Search Results (3,308)

This study examines how investment efficiency and risk jointly shape sustainable grain supply-chain upgrading. Using firm-level panel data for 25 listed grain supply-chain firms in China from 2015 to 2023, this study examines efficiency–risk structures and their heterogeneity across upstream, midstream, and downstream segments. A three-stage data envelopment analysis (DEA) is applied to measure investment efficiency while controlling for environmental heterogeneity and statistical noise, and a multidimensional investment risk index is constructed using principal component analysis (PCA), with an emphasis on sustainability metrics. The results reveal a clear supply-chain gradient: downstream firms exhibit the highest mean third-stage investment efficiency (crete = 0.633) and scale efficiency (scale = 0.634), midstream firms are intermediate (crete = 0.308; scale = 0.326), and upstream firms remain lowest (crete = 0.129; scale = 0.138). This ordering is also visible year by year, while risk profiles indicate higher exposure upstream and pronounced volatility midstream. Efficiency decomposition shows that upstream inefficiency is mainly driven by scale inefficiency rather than insufficient pure technical efficiency. Overall, efficiency–risk mismatch—manifested as persistent low scale efficiency and elevated risk exposure in upstream, volatility in midstream, and stability in downstream—constitutes a key micro-level barrier to long-term and resilient upgrading. The study thus offers policy-relevant insights for segment-specific interventions that align with sustainable agricultural development: facilitating land consolidation and integrated risk management for upstream scale inefficiency, promoting supply-chain finance and digital integration for midstream risk volatility, and leveraging downstream stability to drive coordinated upgrading and sustainable value creation through market-based incentives. Full article

Circular economy (CE) strategies in the agri-food sector hold strong potential for reducing waste, enhancing resource efficiency, and promoting sustainable value creation. However, early-stage assessment of innovative valorisation pathways remains challenging due to limited data availability and heterogeneous sustainability trade-offs. This study presents a multi-criteria evaluation tool designed to identify sustainability hotspots and support the preliminary screening of CE solutions based on easily obtainable information. The tool combines a structured literature review with expert-based scoring across environmental (ENV), economic (EC), and social (SOC) dimensions. Its applicability was demonstrated through the following three case studies: (i) reconstitution of cheese approaching expiration, (ii) extraction of polyphenols from grape-wine residues via subcritical water extraction, and (iii) biodegradable mulching film production from grape-wine pomace. Results show that the tool successfully differentiates sustainability performance across value chain areas Residue, Final Product, and Process (RES, FP, and PRO) and reveals critical gaps requiring further investigation. Scenario 3 achieved the higher overall score (69.7%) due to fewer regulatory constraints, whereas Scenarios 1 and 2 (61.2% and 54.5%, respectively) are penalised due to the more regulations for human consumption. The proposed tool offers a practical and efficient method to support researchers and industry stakeholders in identifying CE strategies with the highest potential for sustainable development. Full article

In this article, we employed a systematic approach to risk assessment and the adaptation of security measures to explore possibilities for more effective cybersecurity in the supply chains of the armed forces. Our focus was on developing a model with quantified indicators that, on one hand, enable dynamic monitoring of the security status and timely threat detection, while, on the other hand, enhance the resilience of supply chains against cyber threats. Our findings indicate that applying this model enables a comprehensive security risk assessment, the adaptation of protective measures to operational requirements, and the optimization of resources to ensure the uninterrupted functioning of the armed forces. Future research will focus on validating the model in real-world scenarios and adapting it to the specific needs of different organizations. Full article

