Search Results (39)

(1) Background. Food sovereignty and local sustainability are ensured by large agro-industrial holdings and small-scale farms; this synergy forms a complementary model of the agrifood system. Maintaining this model’s balance requires the creation of a unified digital ecosystem that integrates all suppliers and consumers into production chains, thereby eliminating unnecessary intermediaries. (2) Methods. This study employs a comprehensive methodological framework, including systems analysis and mathematical modeling, to develop service algorithms. Object-oriented design and software engineering methods facilitated the development and implementation of a service-oriented architecture for the digital system. (3) Results. The study presents a multi-tier architecture featuring an integration bus based on a service-oriented approach. To implement direct supply-and-demand coupling strategies, the system integrates both internal services (microeconomic indicators) and external services (macroeconomic indicators). Additionally, a recommender system based on neural networks and mathematical models was developed to personalize consumer requests and manage product sales. (4) Conclusions. The software solution is consistent with the AgTech 4.0 concept and enables the creation of a seamless environment for interstate trade. The implementation of the system enhances the transparency of the “product footprint”, facilitates the redistribution of surpluses, and, consequently, contributes to price stabilization. Full article

Mandatory Environmental, Social, and Governance (ESG) disclosure requirements—anchored in Corporate Sustainability Reporting Directive (CSRD), International Sustainability Standards Board (ISSB), and Task Force on Climate-related Financial Disclosures (TCFD)—have placed unprecedented demands on supply chain data quality and auditability. Blockchain technology, combining immutability, decentralised governance, and smart contract automation, has emerged as a candidate infrastructure for addressing verification deficits across multi-tier supply chains. To our knowledge, no prior systematic review has simultaneously examined the blockchain specifically for formal ESG transparency and sustainability reporting across all three ESG dimensions within the post-CSRD mandatory reporting landscape. This study presents a systematic literature review (PRISMA 2020). Scopus and Web of Science searches identified 1166 records (2016–2026); after deduplication, 761 unique records were screened, and after blinded screening (κ = 0.84), 96 studies were included. Five blockchain application typologies are identified (T1–T5), spanning provenance tracing, smart contract compliance, carbon accounting, supplier data aggregation, and ESG disclosure systems. A structural asymmetry is identified: governance is addressed in 96% of studies (77.1% under the strictest G-CONFIRMED recoding; 95.8% under the moderate interpretation, including borderline cases), the environmental pillar in 49%, and the social dimension in 21%, explained through institutional theory, with significant implications for CSRD and Corporate Sustainability Due Diligence Directive (CSDDD). Key barriers include scalability, interoperability, and the blockchain–GDPR (General Data Protection Regulation) tension. Three principal contributions are made: (i) a systematic typology of blockchain for ESG transparency; (ii) institutional-theory explanation of ESG dimension asymmetry; and (iii) a research agenda centred on AI–blockchain convergence and post-CSRD empirical studies. The review is limited to English-language peer-reviewed literature. Full article

Megaprojects involve complex, multi-tier supply chains characterised by high interdependence, diverse stakeholders, and significant uncertainty. Despite their strategic and economic importance, many megaprojects continue to experience persistent cost overruns and schedule delays, suggesting that performance challenges stem largely from difficulties in managing supply chain complexity rather than technical issues alone. This study adopts a systematic literature review of peer-reviewed publications from 2015 to 2025, sourced from Scopus and Web of Science. Using PRISMA-guided screening and eligibility procedures, 94 relevant articles were analysed to examine the drivers of supply chain complexity, their performance implications, and resilience strategies applicable to megaproject contexts. The review identifies various supply chain complexity drivers that intensify coordination challenges, reduce supply chain visibility, and increase disruption risks, contributing to inefficiencies, delays, and cost escalation. Proactive and reactive resilience strategies, such as multi-sourcing, collaboration, flexibility, redundancy, and contingency planning, are found to strengthen adaptive capacity and recovery. The study concludes that integrating complexity management with resilience-oriented practices provides a critical pathway for improving megaproject supply chain performance and offers a conceptual foundation for future empirical validation. Full article

Supply chain management (SCM) involves complex coordination among multiple actors under demand uncertainty. However, most existing studies focus on simplified network structures that fail to capture all relevant dimensions of real-world supply chains or assume deterministic demand. This study proposes a comprehensive stochastic bi-level optimization framework for a multi-factory, multi-retailer, multi-customer, and multi-product supply chain network. The model captures the hierarchical interaction between decision-makers, where the production facility owner acts as the leader and the retailer as the follower, and jointly optimizes profit across both levels. To efficiently solve the resulting bi-level problem, two tailored metaheuristic solution approaches—a two-tier genetic algorithm (TT-GA) and a two-tier particle swarm optimization (TT-PSO)—are developed. Computational experiments across multiple scenarios demonstrate that TT-PSO outperforms TT-GA in Scenarios 1 and 2, achieving overall profit improvements of 6.46% and 0.76%, respectively, while TT-GA yields superior performance in Scenario 3 with a 2.80% profit improvement. The proposed framework provides decision-makers with a robust and practical tool for improving profitability and operational efficiency in complex, uncertain supply chain environments. Full article

