Search Results (1,704)

Olive cultivation generates substantial pruning waste, yet current valorization strategies focus solely on leaves despite the logistical challenges of separating them. This study optimized the extraction of bioactive compounds from unseparated pruning waste (branches and leaves) using a D-optimal design of experiments to evaluate solvent composition, temperature, and time effects in thirteen experiments. Optimized conditions were scaled up, and extracts were tested via DPPH, ORAC assays, and ROS inhibition in HaCaT cells. Extracts from unseparated pruning waste demonstrated antioxidant capacity equivalent to isolated leaf extracts, and effectiveness in reducing the oxidative stress by approximately 60% compared to the H₂O₂ condition. This approach eliminates costly leaf separation while maintaining bioactivity, offering a scalable circular economy solution for olive waste management. The practical implications are substantial: whole pruning waste valorization reduces processing costs and time, decreases agricultural waste by utilizing currently discarded branches, and simplifies supply chains for industries requiring olive-derived antioxidants. Our findings challenge the current paradigm in olive waste biorefining, providing a more economically viable and environmentally sustainable pathway for producing antioxidant-rich extracts suitable for cosmetics, nutraceutical, and pharmaceutical applications. Full article

Against the backdrop of great power strategic games, countries around the world have been continuously intensifying their control over the trade of critical metals, including tungsten, in order to seize the commanding heights of scientific, technological, and economic development, which has led to increasingly fierce competition in the global tungsten industry chain and supply chain. Although China is endowed with abundant tungsten ore reserves, its tungsten industry chain remains dominated by mid-to-low-end products, with low added value and limited pricing power in the international market. Therefore, it is of great significance to clarify the export competitiveness level of China in each link of the tungsten industry chain and to identify the influencing factors for improving the overall competitiveness of the industrial chain, which will enhance China’s international status and assist in formulating sustainable tungsten resource management strategies. Based on the industrial chain perspective and the trade data of typical products at various stages of the tungsten industry chain from 2008 to 2022, this study first selects the World Market Share Index, Trade Competitive Advantage Index, and Revealed Comparative Advantage Index to quantitatively depict the export competitiveness of the overall, upstream, midstream, and downstream sectors of China’s tungsten industry chain, and a horizontal comparison is conducted with major global tungsten resource trading countries. Secondly, the entropy weight method is adopted to further comprehensively evaluate the competitiveness level of various countries. Finally, the potential influencing factors of the overall export competitiveness of the tungsten industry chain are explored in accordance with Porter’s Diamond Model, and a fixed-effect model is used to perform regression analysis on the panel data. The research findings show that China has strong export competitiveness in the midstream and downstream sectors of the tungsten industry chain, while its export competitiveness in the upstream tungsten ore sector is relatively weak. The level of education, human capital, educational expenditure, gross national product, and trade openness all have a significant positive impact on the export competitiveness of tungsten resources. Greater efforts should be made in China to cultivate high-end talents in the tungsten industry. Moreover, innovation in green technologies and products should be encouraged, and international cooperation should be deepened, to improve the efficiency of the entire industrial chain so that stable and green long-term competitiveness in the tungsten industry can be achieved. Full article

Digital content platforms rely on value co-creation among users, creators, and the platform. Content value, including historical accumulation, influences platforms’ pricing strategies, quality decisions, and monetization potential. This study explores the impact of content value on pricing and quality strategies under centralized and decentralized content configurations. We capture the relationship between historical content quality and user engagement. The interplay of historical quality and content type is characterized as content value dynamics, which influence platforms in managing content supply, user engagement, and revenue generation under different modes. Results show that operational modes offer distinct advantages depending on subsidy levels, advertising revenue-sharing mechanisms, and the platform development stage. The centralized mode performs better under limited subsidies, particularly by offering content with higher continuity. The decentralized mode benefits from diverse creation and flexible incentives to achieve rapid market scaling when subsidies are sufficient. Notably, higher advertising revenue-sharing is not always optimal, especially in low-advertising environments. Additionally, the platform development stage affects optimal mode selection. The decentralized mode with low subsidies may achieve early profitability, whereas the centralized mode offers greater potential for sustainable long-term growth. This work contributes to platform-based supply chain theory by incorporating dynamic content value into operational decision-making. It provides operational insights for platforms regarding mode design and the optimization of value-based monetization strategies. Full article