Industrial packaging systems exert substantial environmental pressures, including material resource depletion, greenhouse gas emissions, and the accumulation of post-consumer waste. As global supply chains expand and sustainability regulations intensify, demand for environmentally responsible packaging solutions continues to rise. This study evaluates the environmental footprint of industrial packaging by integrating recent developments in life cycle assessment (LCA), ecological footprint (EF) methodologies, material innovations, and circular economy models. The assessment examines the sustainability performance of conventional and alternative packaging materials, plastics, aluminum, corrugated cardboard, and polylactic acid (PLA). Findings indicate that although corrugated cardboard is renewable, it still presents a measurable environmental burden, with evidence suggesting that incorporating solar energy into production can reduce its footprint by more than 12%. PLA-based trays demonstrate promising environmental performance when sourced from renewable feedstocks and directed to appropriate composting systems. Despite these advancements, several systemic challenges persist, including ecological overshoot in industrial regions where EF may exceed local biocapacity limitations in waste management infrastructure, and significant economic trade-offs. Transportation-related emissions and scalability constraints for bio-based materials further hinder large-scale adoption. Existing research suggests that integrating sustainable packaging across supply chains could meaningfully reduce environmental impacts. Achieving this transition requires coordinated cross-sector collaboration, standardized policy frameworks, and embedding advanced environmental criteria into packaging design and decision-making processes. Full article

In response to the evolving dynamics of global supply chains, business-to-business (B2B) sharing economy models within the logistics industry have gained importance for innovation and sustainability over the last few years. According to a literature review, the sharing economy has become a pivotal innovation in the business environment, especially for resource utilisation efficiency and the potential to advance sustainable development policies. Despite the known positive impact on the economy and environment, integrating sharing economy models into logistics and supply chains remains limited. This highlights a key research area that requires a thorough examination of the barriers and opportunities for business-to-business (B2B) sharing economy platforms in logistics and supply chains that reflect environmental policy goals and promote cleaner, more efficient logistics systems. This paper outlines the significance of B2B sharing economy platforms as a crucial part of smart and resource-efficient supply chains. Using a system theory approach, B2B sharing economy platforms in logistics and SC were identified and systematically and comprehensively analysed across four critical aspects: sharing storage, sharing parking space, shared labour, and collaborative transportation. The scope of the research is limited to the smart and sustainable dimensions of logistics and supply chains, with a particular focus on the analysis of B2B sharing economy platforms. The novelty of this study lies in its empirical and theory-informed analysis of B2B sharing platforms as a key driver for smart and resource-efficient logistics. While prior studies have largely focused on consumer-facing sharing models or conceptual frameworks, this paper systematically evaluates operational B2B platforms. The analysis reveals that while B2B platforms offer valuable solutions in collaborative transport, storage, labour, and parking, they are underutilised and insufficiently aligned with environmental and digital objectives. The study introduces a spider chart analysis grounded in system theory to evaluate platforms against six dimensions, uncovering trade-offs between flexibility and sustainability. These insights contribute to understanding the strategic positioning of such platforms and propose a direction for smarter, resource-efficient supply chains. Full article

Fossil fuels have been the main source of energy for decades. However, they are non-renewable resources that take millions of years to replenish from decomposed organic matter. As they are depleting at an alarming rate, a shift towards more sustainable fuels is gaining popularity. Biodiesel is emerging as a biodegradable and renewable energy source that serves as a promising alternative to conventional fuels. It addresses the challenges of greenhouse gas emissions while ensuring energy security. Among potential feedstocks, sunflower oil demonstrates unique advantages due to its high oil yield, favorable fatty acid composition, and availability. Despite extensive research on biodiesel, no comparative study has yet synthesized the four generations of biodiesel feedstocks while integrating optimization strategies with a particular focus on sunflower oil and sustainability trade-offs. This review aims to fill that gap by providing a comprehensive analysis of biodiesel production pathways, highlighting sunflower oil within a broader sustainability framework. The four generations are assessed based on feedstock potential, efficiency, and yield, while optimization processes for sunflower oil-based biodiesel are examined in terms of economic feasibility, limitations, and environmental impacts. The principal findings highlight the low free fatty acid composition of sunflower oil compared to other feedstocks, which makes it efficient for transesterification. Challenges such as production costs, land consumption, and food chain disruption are also discussed. Finally, innovative insights are presented for improving the viability of biodiesel through advanced technologies and supportive policies. Full article