This paper investigates the problem of contract coordination in a two-tier multi-unit auction supply chain consisting of a seller and an auction house. We theoretically show that the conventional commission-based mechanism distorts the transmission of demand information from the demand side to the supply side, thereby preventing effective supply chain coordination. In contrast, guaranteed auction contracts can achieve coordination under both cooperative and non-cooperative game frameworks. Under the cooperative game setting, profits are allocated according to a Nash bargaining solution, in which each party receives its disagreement payoff and a bargaining-power-weighted share of the surplus, with risks and returns being allocated symmetrically. Under the non-cooperative game setting, the supply chain leader can appropriate a larger share of the total profit while bearing relatively lower risk. These results indicate that, as the supply chain leader, the auction house can select different cooperation modes under guaranteed auction contracts according to its bargaining position, but profit allocation should be benchmarked against the cooperative game outcome in order to enhance the long-term competitiveness and stability of the supply chain. Full article

There is diminished transparency, fragmented information exchange, and lack of trust among geographically dispersed stakeholders, which increasingly challenge global supply chains. The classic centralized systems of supply chain management are not always capable of being able to offer real-time traceability and data integrity which is dependable and effective in contract enforcement. The proposed study is a blockchain-based smart contract design that is focused on ensuring increased transparency, traceability and trust in global supply chain management. The suggested framework will combine automated smart contracts, cryptographic provenance tracking, permissioned blockchain consensus, and a decentralized trust score evaluation mechanism to overcome some of the major operation and governance challenges. A simulated assessment with a multi-tier global supply chain setting of 15 blockchain nodes and 12,000 transactions was performed through experimentation. The findings show that the proposed system attained an average transaction delay of 210 ms, which is very low compared to centralized systems (520 ms), with throughput being raised to 120 transactions per minute. End-to-end traceability performance also improved significantly, with a reduction in trace-back time to 8 s compared with 95s this represents a 100% tampering detection rate. The consensus mechanism ensured that the ledger integrity failed only at a rate of less than 1.1%, even when more than 30% of nodes were faulty. Risk-wise, the trust evaluation algorithm dynamically enhanced reliable supplier scores up to 12%, which facilitated the selection of reliable partners. On the whole, the results prove that smart contracts based on blockchains can drastically enhance the efficiency of operations, data integrity, and confidence in global supply chains, with the platform capable of providing a resilient and scalable backbone for the future supply chain management model. Full article

Sustainable Supply Chain Management (SSCM) increasingly integrates environmental, social, and governance (ESG) criteria to address sustainability risks and performance across multi-tier supply networks. However, it remains unclear whether ESG practices directly enhance supply chain outcomes or primarily operate through the development of higher-order management capabilities. This study examines how ESG practices influence supply chain resilience, operational performance, and sustainability performance in the Mexican aerospace industry, emphasizing the mediating role of Sustainable Supply Chain Management Capability (SSCM Capability). Data were collected through a structured survey administered at the Mexico Aerospace Fair (FAMEX) in April 2025, yielding 217 valid responses from Tier 1–3 aerospace firms. The research adopts a hypothesis-driven design integrating Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA) to combine sufficiency- and necessity-based perspectives. The findings show that ESG practices primarily create value by enabling SSCM Capability, which is central to improving all performance dimensions. While ESG practices directly contribute to operational and sustainability performance, resilience improvements depend mainly on capability development. NCA results further indicate that ESG practices are foundational to SSCM Capability and high performance, whereas SSCM Capability constitutes a necessary condition for resilience. These findings underscore the critical role of capability building in translating ESG commitments into robust supply chain performance within compliance-intensive aerospace ecosystems in emerging economies. Full article

Modern supply chains are increasingly expected to meet ambitious sustainability targets, yet they often suffer from limited visibility into upstream relationships, environmental risks, and ethical sourcing practices. This paper presents an artificial intelligence (AI)-based approach for supporting sustainability-oriented decision-making in supply chains through knowledge graph completion and link prediction. We construct a multi-relational supply chain knowledge graph that captures heterogeneous entities and relationships, including suppliers, products, certifications, and locations, and apply graph neural networks to infer missing links and sustainability-related attributes. By enabling reasoning over incomplete and sparse data, the proposed approach supports feasibility-oriented decisions, such as identifying alternative supplier relationships and assessing sustainability alignment across multi-tier networks. Building on recent advances in knowledge graph reasoning and heterogeneous graph learning, the framework integrates relational structure with inductive learning to provide interpretable recommendations under uncertainty. The approach is evaluated on two real-world supply chain datasets, demonstrating its applicability in complex, data-sparse settings. The results indicate that graph-based AI can provide a practical foundation for transparent and sustainability-aware supply chain decision support. Full article

