists of selected publications. Eligible sources included observational and real-world implementation studies, systematic reviews and meta-analyses, economic evaluations, guidelines, policy statements, surveillance reports, and relevant narrative reviews. Evidence was synthesized qualitatively according to policy frameworks, financing and reimbursement, delivery pathways, demographic and socioeconomic determinants, and healthcare-system factors influencing uptake. No statistical software was used because no quantitative re-analysis or meta-analysis was performed. Results: Nirsevimab uptake was strongly influenced by national RSV prevention policies, particularly whether countries adopted universal infant monoclonal antibody programs, maternal RSV vaccination strategies, dual maternal–infant approaches, or targeted risk-based models. Universal, publicly funded programs integrated into neonatal care achieved the highest and most homogeneous coverage, especially when administration occurred before hospital discharge and was supported by registry-based recall systems for infants born outside the RSV season. In contrast, fragmented, outpatient-only, insurance-dependent, or partially reimbursed models were associated with lower, delayed, or more variable uptake. Additional determinants included product cost, reimbursement pathways, provider practices, caregiver awareness and health literacy, insurance status, income, race and ethnicity, geographic deprivation, and access to primary pediatric care. Most available evidence comes from high-income countries, limiting generalizability to low- and middle-income settings, where RSV burden is greatest and implementation constraints may differ. Conclusions: Successful implementation of long-acting monoclonal antibodies for infant RSV prevention requires more than regulatory approval and demonstrated efficacy. Equitable uptake depends on clear national recommendations, sustainable public financing, reliable product supply, integration into neonatal and primary pediatric care, proactive identification and recall of eligible infants, and targeted strategies to reduce socioeconomic and geographic disparities. Although many determinants identified in high-income settings are likely relevant globally, their feasibility, relative importance, and impact require dedicated evaluation in low- and middle-income countries. Full article

Mpox has emerged as a global public health concern, highlighting the limitations of traditional vaccinia-based vaccination strategies and the urgent need for precision vaccinology approaches. Advances in structural virology and immunoinformatics have enabled the identification of conserved immunodominant antigens from both mature virion and extracellular virion forms, supporting the development of multivalent antigen combinations capable of inducing broad neutralizing antibody (nAb) responses. Emerging delivery technologies including mRNA-lipid nanoparticles, viral vectors, and self-assembling protein nanoparticles offer rapid scalability, enhanced immunogenicity, and improved safety compared with conventional live-attenuated vaccines. Addressing antigenic evolution, vaccine supply limitations, and population-specific immune variability will be crucial for optimizing vaccine effectiveness. This review synthesizes current evidence on antigen design, vaccine delivery platforms, and immunological correlates of protection to outline a framework for next-generation mpox vaccines. Precision vaccinology therefore represents a transformative strategy for developing durable, clade-specific mpox vaccines and strengthening preparedness against future orthopoxvirus outbreaks worldwide. Full article

Low-frequency, irregular water waves with continuously changing propagation directions are difficult to harvest efficiently using conventional power generation devices. This work proposes a gyroscope-pendulum-coupled multilayer triboelectric nanogenerator (GP-TENG), in which a multi-axis gyroscope mechanism, an inertial pendulum, and a helical-structured power generation module are integrated inside a spherical floating body. The gyroscope joints enable the pendulum to respond to waves arriving from any horizontal direction, while the heave and tilting motions of the floating body jointly drive periodic contact and separation of the multilayer triboelectric materials. Motor-driven platform and water tank experiments were conducted to investigate the effects of the number of generating layers, excitation frequency, translational stroke, swing amplitude, and external resistance on the output performance. In the controlled translational tests, the maximum root-mean-square open-circuit voltage, short-circuit current, and transferred charge reached 98.6 V, 2.3 μA, and 242 nC, respectively, and a maximum output power of 16.3 μW was obtained at a load of 81 MΩ. In the water tank, the GP-TENG showed a stable response near 1.42 Hz, with maximum output power of 3.45 μW at a 60 MΩ load. The generator successfully charged the capacitor, lit up LEDs, and powered a commercial temperature and humidity sensor. These results indicate that the GP-TENG provides a compact and low-cost approach for omnidirectional low-frequency wave energy harvesting and a distributed power supply for low-power marine electronic devices. Full article