Corporations are increasingly pressured to adopt Creating Shared Value (CSV) not only as a means of profit generation but as a strategic approach to addressing societal challenges. Through value chain innovation, firms can simultaneously enhance competitiveness and contribute to social problem-solving. Although supply chain performance has been widely studied, limited research has examined the combined relationships among CSV activities, information characteristics, and information performance. This study analyzes how CSV—reflected through business and societal value—affects information sharing and information quality, and how these factors further influence sustainable information performance across management, behavioral, and technological dimensions. Using data collected from 182 firms, the findings reveal that CSV activities significantly improve both information sharing and information quality, which subsequently enhance information performance. These results highlight CSV’s essential role in establishing cooperative supply chain relationships and strengthening organizational information capability. By integrating CSV principles with information-driven processes, this research provides theoretical and managerial contributions and demonstrates that fostering high-quality information flows grounded in CSV can support long-term competitiveness and societal value creation. Full article

This study examines the synergistic interaction between technology-driven digitalization and circular economy principles in enhancing sustainable supply chain performance among small and medium-sized enterprises (SMEs). Rather than examining digital technologies in isolation, we adopt an integrative systems perspective that conceptualizes digitalization as a multi-layered ecosystem comprising sensing (Internet of Things), intelligence (Artificial Intelligence and Big Data Analytics), verification (Blockchain), and coordination (Digital Collaboration Capability) layers. Through empirical analysis of 168 Tunisian SMEs across manufacturing and service sectors, this paper investigates the indirect impact of these complementary digital capabilities on sustainable supply chain performance, mediated by three dimensions of circular economy integration: waste reduction, resource efficiency, and sustainable design. The results indicate that digitalization has a positive influence on both environmental and economic performance, operating indirectly through the adoption of circular economy practices. By enhancing transparency, traceability, and operational efficiency, digital innovations reinforce circular economy practices, which consequently promote greater resilience and sustainability in supply chains. Sub-dimensional analyses reveal technology-specific mechanisms: IoT most strongly enables resource efficiency, AI and BDA drive waste reduction, Blockchain facilitates sustainable design, and Digital Collaboration Capability exhibits balanced effects across all circular dimensions. These findings underscore the critical role of integrated technological ecosystems, rather than isolated technology adoptions, in advancing sustainable supply chain management, particularly in resource-constrained SME contexts. Full article

The paper investigates the role of digitalization in strengthening the sustainability of supply chains in the Romanian restaurant sector. The starting point is the intersection between the pressures for digital transformation and the integration of sustainability principles. Digitalization, through advanced digital solutions, can strengthen traceability, reduce waste, and optimize resources, strengthening responsibility for economic efficiency and the environment. However, the implementation of these solutions in HoReCa remains disproportionate and faces barriers such as lack of digital skills, high costs, and resistance to change. The authors conducted a quantitative research study among restaurant managers in Romania. The research was complemented with two Principal Component Analyses (PCA) and a TwoStep Cluster Analysis. The role of the TwoStep Cluster Analysis was to identify a typology of restaurants according to managerial behaviors related to digitalization from a sustainable perspective. The results showed that digitalization is applied predominantly in inventory management, but less in the relationship with consumers and supply chain, where it would bring considerable benefits for sustainability. The study provides theoretical and practical contributions, highlighting the role digitalization has as a facilitator of sustainability and indicating recommendations for managers and decision-makers regarding professional training and financial support policies dedicated to sustainable digitalization. Full article

