Search Results (11,157)

Traceability systems are increasingly central to ensure food safety, quality, biosecurity, and sustainability in agrifood supply chains. Despite advances in digital technologies, adoption and effective implementation remain uneven, with many producers still relying on paper-based systems. This study examines the motivations and conditions that enable or constrain the participation in traceability systems by Australian red meat and honey producers using the Digital Maturity Framework (DMF) as a diagnostic lens. Drawing on seven focus groups and five individual interviews involving a total of 73 producers and supply chain stakeholders from both sectors, the study investigates how value perceptions, technology and infrastructure, data analytics and management, capability, and data governance, influence producers’ engagement with traceability systems. Our findings indicate that while regulatory pressure and market opportunities incentivise adoption, several challenges persist, including high costs, limited digital skills, data sharing concerns, and sector-specific constraints. The red meat sector demonstrates higher digital maturity, driven largely by compliance mandates and an established regulatory system. In contrast, the honey bee sector exhibits more fragmented traceability adoption, challenged by the predominance of small-scale producers and limited trust in data sharing mechanisms. The comparison between two sectors reveals the influence of sectoral context. In particular, the regulatory frameworks and supply chain coordination play a relevant role in the adoption of traceability technologies. Overall, this research reveals the need for tailored policy and industry support, including regulatory harmonisation, improved data interoperability, digital infrastructure, and capacity-building initiatives to enable more consistent and broader traceability implementation across agrifood systems. Full article

Against the background of climate uncertainty, market volatility, and evolving regulatory environments, firms embedded in agricultural value chains face increasing pressure to maintain sustainable growth. This study examines China’s A-share-listed Traditional Chinese Medicine (TCM) firms to explore how internal organizational factors and external institutional conditions jointly shape firm-level sustainable growth capability. This setting is characterized by strong ecological dependence, strict quality regulation, deep policy embeddedness, and supply-chain sensitivity. Drawing on the resource-based view, dynamic capability theory, contingency theory, and the institutional environment perspective, this study applies fuzzy-set qualitative comparative analysis (fsQCA) to 2023 cross-sectional data from 59 A-share-listed TCM firms. The results show that no single condition constitutes a necessary condition for high sustainable growth capability. Instead, high sustainable growth capability is mainly achieved through three configurational pathways: innovation-driven growth, policy-supported development, and market-responsive strategy. Low sustainable growth capability follows asymmetric pathways, mainly reflected in the mismatch between innovation capability and the institutional environment, and the coexistence of high financing constraints and low agility response. The findings indicate that sustainable growth capability is not the result of isolated factors, but a context-specific configurational outcome shaped by innovation, agility response, internationalization, equity governance, ESG performance, government support, marketization level, and financing conditions. This study provides a configurational explanation for growth research on agriculture-related firms and offers differentiated pathway implications for managers and policymakers. Full article

The increasing vulnerability of global food systems—exacerbated by the pandemic, climate change, and disruptions to international supply chains—has highlighted the importance of local food production for sustainability, food security, and rural resilience. At the same time, the LOHAS (Lifestyles of Health and Sustainability) value system is gaining prominence, shaping consumer demand for locally produced, environmentally responsible, and health-oriented products. While the existing literature predominantly addresses LOHAS consumers and local food systems as separate research domains, limited empirical attention has been paid to the value-based alignment between LOHAS principles and local food producers, particularly from a territorial and place-based perspective. This study seeks to address this gap by examining how LOHAS value dimensions are reflected in the self-identification and operational practices of local food producers, and by analyzing how such value alignment may be interpreted as contributing to the sustainability and resilience of territorially embedded rural production systems. From a systems perspective, LOHAS-related value alignment may be interpreted as a potential coordination mechanism that may contribute to strengthening feedback loops between producers and consumers and may enhance the adaptive capacity of short food supply chains as socio-ecological systems. The empirical analysis draws on an online survey conducted in the second quarter of 2024 among 73 local producers operating in Zala and Vas counties in Western Hungary. Factor analysis and cluster analysis were applied to identify underlying value structures and producer typologies. The results reveal two distinct producer clusters, one of which exhibits a strong alignment with LOHAS values. Producers within this cluster place particular emphasis on sustainability, environmental responsibility, health consciousness, and authenticity, alongside a pronounced commitment to local embeddedness and community-oriented practices. Overall, the findings demonstrate that LOHAS-related values are not confined to the consumer side but are increasingly embedded in territorially grounded local production models. This value alignment may contribute to strengthening short food supply chains rooted in specific geographical contexts, thereby contributing to the long-term socio-economic and environmental sustainability of rural regions. Full article

