Search Results (11,803)

As global supply chains face increasing pressure to reconcile economic efficiency, environmental responsibility, and ethical transparency, emerging digital technologies offer unprecedented opportunities for sustainable transformation. This article examines this dynamic in the context of the Moroccan industrial sector, with particular reference to blockchain and digital twin technologies. The study employs a rigorous mixed-methods design, combining an in-depth qualitative exploration with 30 industry professionals and a Partial Least Squares Structural Equation Modeling (PLS-SEM) model based on survey data from 125 Moroccan manufacturing firms. The findings highlight the synergistic contribution of blockchain and digital twins in enabling circular, low-carbon, and resilient supply chains. Blockchain adoption strengthens environmental impact traceability, data reliability, and responsible governance, while digital twin systems enhance eco-efficiency through real-time modeling and predictive flow simulation. Circular integration emerges as a critical enabler, significantly amplifying the positive effects of both technologies by aligning physical and informational flows within closed-loop processes. With its strong empirical grounding and contextual relevance to an emerging economy, this research provides actionable insights for policymakers, industrial managers, and supply chain practitioners committed to accelerating the sustainable transformation of production systems. It also offers a renewed understanding of how digitalization and circularity jointly support environmental performance within industrial ecosystems. Full article

As the supply chain of the electric vehicle (EV) industry becomes increasingly complex and vulnerable, traditional supplier evaluation methods reveal inherent limitations. These approaches primarily emphasize static performance while neglecting dynamic future risks. To address this issue, this study proposes a comprehensive supplier evaluation model that integrates a hybrid Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) framework with the Extreme Gradient Boosting (XGBoost) algorithm, contextualized for the EV sector. The hybrid AHP-TOPSIS framework is first applied to rank suppliers based on multidimensional performance criteria, including quality, delivery capability, supply stability and scale. Subsequently, the XGBoost algorithm uses historical monthly data to capture nonlinear relationships and predict future supplier risk probabilities. Finally, a risk-adjusted framework combines these two components to construct a dynamic dual-dimensional performance–risk evaluation system. A case study using real data from an automobile manufacturer demonstrates that the hybrid AHP–TOPSIS model effectively distinguishes suppliers’ historical performance, while the XGBoost model achieves high predictive accuracy under five-fold cross-validation, with an AUC of 0.851 and an F1 score of 0.928. After risk adjustment, several suppliers exhibiting high performance but elevated risk experienced significant declines in their overall rankings, thereby validating the robustness and practicality of the integrated model. This study provides a feasible theoretical framework and empirical evidence for EV enterprises to develop supplier decision-making systems that balance performance and risk, offering valuable insights for enhancing supply chain resilience and intelligence. Full article

As a pillar industry of the national economy for many countries, the construction sector has long faced challenges in workplace safety. Unsafe behaviors among construction workers are the core cause of safety incidents, and controlling these behaviors is key to enhancing safety management. Numerous studies confirm that unsafe behaviors are closely linked to cognitive biases and decision-making errors. However, existing research still has theoretical gaps in analyzing the multi-factor interaction mechanisms from a cognitive perspective. This study constructs a three-stage theoretical model to reveal the formation mechanism of unsafe behaviors, which is validated by structural equation modeling based on the data collected by a questionnaire from ongoing construction projects in Jiangxi Province, China. It is found that (1) Organizational environment (safety atmosphere, safety culture, and safety management) exerts a negative influence on unsafe behavior; (2) While safety atmosphere has no direct impact on safety motivation, the overall organizational environment positively affects individual cognition; (3) Individual cognitive factors exert a negative influence on unsafe behavior, with the following hierarchical order: safety motivation > safety competence > safety values. (4) While safety motivation does not mediate the relationship between safety atmosphere and unsafe behavior, individual cognitive factors overall mediate the relationship between organizational environment and unsafe behavior. This study theoretically enriches the knowledge system of safety behavior and provides a theoretical foundation for optimizing enterprise unsafe behavior management and formulating differentiated management policies. Full article

Recycling of 6xxx aluminum alloys, which are used extensively in the automotive industry, is important for ensuring a carbon-neutral future and the efficient use of resources on Earth. The sustainability of recycling in aluminum alloys is directly proportional to the correct classification of the scrap to be used. In this study, scrap stream from a novel scrap-sorting technology called MULTI-PICK has been used to validate. The 6063 and 6082 alloys produced with scrap stream, which are commonly used for structural parts in the automotive sector, are analyzed with hydrogen analysis and PREFIL. Cast billets are evaluated considering extrusion. After extrusion, microstructures of the profiles are investigated with scanning electron microscopy (SE), transmission electron microscopy (TE) and electron backscatter diffraction (EBSD). Their mechanical properties and anisotropic behaviors are investigated with tensile testing in different orientations. Additionally, an alternative alloy called 6111 has been studied to replace the target alloys with low critical raw material (CRM) content. According to the findings, highly recycled 6xxx alloys can be used in the automotive industry without losing their existing properties. Furthermore, using alternative feedstock and retrofitted systems can decrease carbon footprint below 4 kgCeq/kgAl. Full article