The increasing frequency and intensity of extreme disasters, exacerbated by climate change, pose significant challenges to sustainable development by disrupting critical infrastructure and hampering relief efforts. Enhancing disaster resilience—a core objective of sustainable development—requires integrated approaches that simultaneously address infrastructure restoration and efficient resource allocation. This study proposes a sustainable optimization framework for post-disaster response, integrating road rehabilitation decisions with emergency logistics planning within a three-tier supply chain network. We develop a mathematical model that synergistically optimizes repair crew scheduling, depot location, and vehicle routing, with the objective of maximizing a comprehensive satisfaction index that balances timely delivery (time satisfaction) and fulfillment of material needs (demand satisfaction). This integrated approach directly contributes to sustainable disaster management by ensuring more reliable and equitable access to vital resources in affected communities. A tailored variable neighborhood search algorithm is designed to solve the model efficiently, as demonstrated through large-scale numerical experiments. Our findings highlight several policy-relevant insights for sustainable emergency planning: adequate budgeting is crucial for uninterrupted relief operations; strategic investments in rapid road repair capabilities or vehicle fleets significantly enhance system efficiency; and prioritizing time satisfaction (rapid response) yields greater overall benefits than merely increasing delivered quantities. Furthermore, restoring critical road infrastructure is shown to mitigate transportation uncertainties, thereby strengthening the resilience of the entire relief system. This work provides a quantifiable methodology and practical decision support tools for building more sustainable and resilient communities in the face of disasters. Full article

Kazakhstan’s mining sector, a vital pillar of the national economy, generates significant volumes of waste. This waste has been found to hold considerable residual value, presenting a substantial opportunity for resource recovery and economic benefit. To unlock this value, establishing efficient reverse logistics operations is fundamental, as it enables the recovery, recycling, and reuse of materials in a cost-effective and sustainable manner. This paper introduces a conceptual optimization framework tailored to Kazakhstan’s mining industry to explore the feasibility of reverse supply chain processes. The implementation of strategies informed by this model can improve resource utilization, reduce environmental impact, and deliver long-term economic benefits. The study also identifies potential challenges to adoption and suggests pathways for further refinement of the model to adapt to the evolving needs of Kazakhstan’s mining sector. The model provides a robust analytical foundation to support discussions on developing a holistic strategy for waste management in the sector. It offers key insights into optimizing waste handling, advancing material recovery technologies, and promoting collaboration between public and private stakeholders. By aligning these insights with the regulatory and economic landscape of Kazakhstan, the model serves as a reference point to shape a broader national framework. The outcomes of this study contribute to the achievement of Sustainable Development Goals (SDGs) 9 and 12 by promoting industrial innovation, resource efficiency, and responsible production practices within Kazakhstan’s mining sector. Full article

Background: In the context of increasing supply chain complexity, efficient inventory management has become important in enhancing the performance of logistics systems and sustaining the competitiveness of companies. Real-time visibility, tracking, and control over stock levels ensure responsiveness, reduce waste, and support strategic decision-making. Decision support systems that integrate demand analysis with inventory policies play a pivotal role in improving operational efficiency. This paper addresses the need for more efficient stock management to optimize purchasing and inventory costs within a manufacturing environment. Methods: Production planning processes were analyzed to determine material requirements, and a representative product was selected. The study involved ABC classification based on the average annual stock value of purchased parts, complemented by an XYZ analysis to evaluate demand variability. Afterwards, stock management policies were tested, namely, continuous and periodic review models. Each item was assessed to determine the most suitable inventory management method based on its consumption profile. Results: A comparison with the company’s existing approach revealed that for 9 out of the 13 materials studied, the application of stock management models led to improvements. Conclusions: The results show a potential cost reduction of 33% for the nine materials to which stock policies were successfully applied. Full article