Background/Objectives: Silver’s ability to kill pathogenic bacteria is being widely researched in environment, consumer, and health-related applications. One topic of voluminous research is the antimicrobial properties of silver and silver in wound dressings. This research literature has been reviewed in articles using qualitative analyses, meta-analyses, systematic reviews, bibliometric analyses, and other grounded methods. We present a new strategy for the analysis of the population of articles on the subject based on an ontology of this topic. Methods: A search of the Scopus database for all peer-reviewed articles on silver in wound dressings yielded a population of 4711 relevant ones. The ontology is a logical deconstruction of the problem: “use of silver species on nanosupports deposited on a matrix with antimicrobial effectiveness assayed by methods to promote wound healing of chronic wounds as determined by recovery”. Each bolded term denotes a dimension of the ontology, and each dimension denotes a taxonomy of constituent elements. A Convolutional Neural Network (CNN) was trained using a manually mapped subset of articles. The CNN was then used to map the population of articles. Results: Out of the 4711 articles, 3079 dealt with silver and wound dressings; the others involved silver, but were not related to wound dressings and were not considered. Overall analysis shows that three classes of silver encompass the entire field: silver nanoparticles (AgNP) (78% of papers), inorganic silver-ion-containing species (7%) and silver associated with organic molecules (15%). AgNP papers have grown exponentially beginning in the early 2000s; there is no clear trend regarding inorganic silver-containing-species papers; whereas with the silver-organics species papers, there has been growth in the past decades, but now the number of publications is stabilizing. Research on the AgNPs has primarily focused on in vitro testing (54%), with very limited animal testing (17%) and human testing (3%). On the other hand, with silver-organics, animal (30%) and human testing (38%) are prominent. Inorganic silver ion species also have been human-tested extensively (43%). Thus, in clinical applications of silver wound dressings, AgNP lags considerably as compared to the other silver species, though academic research in AgNP is robust. Conclusions: From detailed temporal visualizations of the ontological mapping, the antecedents and consequences of silver in wound dressings are presented. This first ontological analysis is a novel way of visualizing an entire research field and the temporal characteristics of the various dimensions of the ontology provide information on the current state of research as well as where the field is headed. Full article

Driven by the rapid proliferation of generative artificial intelligence, the computing power industry is undergoing a paradigm shift from traditional linear supply chains toward complex, interdependent innovation ecosystems. This study investigates the evolutionary dynamics of the computing power ecosystem, specifically examining the strategic interplay between antitrust regulation and vertical integration. We construct a tripartite evolutionary game framework involving the government regulators, leading computing power incumbents, and downstream AI innovators. By deriving evolutionarily stable strategies, we analyze the underlying mechanisms of system transitions and employ numerical simulations to explore key parametric sensitivities. The theoretical analysis suggests that the evolution of the AI computing power innovation ecosystem manifests distinct stage-based progressions and threshold-driven bifurcation characteristics—potentially transitioning from an initial efficiency-based state of “natural monopoly and passive dependence” during the industry’s emergence, through transitionary states such as the “comfort zone trap” or “regulatory stalemate” during the expansion phase, and ultimately converging toward a mature configuration of “co-opetition and endogenous growth.” The model suggests that downstream AI firms may benefit from advancing vertical integration, achieving hardware–software co-optimization through self-developed domain-specific architectures, The analysis further implies that the leading computing power firm could strengthen its ecological niche by opening its underlying interfaces and software stacks to maintain its ecological niche as the industry cornerstone in integrated form. For the government, it is necessary to establish precise dynamic intervention and orderly exit mechanisms. Full article