Hierarchical retail forecasting requires predictions that are both accurate and coherent across multiple planning levels, from total demand to individual product–store series. Because these forecasts guide inventory, replenishment, storage, and distribution decisions, improving their coherence and reliability can support more efficient resource use, reduce avoidable overstock and product waste, and limit the need for emergency logistics. This study investigates how global deep-learning architectures interact with post hoc reconciliation in point and probabilistic forecasting. Using an M5-derived hierarchical and grouped structure comprising 42,840 series, we compare three MLP-oriented models, MLP, N-BEATS, and N-HiTS, with five transformer-based models, Transformer, Temporal Fusion Transformer, Informer, PatchTST, and Autoformer. All models are evaluated under a common 28-day forecasting horizon, temporal partition, Optuna-based tuning protocol, and three complete seeded runs. Coherence is imposed using Bottom-Up reconciliation and four MinTrace variants, while probabilistic forecasts are generated through residual-block bootstrap reconciliation. Point and probabilistic performance are assessed level-wise and globally using MASE and scaled CRPS, respectively. The results show that the strongest transformer-based combination outperforms the strongest MLP-based combination at every hierarchy level. PatchTST combined with MinTrace-WLS-struct is particularly effective at aggregate and intermediate levels, achieving a Total-level MASE of 0.537 and sCRPS of 0.037. At the Product–Store level, Bottom-Up reconciliation becomes preferable, with the Transformer attaining the lowest MASE of 1.367 and sCRPS of 0.912. Because granular series dominate the hierarchy-wide average, the lowest overall MASE is obtained by TFT with Bottom-Up reconciliation (1.428), whereas the lowest overall sCRPS is shared by the Transformer and Informer with Bottom-Up reconciliation (0.813). These findings demonstrate that neither the forecasting architecture nor the reconciliation method should be selected independently of hierarchy depth and forecasting objective. Strategic and tactical levels benefit primarily from PatchTST with MinTrace reconciliation, whereas highly granular operational forecasting favors Bottom-Up reconciliation with transformer-based models. From a sustainability perspective, this level-aware framework provides a basis for aligning forecasting decisions with resource efficiency, waste reduction, service reliability, and greater resilience across the retail supply chain. Full article

Peru holds a prominent position in international fresh asparagus trade, with a strong export profile and a well-established presence in global markets. Nevertheless, sustaining this position requires diversification toward a more resilient and sustainable portfolio of destination markets. This study assessed the global competitive sustainability of Peru’s asparagus agro-export industry during 2010–2024. Official data from the World Bank, Veritrade, CEPII, and the Peruvian Ministry of Foreign Trade and Tourism (MINCETUR) were analyzed using a quantitative longitudinal single-case study design with descriptive and explanatory components. The results show that the Herfindahl–Hirschman Index (HHI) for Peruvian asparagus exporters remained low, indicating limited firm-level concentration and a relatively diversified supply structure. Thus, Peruvian asparagus exports did not depend on a single dominant firm but were distributed among multiple exporters. In contrast, the HHI for destination markets revealed high geographic concentration of demand. Regarding competitiveness, Peru maintained a strong net-export position, with trade competitiveness index values close to 1. The Revealed Symmetric Comparative Advantage (RSCA) index showed favorable performance in markets such as the United States, Spain, The Netherlands, and the United Kingdom, although this advantage had not yet reached full structural stability. The gravity model, estimated using EGLS with Panel-Corrected Standard Errors (PCSE), identified destination-country economic size as the most important determinant of Peruvian asparagus exports. Geographic distance constrained exports, whereas trade agreements did not show a consistent statistical effect. Potential expansion opportunities were identified in China, Australia, Norway, Ecuador, Sweden, Austria, Russia, Poland, New Zealand, and Romania. Consequently, the competitive sustainability of Peruvian asparagus depends not only on preserving export leadership but also on reducing destination-market concentration, improving logistical efficiency, expanding production capacity, and directing trade policy toward markets with favorable economic fundamentals. 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