Modern supply chains operate as highly interconnected networks characterized by decentralization, data silos, and increasing sustainability constraints. Although Graph Neural Networks (GNNs) have demonstrated strong capability in modeling relational dependencies in such systems, their deployment is often restricted by limited inter-organizational data sharing. Federated learning (FL) enables collaborative model training without exposing proprietary data; however, existing federated approaches rarely integrate graph structure and sustainability objectives within a unified framework. This study proposes a Sustainability-Aware Federated Graph Attention Network (FedGAT) for decentralized supply chain process modeling. The framework combines Graph Attention Networks with federated optimization and introduces an emission-weighted attention modulation mechanism that embeds environmental considerations directly into the message-passing process. A multi-tier synthetic supply chain benchmark is constructed to evaluate the approach under realistic governance and data-locality constraints. Experiments are conducted across multiple random seeds, graph scales (up to 500 nodes), and client partition settings. Results show that while centralized graph learning achieves the lowest prediction error, the proposed sustainability-aware federated model maintains statistically indistinguishable predictive performance compared to standard federated baselines (paired sign test p = 1.000), while systematically reducing attention allocated to high-emission transport links. A structured label sensitivity analysis confirms that performance gains are not attributable to circular label construction. Furthermore, a λ-ablation study demonstrates a smooth and controllable trade-off between predictive accuracy and sustainability alignment through a single governance parameter. These findings establish the feasibility of privacy-preserving, sustainability-modulated graph learning for decentralized supply chain analytics and provides a principled foundation for environmentally aligned AI deployment in multi-enterprise networks. Full article

Aeroponics has emerged as a key technology for sustainable and resource-efficient food production, particularly under intensifying constraints on water availability, land use, and greenhouse gas (GHG) emissions. This review synthesizes recent advances in water–energy–nutrient integration, highlighting operational parameters—humidity (50–80%), temperature (18–25 °C), nutrient solution pH (5.5–6.5), and electrical conductivity (1.5–2.5 mS cm⁻¹)—that critically influence system performance. Evidence indicates that closed-loop water recirculation and AI-assisted monitoring for environmental control and nutrient dosing can stabilize system dynamics and reduce water consumption by more than 90%. Reported yield improvements ranged from 45% to 75% compared with conventional soil-based cultivation. Moreover, systems powered by renewable energy demonstrated up to an 80% reduction in GHG emissions. Life-cycle assessment studies further suggest that aeroponics, coupled with low-carbon electricity in controlled-environment agriculture (CEA), can outperform traditional agricultural supply chains in climate and resource efficiency metrics. Additional technological innovations—including multi-tier vertical rack architectures, optimized misting intervals, and micronutrient-enriched fertigation formulations containing N, P, Ca, Mg, and K—were found to enhance spatial productivity and crop quality. Overall, aeroponics represents a promising pathway toward net-zero, high-performance agricultural systems. Full article

Critical mineral supply chains underpin electric mobility, power electronics, clean hydrogen, and advanced manufacturing. Drawing on the resource-based view (RBV), the relational view, and dynamic capabilities, we conceptualize advantage not as ownership of ore bodies but as orchestration of multi-tier resource systems: upstream access, midstream processing know-how, standards and permits, and durable inter-organizational ties. In a world of high concentration at key stages (refining, separation, engineered materials), full “decoupling” is economically costly and technologically constraining. We argue for structured cooperation among the United States, European Union, China, and other producers and consumers, combined with selective domestic capability building for bona fide security needs. Methodologically, we conduct a structured conceptual synthesis integrating RBV, relational view, dynamic capabilities, and network-of-network research, combined with a structured comparative policy analysis of U.S./EU/Chinese instruments anchored in official documents. We operationalize the argument via technology–material dependency maps that identify midstream bottlenecks and the policy/standard levers most likely to expand qualified, compliant capacity. Full article