The cosmetic industry represents a major sector of the global economy and is expected to significantly grow in the coming years. To enhance consumer acceptance and address increasing sustainability concerns, cosmetic companies are actively seeking innovative solutions to mitigate their environmental, economic, and social impacts. In accordance with this, several scientific studies focus on the development, scale-up, and life cycle assessment of sustainable cosmetic products, especially those derived from side streams in accordance with circular economy principles. Various reviews have addressed this topic; however, they typically cover one or two of these dimensions, providing only a partial perspective. In particular, existing studies mainly analyze the types of side streams used and the resulting products, often lacking a comprehensive framework that can effectively support the translation of these approaches into industrial-scale production. The aim of the present review is to address this gap by providing a comprehensive analysis of the maturity level of development, scale-up processes, and life cycle assessment of cosmetic products based on agro-industrial side streams. This analysis is intended to support companies in the transition towards more sustainable practices by reducing carbon footprint and limiting the intensive extraction of virgin raw materials. The different approaches and methodologies proposed for the development and scale-up of sustainable cosmetic products from agro-industrial side streams are also analyzed, considering whether life cycle assessment has been performed. Furthermore, the most suitable business models will be selected as innovative and sustainable value chains capable of generating economic benefits, fostering local development, and enhancing resource efficiency and supply security. Full article

This study presents an efficient and environmentally friendly route for synthesizing succinic acid derivatives via palladium-catalyzed oxidative dicarbonylation of ethylene, utilizing oxygen as the terminal oxidant. By systematically optimizing reaction parameters—including catalyst composition, solvent volume, gas ratio, temperature, and additives—the turnover number (TON) for dimethyl succinate was significantly enhanced to 10,325. This strategy not only demonstrates the potential of CO and ethylene as simple and abundant C1 and C2 building blocks but also highlights the viability of oxygen as a sustainable oxidant. The developed process offers a promising pathway toward the cost-effective and scalable production of biodegradable materials such as poly(butylene succinate) (PBS), with important implications for advancing green synthesis and enabling an autonomous supply chain in the biodegradable polymer industry. Full article

This study investigates the interaction between a manufacturer’s blockchain adoption strategy and a retailer’s demand information sharing strategy in a green supply chain. For four strategy combinations, we establish a multi-stage game-theoretical model of a green supply chain consisting of a single manufacturer and a single retailer. We first derive the optimal pricing, greenness, service level, and profits, followed by sensitivity and comparative analyses. Next, by examining how consumer price sensitivity and the unit adoption cost of blockchain technology interact, we identify equilibrium strategy combinations. Finally, we validate the relevant findings through numerical analysis. The results demonstrate that adopting blockchain can mitigate the double marginalization effect when consumer price sensitivity is moderate, and can enhance product greenness and service level when the adoption cost remains low. Interestingly, the manufacturer is inclined to adopt blockchain irrespective of the degree of consumer skepticism. Meanwhile, the implementation of blockchain may motivate the retailer to share information when price sensitivity falls within a moderate range. These findings present actionable guidance for green supply chains regarding blockchain and information-sharing strategies. Full article