Poultry production faces considerable challenges in terms of feed costs and sustainability, particularly regarding conventional protein sources such as fish meal (FM). Insect-based proteins, such as housefly larvae (HL) meal, offer sustainable alternatives. Therefore, this study aimed to investigate the effects of HL on growth, gut health, metabolizable energy, and gut microbiota of broilers to clarify the availability of HL meal for broiler diet. Experiment 1 was performed to investigate the effects of replacing FM with HL on growth performance, intestinal morphology, cecal short-chain fatty acids, and gut microbiota composition and diversity in male broilers. Experiment 2 was performed to assess the digestibility of broiler diets containing HL. HL addition effectively maintained growth and improved intestinal morphology. Blood analysis revealed that HL addition reduced TNF-α levels and improved protein utilization. Additionally, HL substitution induced significant changes in the gut microbiota community and metabolic pathways. In conclusion, HL are a viable alternative to FM with adequate energy content and beneficial effects on gut health, supporting their use as a sustainable protein source. Full article

Research has identified self-concept clarity as a critical psychological resource; however, its mechanisms in mitigating artificial intelligence (AI) anxiety remain underexplored. This study employed a cross-sectional survey of 2176 graduate students (1584 females; M_age = 23.60, SD = 2.03) to build a moderated chain mediation model that examines the mediating role of intentional self-regulation and perceived stress, as well as the moderating role of intolerance of uncertainty. Self-concept clarity was negatively correlated with AI anxiety, perceived stress, and intolerance of uncertainty, and positively correlated with intentional self-regulation. Mediation analyses showed that self-concept clarity predicted lower AI anxiety through both independent and chain mediation effects of intentional self-regulation and perceived stress. Moreover, intolerance of uncertainty moderated the links of self-concept clarity, intentional self-regulation, and perceived stress with AI anxiety. These findings highlight the importance and key explanatory mechanisms of self-concept clarity in mitigating AI anxiety among adults, elucidating that the cultivation of self-concept clarity and acceptance of uncertainty should be a crucial target for prevention and intervention strategies. Full article

To meet 2050 climate targets, the construction sector must reduce CO₂ emissions and transition toward circular material flows. Recycled aggregates (RA) derived from construction and demolition waste (CDW) and industrial byproducts such as oil shale ash (OSA) show potential for use in concrete, although their application remains limited by standardisation and performance limitations, particularly in structural uses. This study aims to develop and evaluate low-strength, resource-efficient concrete mixtures with full replacement of natural aggregates (NA) by CDW-derived aggregates, and partial or full replacement of cement CEM II by OSA–metakaolin (MK) binder, targeting non-structural 3D-printing applications. Mechanical performance, printability, cradle-to-gate life cycle assessment, eco-intensity index, and transport-distance sensitivity for RA were assessed to quantify the trade-offs between structural performance and global warming potential (GWP) reduction. Replacing NA with RA reduced compressive strength by ~11–13% in cement-based mixes, while the aggregate type had a negligible effect in cement-free mixtures. In contrast, full cement replacement by OSA-MK binder nearly halved compressive strength. Despite the strength reductions associated with the use of waste-derived materials, RA-based cement-free 3D-printed specimens achieved ~30 MPa in compression and ~5 MPa in flexure. Replacing CEM II with OSA-MK and NA with RA lowered GWP by up to 48%, with trade-offs in the air-emission, toxicity, water and resource categories driven by the OSA supply chain. The cement-free RA mix achieved the lowest GWP and best eco-intensity, whereas the CEM II mix with RA offered the most balanced multi-impact profile. The results show that regionally available OSA and RA can enable eco-efficient, structurally adequate 3D-printed concrete for construction applications. Full article