The maritime sector is undergoing a profound transformation driven by disruptive technologies and global decarbonization objectives, placing new demands on Maritime Education and Training (MET) systems. Equipping maritime professionals with competencies for low-carbon shipping is now as critical as technological advancement itself. This study examines how disruptive technologies can be effectively integrated into MET frameworks to support environmental sustainability, using Panama as a representative case study of a major flag and maritime service state. A mixed-methods approach was adopted, combining a structured literature review, expert surveys, and a multi-criteria decision-making analysis based on the Analytic Hierarchy Process (AHP). The findings reveal a significant misalignment between existing MET curricula and the competencies required for decarbonized maritime operations. Key gaps include limited training in alternative fuels, emissions measurement and reporting, energy-efficient technologies, digital analytics, and regulatory compliance. Stakeholders also reported fragmented training provision, uneven access to emerging technologies, and weak coordination between academia, industry, and regulators, particularly in developing contexts. The results highlight the urgent need for curriculum reform and stronger cross-sector collaboration to align MET with evolving technological and regulatory demands. The study provides an applied, evidence-based framework for MET reform, with insights transferable to other systems facing similar decarbonization challenges. Full article

South Africa’s manufacturing sector, a driving force for sustainable development, faces a profound challenge in decarbonizing without deindustrializing. This study provides an optimized, scenario-based assessment of the sector explicitly aligned with its Just Energy Transition Partnership (JETP) objectives. A novel framework is applied, integrating an extended Kaya–Logarithmic Mean Divisia Index (Kaya–LMDI) decomposition with scenario forecasting and Genetic Algorithm (GA) optimization. The decomposition disaggregates a conventional carbon intensity (CI) driver to include Electrification Share (ELE), Renewable Share (REN), and a newly defined Residual Carbon Factor (RCF) that captures direct fossil fuel use for industrial process heat. Historical analysis (2002–2022) shows that emissions growth was primarily driven by the RCF (224.1 MtCO₂, 160%) and Economic Activity (187.5 MtCO₂, 134%), partly offset by gains in Energy Intensity (−141.8 MtCO₂, 101.35%) and REN (−202.2 MtCO₂, −144.53%). Carbon emissions projections to 2040 reveal a critical sustainability trilemma: the Just Transition accelerated scenario (JTAS), despite achieving rapid renewable deployment, increases emissions by 469% as economic growth overwhelms decarbonization efforts. Conversely, the mathematically optimal (GA) pathway achieves a 90.8% reduction but only through structural contraction that implies socially unsustainable deindustrialization. This tension exposes the systemic limits of incremental decarbonization and underscores that a truly sustainable pathway requires transcending this binary choice by directly addressing the fossil fuel substrate of industrial production. Full article

Carbon emission reduction in the construction industry is pivotal for global carbon emission reduction, yet the lack of coordination mechanisms within the sector limits its effectiveness. This study examines the Yangtze River Economic Belt from 2010 to 2022, capturing the spatial and temporal evolution characteristics and key influencing factors of carbon emission efficiency in the construction industry (CEECI) to achieve coordinated emission reduction. Using the super-efficiency Slack-Based Measure (SBM) model and the Malmquist–Luenberger (ML) index, the study analyzes changes in CEECI, revealing significant regional variations: downstream, midstream, and upstream regions demonstrated average values of 1.10, 1.00, and 0.68, respectively. Resource redundancy is a major issue affecting CEECI, with energy redundancy rates exceeding 20%. The ML index indicates continuous improvement in CEECI, with technological change (TC) contributing the most to this improvement, as shown by index decomposition. Spatial analysis using Moran’s index (Moran’s I) revealed significant positive spatial autocorrelation, with distinct “high-high” (H-H) and “low-low” (L-L) clustering patterns, suggesting that regions with high CEECI positively influence their neighbors. Finally, we built a spatial econometric model to identify key influencing factors, including industrialization level, construction industry production level, energy consumption structure, human resources, and internal innovation levels, which directly or indirectly impact CEECI to varying degrees. These findings highlight the importance of regional coordination and targeted policy interventions to enhance carbon emission efficiency in the construction industry, addressing resource redundancy and leveraging technological advancements to contribute to global carbon reduction goals. Full article