Background: Supply chain management (SCM) research has expanded across the Middle East and North Africa (MENA), yet the field remains fragmented. Limited synthesis exists on how regional conditions shape research themes, theories, and methods. Methods: This study applies the PRISMA 2020 protocol to review SCM articles indexed in Scopus and Web of Science from January 2000 to March 2025. After screening and eligibility assessment, 512 peer-reviewed studies were retained. Bibliometric mapping and thematic coding were used to identify publication trends, research streams, theoretical lenses, and methodological patterns. Results: SCM research increased sharply after 2015, reflecting national diversification agendas, logistics reform, digitalization, and exposure to global supply chain disruptions. Three dominant streams were identified: resilience, sustainability, and digital transformation. Research output is concentrated in Saudi Arabia and the United Arab Emirates, while cross-country comparative studies remain scarce. Empirical studies rely mainly on cross-sectional surveys and SEM-based analysis, with limited longitudinal, qualitative, mixed-method, and comparative work across the region. Conclusions: The study develops an integrative SCM capability framework linking regional structural conditions, capability development, and supply chain outcomes. The findings support managers and policymakers seeking resilient, sustainable, and digitally enabled supply chains, and define clear future research priorities for the MENA region. Full article

Dairy foods—particularly cheeses produced from raw or minimally processed milk—remain vulnerable to hazards such as Listeria monocytogenes, where delayed laboratory confirmation can expand recalls, increase food waste, and delay outbreak containment. This study proposes a veterinary-aware digital traceability framework that embeds herd health data, milk-quality testing, and inspection outcomes directly into batch-level EPCIS event records. By representing veterinary public health controls as structured, machine-actionable traceability elements, the framework enables automatic logging of mandatory control points, systematic compliance verification, and rule-based risk state transitions within standard EPCIS infrastructures. Using regulation-consistent dairy simulations modeling delayed Listeria detection during maturation, we evaluate the operational impact of event-level causal traceability within the proposed architecture. Compared with conventional time-window recall strategies, provenance-based trace-forward queries reduced recall scope under the evaluated synthetic scenarios. Integrating structured veterinary controls into EPCIS-based traceability systems supports automated regulatory evidence generation and more targeted recall decisions, contributing to improved auditability and reduced food waste in dairy supply chains. Full article

Background: Rapid adoption of artificial intelligence (AI) in logistics enhances operational efficiency and firm performance; however, empirical evidence on its capability-driven impact remains limited, particularly in Saudi Arabia’s e-commerce sector. This study’s purpose is to examine the influence of AI on logistics firm performance through the mediation role of supply chain consistency and logistics capabilities. Methods: A quantitative study was conducted and data were collected using a convenience sampling technique from 275 employees working in the Saudi Arabian logistics firms. Partial Least Squares Structural Equation Modeling was used to perform data analysis. Results: The study findings indicated that AI usage has significant and positive influence on supply chain consistency (β = 0.290) and logistics capabilities (β = 0.303). Furthermore, supply chain consistency (β = 0.115) and logistics capabilities (β = 0.171) play mediating role between AI usage and firm performance. The research model exhibits substantial predictive capability, explaining 74.6% (R² = 0.746) of the variance in firm performance, while AI usage explains a smaller portion of the variance in supply chain consistency 8.4% (R² = 0.084) and logistics capabilities 9.2% (R² = 0.092). Conclusions: The findings demonstrate that AI-based logistics operations provide extensive support to streamline operations and reduce costs. Full article

Background: Healthcare inventory management is critical for ensuring timely access to supplies and reducing stockouts. As supply chains grow more complex, algorithms, AI, and analytics techniques have emerged as tools for forecasting, tracking, classification, and procurement. Yet empirical validation across diverse contexts remains inadequate, and existing reviews treat these approaches as separate streams rather than an integrated system. Methods: To evaluate these capabilities, a systematic review of 64 peer-reviewed articles published between 2011 and 2025 was conducted using a descriptive and content analysis approach on the use of Triple A (Analytics, AI, and Algorithms) techniques in inventory frameworks across various healthcare contexts, such as hospitals, pharmaceutical supply chains, and humanitarian supply chains. Results: Integrating multiple Triple A approaches consistently outperforms single-method strategies, particularly with RFID and IoT tools. Key findings often overlooked are: emergency procurement and classification, which remain neglected despite the highest patient safety stakes, and key procurement drivers—organizational conditions, supplier reliability, and team capacity. Data quality, interoperability, and cybersecurity further constrain generalizability. Conclusions: Bridging these gaps requires integrated Triple A approaches rather than single methods. Phased implementation, cloud-based platforms, and privacy-by-design offer practical pathways for building resilience under real-world constraints. Full article