The sustainability of the beef and dairy industry requires a systems approach that integrates environmental stewardship, social responsibility, and economic viability. Over the past two decades, global genetics consortia have advanced data-driven germplasm programs (breeding and conservation programs focusing on genetic resources) to enhance sustainability across cattle systems. These initiatives employ multi-trait selection indices aligned with consumer demands and supply chain trends, targeting production, longevity, health, and reproduction, with outcomes including greenhouse gas mitigation, improved resource efficiency and operational safety, and optimized animal welfare. This study analyzes strategic initiatives, germplasm portfolios, and data platforms from leading genetics companies in the USA, Europe, and Brazil. US programs combine genomic selection with reproductive technologies such as sexed semen and in vitro fertilization to accelerate genetic progress. European efforts emphasize resource efficiency, welfare, and environmental impacts, while Brazilian strategies focus on adaptability to tropical conditions, heat tolerance, and disease resistance. Furthermore, mathematical models and decision support tools are increasingly used to balance profitability with environmental goals, reducing sustainability trade-offs through data-driven resource allocation. Industry-wide collaboration among stakeholders and regulatory bodies underscores a rapid shift toward sustainability-oriented cattle management strategies, positioning genetics and technology as key drivers of genetically resilient and sustainable breeding systems. Full article

This paper constructs a two-way fixed effects model using data from 4623 Chinese A-share listed enterprises from 2011 to 2022, confirming that firm digital transformation can enhance access to sustainable trade credit. Specifically, for every 1% increase in the standard deviation of digital transformation, the trade credit obtained by enterprises increases by 2.14% in relation to their average value. We employed instrumental variable (IV) and propensity score matching (PSM) methods, utilizing the Broadband China pilot policy as a quasi-natural experiment to conduct a multi-period propensity score matching-difference in differences (PSM-DID) analysis to address potential issues of reverse causality and sample selection bias. Mechanism analysis indicates that the diversification of supplier structures, R&D innovation, and market share facilitated by digitalization are three main channels. This effect is particularly significant in state-owned enterprises, mature enterprises, and those with higher social trust. Finally, the study also found that the spillover effects of digital transformation encourage client enterprises to allocate credit resources to downstream firms, thereby promoting the sustainable development of supply chain finance. Furthermore, the digital transformation primarily alleviates short-term credit challenges for enterprises and reduces their reliance on bank credit. Full article

As contemporary global supply chains have become interconnected and exposed to diverse escalating cyber threats, Cyber Supply Chain Risk Management (C-SCRM) has rapidly evolved as a managerial imperative to safeguard security, robustness, and resilience, and hence ensure organizational sustainability and growth. While the concept of C-SCRM has recently received much attention among scholars, practitioners, and policymakers as an emerging field of study, its conceptual utility and theoretical foundation remain undeveloped. To address this gap, this paper provides a systematic literature review of C-SCRM using a hybrid approach that integrates bibliometric and concept evaluation analysis to ensure the goodness of the concept. A total of 175 relevant peer-reviewed scholarly articles from the Web of Science (WOS) Core Collection were collected and analyzed. The review reveals that the concept has many strengths, in terms of its interdisciplinary conceptual foundation and growing managerial relevance, but it also suffers from conceptual diffusion, overlapping terminology, and limited construct operationalization that inhibits theory development, hinders empirical accumulation, and limits practitioners’ ability to operationalize C-SCRM as a strategic resource. This review contributes to the C-SCRM literature by providing (1) a historical overview and intellectual structure of C-SCRM; (2) a synthesis and comparative analysis of the existing definitions; (3) an evaluation of the conceptual adequacy and theoretical relevance that underpin C-SCRM research based on established criteria and (4) conceptual and empirical research directions as well as an integrative framework. Based on the insights, our review might facilitate the improvement of multidimensional construct clarity and validation in future empirical studies and could be a useful tool for managers to benchmark C-SCRM maturity in practice. Full article