This study reassesses whether China’s 2018 Supply Chain Innovation and Application Pilot Policy changed corporate green innovation. The policy designated both 55 pilot cities and 266 pilot enterprises. To resolve ambiguity in treatment assignment, firms headquartered in pilot cities constitute the primary treatment group, while official pilot-enterprise status is analyzed separately. The updated panel contains 33,473 firm-year observations for 4265 A-share listed firms from 2011 to 2023; the main specification links covariates at year t to patent applications at t + 1, so outcomes extend through 2024. Firm and year fixed effects are included, and inference is clustered by city in the pilot-city design. Pilot-city exposure is associated with a 0.050 increase in log(1 + green invention patents) (p = 0.037), equivalent to a 5.16% change in one plus patent counts, or approximately 0.271 additional patents at the post-policy control mean. The corresponding pilot-city coefficient for utility model patents is −0.041 (p = 0.060). A joint event-study test does not reject equal pre-policy trends (p = 0.653), although the invention effect attenuates in the latest outcome cohort. Official pilot-enterprise exposure is associated with positive coefficients for both patent types. Robustness is mixed: the pilot-city invention result is directionally consistent under negative-binomial estimation and entropy balancing, but is not significant under PPML, industry-by-year fixed effects, or propensity-score matching. Exploratory channel tests do not support talent structure, lagged technology novelty, or information transparency as candidate pathways. Pilot-city exposure is associated with a higher share of cited patents but not with significantly lower environmental protection costs. The evidence therefore supports a narrow conclusion: the pilot-city estimates are consistent with a modest reallocation toward invention-oriented and more frequently cited green innovation, but the average causal magnitude and causal channels remain uncertain. Full article

To investigate the development characteristics of winding interturn insulation partial discharge in a full-scale converter transformer, an interturn insulation defect specimen was installed inside a ±400 kV full-scale converter transformer. A partial-discharge test was conducted under stepwise alternating-current (AC) voltage, while pulse-current, high-frequency, ultra-high-frequency, ultrasonic, sound-pressure, and vibration signals were acquired synchronously. To reduce the subjectivity of discharge-stage classification, a dimensionless discharge-development index was constructed by integrating the 95th-percentile apparent charge, discharge pulse count, and phase occupancy, and the stage-transition points were identified using piecewise-linear change-point analysis. Two change points at approximately 1.9 and 4.3 min divided the discharge process into the inception, development, and severe stages. The apparent charge increased from approximately 1.5 × 10² pC in the inception stage to the order of 10³ pC in the development stage, and then rose sharply to approximately 1.6 × 10⁵ pC in the severe stage. Meanwhile, the discharge activity changed from an intermittent low-intensity state to a continuous high-intensity state. After the test, insulation-paper ablation and carbonization, conductor exposure, and a continuous breakdown channel were observed in the defect region. These post-test observations confirm severe final damage to the interturn insulation, although the time sequence of the individual damage features could not be determined from the final morphology alone. Under the present sensor arrangement, the HF channel provided the earliest identifiable response at approximately 1.9 min, whereas the UHF and internal ultrasonic channels supplied complementary evidence during subsequent discharge development. The external ultrasonic, sound-pressure, and vibration responses were more strongly affected by propagation paths, structural coupling, sensor location, and background disturbance and were therefore treated as supplementary indicators. These findings support a staged multisensor interpretation strategy for interturn partial discharge in a full-scale converter transformer rather than a universal ranking of sensor performance. Full article

Water scarcity threatens global stability, with demand set to surge 20–30% by 2050, pushing withdrawals from 4600 km³ yr⁻¹ today to 5500–6000 km³ yr⁻¹ under rising demographic and climatic pressures. This study presents a sequentially coupled econometric–hydrological–reduced-form economic framework that couples water supply dynamics with demand forecasting and macroeconomic impact assessment. Agriculture dominates current withdrawals at 70% (FAO AQUASTAT), followed by industry (20%) and domestic use (10%). Monte Carlo simulations (n = 1000) identify critical regional hotspots: Asia (stress ratio = 1.06), the Middle East (1.18), and Africa (0.99). The reduced-form economic module uses a target-calibrated scarcity elasticity (ε = 0.1865) applied against a fixed economic reference threshold (4600 km³ yr⁻¹). This internally calibrated parameter yields a first-order GDP loss estimate of approximately $16.0 trillion under the high-demand (+30%) 2050 scenario (6000 km³ yr⁻¹ demand), equivalent to 5.5% of projected 2050 global GDP ($290 trillion, PwC 2017 baseline). The resulting magnitude is broadly consistent with the order of GDP impacts discussed by OECD (2012) and GCEW (2024), although neither publication reports this specific elasticity value. This is not an independently predicted outcome; it is a calibrated scenario estimate produced by a reduced-form damage function designed to reproduce first-order magnitudes consistent with published structural model results. Mitigation strategies including efficiency improvements, pricing reforms, and AI-driven allocation can reduce demand by up to 40%, which within the model’s mathematical structure reduces the calibrated economic loss to zero. Sectoral water distribution is addressed through continuous linear programming with proportional rationing. This framework advances transparent, reproducible scenario-based understanding and informs policy decisions aimed at mitigating future water scarcity challenges globally, while explicitly acknowledging limitations relative to full structural CGE models and empirically estimated panel econometric models. 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