Background. Ethanol distribution in the energy supply chain can be maximized by solving a Location Routing Problem (LRP). Manifold LRP (MLRP) expands on the classic domain assumptions of LRP to manifold surfaces, and it can be applied to profit maximization in ethanol supply chains. Methods. In this work, a hybrid MLRP (H-MLRP) is introduced as a new mixed integer nonlinear programming NP-hard problem assuming discrete facility allocation that requires a mix of truck and train transportation for ethanol distribution from the facility to its customers. Ethanol supply chain profit can be maximized by solving a stochastic nonlinear integer programming problem (SNLP) using ethanol raw materials, production quantity, logistics, railcar shipments, and transit times as the decision variables. H-MLRP and SNLP are combined as a two-stage optimization methodology to design a biofuel energy distribution system for making optimal decisions to maximize ethanol profit. Results. A case study demonstrated the effectiveness of the proposed method on the relocation of an ethanol producer that is currently located in North Dakota (ND) to Oklahoma (OK). In this case study, customer demand destinations and suppliers of raw materials are located in different regions of the United States. Conclusions. The results indicate a good use of the new model for decision-making. Full article

Situated within Saudi Arabia’s Vision 2030 transformation agenda, this study examines the performance implications of sustainable logistics practices (SLPs) and the mediating role of Management Information Systems (MIS). Although achieving a “double bottom line” is a central premise of sustainable supply chain management, its realization in state-driven emerging economies remains unclear. Drawing on the Natural Resource-Based View and Stakeholder Theory, a structural equation model is tested using survey data from 372 logistics and supply chain professionals in Saudi Arabia. The model assesses the effects of Green Transportation, Sustainable Packaging, and Sustainable Waste Management on Environmental Sustainability and Economic Performance. The results reveal a clear “Economic Performance paradox.” While all three practices significantly enhance Environmental Sustainability, only Sustainable Waste Management directly improves Economic Performance. Moreover, Green MIS significantly mediates the relationship between sustainable logistics practices and Environmental Sustainability but shows no direct or mediating effect on Economic Performance. This indicates a prevailing compliance-oriented use of MIS, where firms prioritize environmental monitoring and reporting over operational optimization. This study demonstrates that the double bottom line is not automatic, but contingent on practice type and institutional context. By providing firm-level evidence from Saudi Arabia, the study extends sustainable logistics and information systems research and offers contextually grounded insights for managers and policymakers. Full article

The global transition toward renewable energy and decarbonization is intrinsically linked to the management of critical materials. Rare Earth Elements (REEs) are no exception, as they play a strategic role at the center of climate goals. Therefore, this review provides a comprehensive assessment of the REE landscape, explicitly addressing the proposed Demand-Sustainability-Risk Nexus (DSR-Nexus), which integrates technological demand, environmental sustainability, and geopolitical supply risks. A systematic review based on PRISMA methodology was conducted to analyze scientific contributions published between 2015 and 2026, revealing a significant research imbalance. By 2025, while 87% of works focus on resource availability, production, and recycling, only 1.4% address the global supply chain and its geopolitical implications. Key findings highlight that China’s dominance in mining, processing, and refining capacities, accounting for 69.5%, 92%, and 94%, respectively, creates structural vulnerabilities for future environmental goals. In contrast, emerging producers such as Malaysia and the United States are expected to contribute 9% and 8% of refining capacity, respectively. Furthermore, this review discusses environmental trade-offs, including high energy intensity, water consumption, and radioactive byproducts. It also examines mitigation strategies, such as recycling, urban mining, and material substitution. Ultimately, achieving a resilient energy transition requires expanding supply, strengthening circular strategies, and international cooperation. Full article