The transition toward a Circular Economy (CE) has received significant attention from academia, industry, and policymakers; however, manufacturing practices remain predominantly linear, generating waste and inefficiencies. This study addresses the lack of accessible sustainability assessment methods by introducing the Circularity Calculator (CC), a novel tool for evaluating circular strategies during the early phases of process development. Unlike existing assessment frameworks, which often require extensive data and customization, the CC can be integrated directly to existing processes to combine environmental and economic impact into a streamlined evaluation process for early decision-making. The research involves collaboration with a leading German automotive manufacturer. Site visits and interviews enabled the identification of material flows and primary waste streams, which informed the definition of relevant indicators. The CC generates a dimensionless index, enabling comparison and prioritization of proposed scenarios without relying on supply-chain-wide data, which is often unavailable at early stages. Implications demonstrate the adaptability of the CC across industrial contexts, supporting conceptual planning and operational phases. Its intuitive design facilitates adoption by practitioners without extensive expertise in sustainability. The tool represents an advance in CE assessment, contributing to Sustainable Development Goals (SDGs) 9, 12, and 17 by promoting sustainable industrial practices, resource circularity, and collaborative evaluation frameworks. Full article

Bacillus licheniformis Mb1, a thermophilic strain isolated from the Yungas rainforest in northwestern Argentina, was analyzed through genomic and experimental approaches to explore its biotechnological potential. Phylogenomic analysis confirmed its close relationship with B. licheniformis reference strains. The genome revealed multiple genes associated with hydrolytic, oxidative, carbohydrate-active, and polyester-degrading activities, indicating a wide enzymatic capacity. Experimental assays demonstrated strong extracellular hydrolytic activities and efficient degradation of bis(2-hydroxyethyl) terephthalate (BHET), a key polyethylene terephthalate (PET) intermediate. In liquid cultures with 3 mg/mL BHET, B. licheniformis Mb1 achieved 99.9% depletion within four days, with transient BHET dimer accumulation and progressive terephthalic acid (TPA) production, reaching 1.17 mg/mL after 15 days. Mono (2-hydroxyethyl) terephthalate (MHET) and vanillic acid were not detected. Complete BHET and dimer degradation suggests the presence of versatile hydrolases acting on short-chain polyester intermediates. Sequence and molecular docking analyses identified a BHETase-like carboxylesterase as the main enzyme candidate, featuring a truncated lidC region that generates a more open catalytic cleft. This structural trait, not previously reported in bacterial BHETases, enables the accommodation of bulkier substrates such as BHET dimer. These findings highlight B. licheniformis Mb1 as a promising biocatalyst for polyester depolymerization and a valuable microbial resource for future enzyme discovery and plastic bioremediation strategies. Full article

This paper proposes a process-aware, tag-based digital identity framework that enhances interoperability while enabling identity unlinkability and selective disclosure across multi-party workflows involving sensitive data. We realize this framework within the self-sovereign identity (SSI) paradigm, employing zk-SNARK–based zero-knowledge proofs to enable verifiable identity authentication without plaintext disclosure. The framework introduces a protocol-tagging mechanism to support multiple proof systems within a unified architecture, thereby enhancing SSI scalability and interoperability. Its core innovation lies in combining identity unlinkability and process-driven data disclosure: derived sub-identities mitigate identity-linkage attacks, while layered encryption enables selective, stepwise decryption of sensitive information (e.g., delivery addresses), ensuring participants access only the minimal information necessary for their tasks. In addition, zero-knowledge proof-based verification guarantees that the validation of derived sub-identities can be performed without sharing any plaintext attributes or identifying factors. We applied the framework to logistics, where sub-identities anonymize participants and layered encryption allows for delivery addresses to be decrypted progressively along the logistics chain, with only the final courier authorized to access complete information. During the parcel receipt process, users can complete verification using derived sub-identities and zero-knowledge proofs alone, without disclosing any real personal information or attributes that could be linked back to their identity. Trusted Execution Environments (TEEs) ensure the authenticity of decryption requests, while blockchain provides immutable audit trails. A demonstration system was implemented, formally verified using Scyther, and performance-tested across multiple platforms, including resource-constrained environments, showing high efficiency and strong practical potential. The core paradigms of identity unlinkability and process-driven data disclosure are generalizable and applicable to multi-party scenarios involving sensitive data flows. Full article