Cost control in engineering, procurement, and construction (EPC) public works is shaped by interacting drivers, nonlinear feedback, and qualitative judgments. Existing studies usually apply the three relevant method families separately: DEMATEL-ISM maps causal structure but does not propagate hesitation-aware expert judgments into cost trajectories; fuzzy systems represent uncertainty but commonly lack a verified causal hierarchy; and system dynamics (SDs) capture dynamic accumulation but often rely on crisp inputs. The resulting absence of a traceable causal screening to uncertainty to dynamic cost link is the specific gap addressed in this study. We therefore develop a transparent three-stage pipeline combining the Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL-ISM) method, triangular intuitionistic fuzzy reasoning (TIFR), and SDs. DEMATEL-ISM identifies the causal hierarchy; TIFR represents membership, non-membership, and hesitation in design complexity and human–technology synergy judgments; and SDs evaluate stage-specific cost trajectories. Recalculation from the supplied 17 × 17 direct influence matrix produced a six-level hierarchy in which senior management decision-making capability and the level of integration occupy the two deepest driving levels. For the Urumqi Civic Center case, the baseline terminal cost absolute percentage error was 0.492%. A coordinated intervention scenario shifted the simulated terminal cost by CNY 12.1243 million (6.1%) relative to the baseline; this is a model-based scenario difference, not an observed project saving. Integration had the largest simulated effects on design and transportation costs, whereas senior management decision-making capability had the largest effects on procurement and construction costs. Security cost curves showed a complementary pattern between managerial capability and workers’ professional competence, but no statistical interaction effect is claimed. The framework is intended for within-case scenario comparison and intervention prioritization; multi-project and time-series validation remains necessary. Full article

Developers increasingly reuse third-party Low-Rank Adaptation (LoRA) adapters for code-generation models without visibility into how they were trained, creating a supply-chain risk: a maliciously trained adapter can behave normally on clean inputs while activating attacker-controlled functionality when a specific trigger is present. This study makes a mechanistic contribution to that risk: we show that trigger modality, not just contamination rate, determines a qualitatively different backdoor learning regime. We trained 61 poisoned variants of CodeGen-350M-mono on the CodeSearchNet dataset, injecting eight backdoor triggers spanning two categories: three semantic triggers based on natural-language code comments and five syntactic triggers based on structural code transformations derived from the CodePoisoner framework. Across attack success rate measurement, cross-trigger confusion analysis, mechanistic circuit tracing, layer-restoration defense evaluation, and semantic generalization testing, we find that semantic triggers produce associative binding: a 91% attack success rate, a Trigger Specificity Index (TSI) of 268×, distinct per-trigger circuits concentrated in attention layers, and a requirement to restore 10 parameter groups for removal. Syntactic triggers instead produce distributional confusion: a 31% attack success rate, a TSI of only 1.25× (1.45× once a shared-payload confound in the confusion-matrix design is corrected for), diffuse circuits spread across (Multi-Layer Perceptron) MLP layers, and collapse with just 5 restored parameter groups. Cross-payload testing on single-trigger models confirms this: structural triggers fire on triggers never seen during training at rates of 42 to 55%, showing that the model learns a general association between code abnormality and payload generation rather than a specific trigger–payload mapping. Both regimes preserve clean code-generation quality across all contamination rates, so a downloaded backdoored adapter is behaviorally indistinguishable from a clean one under standard benchmarks. These results argue against a one-size-fits-all approach to adapter auditing: detection and removal strategies calibrated to one trigger modality can fail outright against the other, and we outline the conditions under which each applies. 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

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