Background: Digital supply chain transformation research exhibits a critical gap, examining technologies in isolation rather than as integrated ecosystems. Methods: This study addresses this limitation by developing a comprehensive orchestration frame-work through PRISMA-guided systematic review of 96 publications (2012–2024) using bibliometric analysis, structural topic modeling, and thematic synthesis across Scopus and Web of Science databases. Results: Analysis revealed three distinct research clusters: Supply Chain Management (centrality: 14.95), Digital Transformation (centrality: 9.50, density: 101.05), and Big Data Analytics (density: 113.22), with substantial negative correlations (−0.48 to −0.54) indicating organizational evolution from fragmented adoption toward integration. Conclusions: Publications increased 78% year-over-year during 2021–2022, while Supply Chain Management dominated topic prevalence (41%) and Big Data Analytics declined from 0.9 to 0.15 as practices normalized. The Digital Supply Chain Orchestration Framework conceptualizes transformation as multi-layered with hierarchical relationships between foundational domains, technological enablers, integration mechanisms, and value creation dimensions. This framework provides structured approaches for organizations to assess digital maturity, identify technological gaps, and develop strategic roadmaps aligned with Sustainable Development Goals, bridging theory and practice for integrated, value-driven digital transformation. Full article

The rapid expansion of digital trade presents transformative opportunities for South-South cooperation, particularly between China and West Africa. However, emerging new risks in technological, institutional, and sociocultural domains pose significant challenges to sustainable e-business collaboration. This study proposes a Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) framework to evaluate and prioritize these risks under conditions of uncertainty and expert judgment ambiguity. By integrating fuzzy logic with AHP, the model effectively captures the vagueness and imprecision inherent in multi-criteria decision-making (MCDM). Expert assessments from professionals in digital trade, cybersecurity, and risk management were used to conduct pairwise comparisons across three primary risk categories: Technological, Institutional, and Sociocultural Risks. The results indicate that Institutional Risk (weight: 0.3488) holds the highest priority, followed by Sociocultural Risk (weight: 0.3268) and Technological Risk (weight: 0.3244), highlighting the critical influence of cultural alignment, consumer trust, and behavioral norms in cross-border digital collaboration. The PF-AHP approach enhances decision reliability by incorporating membership, non-membership, and indeterminacy degrees, offering a robust tool for risk assessment in complex digital supply chains. This research contributes to the discourse on equitable digital globalization and provides strategic insights for policymakers and stakeholders aiming to build inclusive, resilient, and mutually beneficial digital trade ecosystems between China and West Africa. Full article

Three-Dimensional Printing (3DP) is rapidly emerging as a pivotal technology for advancing Facilities Management (FM) toward smart and sustainable buildings. This systematic review, following PRISMA 2020 guidelines, critically evaluates 3DP applications, benefits, and challenges across core FM domains—construction, maintenance and repair, supply chain management, and specialized applications—through analysis of 179 studies. To our knowledge, this represents the first comprehensive, FM-specific systematic review of 3DP implementation frameworks. Evidence synthesis reveals that 3DP enables on-demand, localized manufacturing of bespoke components, with documented inventory cost reductions in maintenance applications, substantial production cost decreases for complex geometries, and significant lead time improvements from traditional procurement cycles to rapid on-demand fulfillment for spare parts applications. However, quantitative evidence remains limited and context-dependent, particularly regarding economic feasibility and scalability. 3DP adoption in FM faces significant barriers: quality assurance protocols, workforce readiness, BIM/IoT integration challenges, and regulatory uncertainty. This review identifies the absence of validated decision-making frameworks to guide FM professionals on 3DP implementation versus traditional alternatives, a fundamental research and practice gap. Through structured quality assessment and stakeholder analysis, we propose strategic recommendations emphasizing cross-sector collaboration, standardization development, and workforce upskilling. A novel conceptual decision framework supports practical implementation decisions. These findings position 3DP as potentially transformative for sustainable building operations while highlighting critical research priorities for systematic FM sector deployment. Full article