Polyurethanes (PUs) are indispensable polymeric materials widely employed across diverse industrial sectors due to their excellent thermal stability, chemical resistance, adhesion, and mechanical durability. However, the intrinsic three-dimensional crosslinked network that underpins their performance also presents a fundamental barrier to reprocessing and recycling. Consequently, most end-of-life PU waste is currently managed through landfilling or incineration, resulting in significant resource loss and environmental impact. To address these challenges, this review presents an integrated perspective on sustainable PU systems by unifying green synthesis strategies with closed-loop recovery approaches. First, recent advances in bio-based polyols and phosgene-free isocyanate synthesis derived from renewable resources—such as plant oils, carbohydrates, and lignin—are discussed as viable means to reduce dependence on petrochemical feedstocks and mitigate toxicity concerns. Next, emerging chemical recycling methodologies, including acidolysis and aminolysis, are reviewed with a focus on the selective recovery of high-purity monomers. Finally, PU vitrimers and dynamic covalent polymer networks (DCPNs) based on urethane bond exchange reactions are examined as reprocessable architectures that combine thermoplastic-like processability with the mechanical robustness of thermosets. By integrating synthesis, recovery, and reuse within a unified framework, this review aims to outline a coherent pathway toward establishing a sustainable circular economy for PU materials. Full article

In recent years, Ammonia has emerged as a promising carbon-free fuel alternative, offering considerable potential to reduce CO₂ emissions and contribute to the decarbonization of the transportation industry. This study focuses on the economic feasibility and market price of ammonia now and in the future, highlighting the necessary infrastructure for emission-free transport operation. The project compares various production pathways for alternative fuels including hydrogen, ammonia, methanol, LNG, and diesel, considering both “green” and “gray” production methods. A key output of this research is the development of a flexible cost calculation tool, which allows users to simulate various scenarios by adjusting variables to ensure the continuity of the project. This tool enables dynamic analysis of future fuel prices and operational costs, accounting for the fluctuating electricity prices for green ammonia production and the long-term rise in CO₂ prices. Moreover, the study provides detailed cost modeling, infrastructure requirements, and refueling options for ammonia in comparison to other fuels. The findings indicate that ammonia is a promising long-term option for the maritime sector. While the adaptation to ammonia-based engines remains in the research phase, the long-term benefits of lower emissions and operating costs justify the investment in the necessary research and infrastructure, such as storage and refueling facilities. Full article

Pear cultivation in Greece, with an annual production of approximately 81,000 tonnes, constitutes a significant segment of the national fruit industry, particularly in Northern regions such as Macedonia and Thessaly. Despite ranking 8th in the EU in terms of pear production, Greece’s cultivated area is slightly declining, and adoption of smart agriculture technologies (SAT) remains limited. In this context, the present study investigates the preferences, patterns, and barriers of SAT adoption within the Greek pear sector, aiming to lay the groundwork for more effective digital transformation in the agri-food domain. Using a structured interview-based survey, data were collected from 30 pear growers, revealing critical insights into the technological landscape of the sector. A central challenge that emerged was the insufficient internet connectivity in rural farming areas, highlighting the urgent need for improved digital infrastructure to support SAT deployment. Furthermore, the study emphasizes the importance of targeted education and awareness programs to bridge the digital knowledge gap among pear farmers. An especially notable finding concerns the role of the chosen tree training system in influencing SAT uptake: more than 50% of adopters utilize the palmette training system, suggesting a strong correlation between orchard design and technological readiness. Among the SAT categories, Data Analytics and Farm Management Software were the most widely adopted, a trend partly driven by attractive governmental subsidies of €30 per hectare. Importantly, all respondents who had implemented SAT (100%) reported a measurable increase in farm income, reinforcing the technologies’ impact on productivity and profitability. Foremost among the challenges encountered is the deficit in technical knowledge and training. In conclusion, this study offers a comprehensive overview of Greek pear producers’ perceptions, challenges, and emerging opportunities related to smart agriculture. Full article

The construction sector generates a substantial proportion of Australia’s total solid waste, underscoring the urgent need for sustainable and circular resource management approaches to mitigate environmental impacts. This study evaluates the environmental performance and circularity potential of construction and demolition waste (C&DW) management across five Australian states. Three representative building cases were modelled using both national-average and state-specific recycling rates and electricity generation mixes. A Life Cycle Assessment (LCA) was conducted to compare two end-of-life pathways: landfill and recycling. Key parameters, including transport distance and substitution ratio, were also examined to assess their influence on carbon outcomes. The results show that regional variations in electricity generation mix and recycling rate have a strong influence on the total Global Warming Potential of C&DW management. States with cleaner electricity grids and higher recycling rates, such as South Australia, exhibited notably lower recycling-related emissions than those relying on fossil-fuel-based power. The findings highlight the importance of incorporating regional characteristics into sustainability assessments of C&DW management and provide practical insights to support Australia’s transition toward a circular and low-carbon construction industry. Full article