Pleurotus ostreatus is valued for its nutritional, medicinal, economic, and ecological benefits and is widely used in the food, pharmaceutical, and environmental protection industries. Pleurotus ostreatus, as a highly perishable edible fungus, faces significant challenges in supply chain quality control and food safety due to its short shelf life. As consumer demand for food freshness and full traceability increases, there is an urgent need to establish a reliable traceability system that enables real-time monitoring, spoilage prevention, and quality assurance. This study focuses on the Pleurotus ostreatus supply chain and designs and implements a multi-role flexible traceability system that integrates blockchain and the Internet of Things. The system collects key production and storage environment parameters in real time through sensor networks and enhances data accuracy and robustness using an improved adaptive weighted fusion algorithm, enabling precise monitoring of the growth environment and quality risks. The system adopts a “link-chain” mapping mechanism for multi-chain storage and dynamic reorganization of business processes. It incorporates attribute-based encryption strategies and smart contracts to support tiered data access and secure sharing among multiple parties. Key information is stored on the blockchain to prevent tampering, while auxiliary data is stored in off-chain databases and the Interplanetary File System to ensure efficient and verifiable data queries. Deployed at Shandong Qihe Ecological Agriculture Co., Ltd., No. 517, Xilou Village, Kunlun Town, Zichuan District, 255000, Zibo City, Shandong Province, China, the system covers 12 cultivation units and 60 sensor nodes, recording over 50,000 traceable data points. Experimental results demonstrate that the system outperforms baseline methods in query latency, data consistency, and environmental monitoring accuracy. The improved fusion algorithm reduced the total variance of environmental data by 20%. In practical application, the system reduced the spoilage rate of Pleurotus ostreatus by approximately 12.3% and increased the quality inspection pass rate by approximately 15.4%, significantly enhancing the supply chain’s quality control and food safety capabilities. The results show that the framework is feasible and scalable in terms of information credibility and operational efficiency and significantly improves food quality and safety monitoring throughout the production, storage, and distribution of Pleurotus ostreatus. This study provides a viable technological path for spoilage prevention, quality tracking, and digital food safety supervision, offering valuable insights for both food science research and practical applications. Full article

Environmental management systems (EMSs), such as ISO 14001, are commonplace across the architecture, engineering, construction, operations, and management (AECOM) sectors of advanced economies. However, their uptake remains limited across emerging markets and developing economies. This study explores stakeholders’ perceptions of the benefits and barriers to implementing EMSs within the AECOM sectors of Malaysia. Guided by a positivist stance, the study takes a quantitative approach using an online questionnaire to gather the opinions of AECOM professionals. The findings reveal that participants believe the most significant benefits of implementing EMSs in Malaysia are to improve corporate image and contribute to the environmental standards of the sector, whereas the most significant barriers to implementing EMSs are lack of client support and the difficulty in coordinating environmental performance among multi-tier subcontractors. Based on the evidence collected, the study recommends encouragement by the government of Malaysia to drive forward environmental management and further research into the reasons for the lack of reported support for ISO 14001 within the supply chain. Full article

This study examines green investment and emission reduction strategies in a two-tier supply chain under dual-carbon regulation that combines a carbon tax with a cap-and-trade mechanism. A multi-stage dynamic game model is developed, in which the manufacturer reduces emissions through recycling efforts and investments in green technology. We compare optimal decisions under centralized, decentralized, and coordinated structures, and propose an enhanced bilateral cost-sharing contract to improve collaboration. Numerical experiments validate the theoretical results, and sensitivity analyses provide further insights. The results show that while both carbon tax and permit trading increase emission reduction, the carbon tax may lower manufacturer profit, underscoring the need for coordinated policy design. Benchmarking proves more effective than grandfathering in stimulating green investment, particularly under high carbon prices and strong consumer environmental preferences. The proposed contract alleviates free riding, enhances overall supply chain profitability, and improves emission reduction performance. Policy implications highlight the importance of prioritizing benchmark allocation, promoting consumer environmental awareness, and encouraging firms to integrate carbon asset management with technological innovation. This research provides both theoretical and practical insights for designing effective carbon policies and collaborative mechanisms in green supply chains. Full article

Global Value Chains (GVCs) have driven the worldwide dispersion of manufacturing but remain highly vulnerable to macro-level shocks, including financial crises, geopolitical tensions, and the COVID-19 pandemic. These shocks expose manufacturing supply chains (MSCs) to systemic risks, but limited research has explored how GVC reconfiguration mediates their impact on manufacturing supply chain resilience (MSCR). To address this gap, this study conducts an enhanced bibliometric–systematic literature review (B-SLR) of 120 peer-reviewed articles. The findings reveal that macro-level shocks induce GVC reconfigurations along geographical, value, and governance dimensions, which in turn trigger MSCR through node- and link-level mechanisms. MSCR represents a manufacturer-centered capability that enables MSCs to preserve, realign, and enhance value amid shocks. Building on these insights, this research proposes a multi-tier strategy encompassing firm-level practices, inter-firm collaborations, and policy interventions. This study outlines three key contributions. First, at the theoretical level, it embeds MSCR within a GVC framework, clarifying how GVC reconfiguration mediates SCR under macro-level shocks. Second, at the methodological level, it ensures corpus completeness through snowballing and refines bibliometric mapping with multi-dimensional visualization. Third, at the managerial level, it provides actionable guidance for firms, industry alliances, and policymakers to align MSCR strategies with the dynamics of global production networks. Full article