This study proposes an enhanced model for optimizing cost-sharing strategies in competitive manufacturing supply chains, integrating the effects of learning, forgetting, and sustainable green practices. Building on the foundational framework of a monopolistic competition environment, the research extends the traditional cost allocation between an incumbent manufacturer and a midstream assembly plant by incorporating environmental costs, such as carbon emissions taxes, into the total cost function. The model accounts for learning and forgetting dynamics in both setup and production stages, influencing setup costs, production costs, and inventory holding costs, alongside defensive costs against competitors. A novel sustainability extension introduces an environmental cost component, reflecting the impact of demand-driven emissions under varying cost-allocation rates. Sensitivity analyses demonstrate that a higher rate of competitor entry, reduced dispersion in defensive costs, and elevated learning/forgetting rates increase the optimal cost-allocation rate and total expected cost, with production-stage effects dominating setup-stage impacts. Furthermore, the inclusion of green practices reveals a trade-off, where higher environmental taxes and emission rates lower the optimal allocation to mitigate emissions, albeit at an increased overall cost. Numerical simulations validate the model, offering insights for managers to balance economic efficiency with environmental sustainability in dynamic supply chain contexts. Full article

This study examines the evolution of environmental discourse in supply chain management (SCM) research from 2004 to 2024, systematically comparing scholarly trajectories with media narratives to identify critical implementation gaps at the theory–practice interface. Following PRISMA guidelines, we employ structural topic modeling on 6586 academic articles and 384,190 media articles (2019–2023) within the SPAR-4-SLR protocol, we document substantial growth in sustainability scholarship—from fewer than 200 publications in 2004 to over 700 in 2024—with research emphasis shifting from compliance-oriented frameworks toward strategic integration models. Systematic comparison reveals significant misalignments: six domains—community-based sustainability initiatives, climate adaptation strategies, plastic reduction mandates, food security resilience, event-driven crisis responses, and sustainable product design—receive substantially greater media emphasis than scholarly investigation, constituting what we characterize as the implementation knowledge gap. This gap reflects disconnection between theoretically sophisticated academic frameworks emphasizing long-term strategic integration and practitioner concerns prioritizing acute operational challenges, rapid regulatory compliance, and grassroots sustainability mechanisms. Our findings demonstrate that, while academic research remains theoretically robust, it insufficiently captures short-term adaptation imperatives, community-level integration mechanisms, and sector-specific resilience strategies that climate volatility demands. By establishing a transferable analytical framework integrating media discourse with academic literature, this study advances sustainable supply chain management theory through reconceptualizing implementation challenges as central research concerns while generating actionable imperatives for aligning scholarship, policy interventions, and industrial strategies toward climate-resilient supply chain systems. Full article

In light of the ambitious “dual carbon” targets, the refined oil supply chain faces challenges in balancing economic viability with environmental sustainability. Traditional resource allocation methods predominantly prioritize cost minimization, often overlooking significant environmental impacts and leading to carbon-intensive transportation practices. This paper proposes a multi-objective optimization model to simultaneously minimize total logistics costs and carbon emissions across the entire refined oil supply chain. The model encompasses key stages, including refinery production, external procurement, multimodal transport operations, and inventory management. The proposed framework integrates practical con straints such as sending and receiving capacities, inventory balance, and supply and demand requirements. The ε-constraint method is employed for model solution to generate a set of Pareto optimal solutions, highlighting the inherent trade-offs between economic and environmental objectives. A case study is carried out, involving a refined oil logistics system in Central China, which comprises five refineries, 31 depots, and two external purchasing nodes. Compared to a purely economic optimization, a balanced scenario (e.g., with an ε-constraint of 9000 tons/season for carbon emissions) achieves a substantial 10–15% reduction in emissions with only a marginal 1–2% increase in logistics costs. Furthermore, the optimization significantly reconfigures the transport structure, increasing pipeline utilization from 27.3% to 35% and leading to a 26.1% reduction in waterway-related carbon emissions. This study can offer an efficient decision-making tool that facilitates the green transformation of the refined oil supply chain, bridging the gap between corporate logistics cost efficiency and ambitious carbon neutrality targets. Full article