The automotive industry’s use of aluminum alloys continues to rise, driven by efforts to reduce vehicle weight—and thus fuel consumption—amid growing demand for larger vehicles such as SUVs, as well as the accelerating shift to electric vehicles and the expanding global vehicle fleet. These trends create major challenges for the aluminum sector. This paper provides a narrative literature review of available and published data, primarily from the period 2020–2025, examining new trends, challenges and opportunities regarding the implementation of recycled aluminum as a substitute for primary aluminum in the European automotive industry. The goal is to develop a discussion based on the answer to the following three issues: (1) What opportunities exist for increasing the production of recycled aluminum, given the imperative to conserve diminishing raw materials required for primary aluminum production? (2) What methods could enhance the obtaining of recycled aluminum over primary aluminum? (3) How might the technological barriers that hinder the wider use of recycled aluminum be overcome? This review finds that recycled aluminum availability in the EU automotive sector is improving due to rising demand for recycled material over primary aluminum—supported by a steadily growing scrap supply—alongside the development of advanced recycling strategies capable of producing high-purity recycled alloys. Full article

Objectives: The study aims to assess the strategies used to estimate antimicrobial consumption (AMC) and the barriers encountered in data collection. It also addresses the perception about AMC based on the World Health Organization (WHO) definition. Methodology: The qualitative study adhered to the standard consolidated criteria for reporting qualitative studies (COREQ) guidelines. It involved stakeholders from diverse sectors, i.e., regulatory bodies, the pharmaceutical industry, international health organizations, policy experts, medical professionals, veterinary doctors, and academia (nursing, medicine, and pharmacy). A total of 37 in-depth interviews were conducted using a semi-structured interview schema. The interviews were recorded and transcribed verbatim. Codes were generated afterward and organized into themes. Results: Data analysis yielded five themes consisting of (i) Perception about Antimicrobial Consumption, AWaRe (Access, Watch, Reserve) classification and related terms, (ii) Antimicrobial Consumption: Policy Design, (iii) Data management and record keeping for the Estimation of Antimicrobial Consumption, (iv) Levels of Estimation for Antimicrobial consumption and Organizations, and (v) Challenges and suggested solutions in estimation of AMC: One health approach is the way forward. Conclusions: The study concluded that AMC and AMR are two sides of the same coin. The solution to AMR and excessive AMC is to re-evaluate the policy and implement legislation strictly. Efforts focused on irrational prescribing and unsupervised OTC sales of antimicrobials. This will help in reducing the consumption of broad-spectrum antimicrobials. Full article

To address the pervasive challenges of resource inefficiency and static management in the hospitality sector, this study proposes a novel management framework that synergistically integrates Model Predictive Control (MPC) with Green Human Resource Management (GHRM). Methodologically, the framework establishes a dynamic closed-loop architecture that cyclically links environmental sensing, predictive optimization, plan execution and organizational learning. The MPC component generates data-driven forecasts and optimal control signals for resource allocation. Crucially, these technical outputs are operationally translated into specific, actionable directives for employees through integrated GHRM practices, including real-time task allocation via management systems, incentives-aligned performance metrics, and structured environmental training. This practical integration ensures that predictive optimization is directly coupled with human behavior. Theoretically, this study redefines hospitality operations as adaptive sociotechnical systems, and advances the hospitality energy-saving management framework by formally incorporating human execution feedback, predictive control theory, and dynamic optimization theory. Empirical validation across a sample of 40 hotels confirms the framework’s effectiveness, demonstrating significant reductions in daily average water consumption by 15.5% and electricity usage by 13.6%. These findings provide a robust, data-driven paradigm for achieving sustainable operational transformations in the hospitality industry. Full article

As sustainability becomes a strategic priority, the Information Technology (IT) sector faces pressure on both reducing its environmental impact and leading in innovation. This study examines how Green Human Resource Management (GHRM) practices influence employees’ Green IT Attitudes (GITA) and beliefs within the IT industry. Guided by the Belief–Action–Outcome (BAO) framework, it explores how HR strategies can foster eco-conscious mindsets that support sustainable behaviour. A quantitative cross-sectional design was used, collecting data through a validated questionnaire. The study was conducted in Australia, focusing on IT professionals employed. Responses from 112 IT professionals, determined through G*Power sample estimation, were analysed using SPSS 28.0.1 with regression techniques to assess the relationship between GHRM practices and environmental attitudes and beliefs. Results indicate that GHRM practices have a modest but significant positive effect on employees’ green IT attitudes and beliefs, supporting the view that structured HR initiatives can shape sustainability-driven mindsets. The findings emphasize the strategic role of HR in embedding sustainability within organizational culture, particularly in technology-driven environments. The study offers practical guidance for IT organizations aiming to integrate sustainability into internal systems by leveraging HRM. Future research should examine moderating variables and long-term behavioural effects, enhancing our understanding of sustainability-focused HRM in the digital era. Full article