Search Results (53)

With the current acceleration of climate change, there is a global demand for sustainable development and carbon emission reduction. As a major link in the global supply chain, the logistics industry’s green and low-carbon transformation has become a critical breakthrough in achieving the objective of reducing carbon emissions. This study develops a multidimensional assessment index method for the green logistics level. The study selects 51 major economies worldwide from 2000 to 2022 as research subjects. The cloud model–entropy value–TOPSIS method is applied to measure the green logistics level. The results of the green logistics level are analyzed from the perspectives of developed and developing countries, and their spatiotemporal evolution characteristics are explored. The study shows that (1) the green logistics level in developed countries is relatively high, mainly due to policy-driven, core technology advantages. However, they continue to encounter issues, such as regional imbalance and excessive green costs. (2) The green logistics level in developing countries is in the middle to lower level, limited by technological dependence, outdated infrastructure, and so on. They are generally caught in a “high-carbon lock-in” situation. (3) From the perspective of time, the global level of green logistics shows a rising trend year by year. The peak of the kernel density curve of the green logistics level is characterized by an “I” shape. There is a significant disparity in each country’s green logistics level, although it is narrowing every year. (4) From the spatial perspective, the green logistics level in each country shows a rising trend year by year vertically, while the horizontal disparity between countries is enormous. The development of the green logistics level between continents is unbalanced. The study presents several recommendations, including boosting technology transfer, giving financial support, strengthening international cooperation, and developing green infrastructure, to promote the global logistics industry’s green and low-carbon transformation to accomplish sustainable development goals. Full article

In a dynamic global market, platinum-group metals (PGMs), particularly palladium, are in high demand across various industries due to their unique properties. Palladium plays a crucial role in environmentally friendly technologies, such as catalytic converters, which mitigate harmful automotive emissions. Additionally, it is essential for clean energy production, particularly in hydrogen generation, which makes palladium a critical resource for building a sustainable and secure supply chain. This study evaluates the prospects of the palladium market through strategic analysis, focusing on the Russian mining and metals company PJSC MMC Norilsk Nickel. The research employs strategic and industry analysis methods to examine palladium production, market dynamics, and technological advancements, as well as emerging applications in the context of a green economy. The article analyzes the economics of palladium production, including price volatility driven by stringent environmental regulations and the rising adoption of electric vehicles. The palladium market faces challenges such as a constrained resource base, supply disruptions due to sanctions, price instability, and growing demand from key sectors, particularly the automotive industry. Nevertheless, innovation-driven trends offer promising opportunities for market growth, aligning with sustainable development principles and the transition toward a green, low-carbon economy in both established and emerging markets. As a key scientific contribution, this study proposes a modified methodological approach to industry analysis, enabling the assessment of a mining and metals company’s competitive sustainability in the palladium market over the medium and long term. Furthermore, the research models the life cycle of palladium as a commodity, considering evolving market trends and the rapid development of new industries within the green economy. Full article

One of the core objectives of the European Green Deal in pursuing climate neutrality and sustainable development is the decarbonization of high-impact sectors. Among the most polluting is the fast fashion industry, driven by linear business models that must urgently transition to circular economy frameworks and decarbonized supply chains. Fast fashion poses significant environmental and social challenges due to its high greenhouse gas emissions, excessive resource consumption, and substantial waste generation. To foster greater sustainability within the sector, this study examines environmental indicators defined by the European Sustainability Reporting Standards (ESRS), in accordance with the EU’s Corporate Sustainability Reporting Directive (CSRD) 2022/2464. Aligned with the Global Reporting Initiative (GRI), these standards aim to harmonize sustainability disclosures and enable better decision-making across environmental, social, and governance (ESG) dimensions throughout Europe. This research focuses on five key environmental aspects—climate change, pollution, water resource management, biodiversity, and circular economy/resource use—across four leading fast fashion brands: Mango, Zara, H&M, and Shein. Using an exploratory web-based methodology, this study evaluates how these companies disclose and implement ESG strategies in their supply chains. The central aim is to assess the sustainability and resilience of their operations, with particular emphasis on communication strategies that support the transition from linear to circular business models. Ultimately, this study seeks to highlight both the progress and persistent challenges faced by the fast fashion industry in aligning with ESG and ESRS requirements. Full article

The development of new technologies for the production of renewable energy is fundamental to reducing greenhouse gas emissions. Therefore, the search for new energy generation methods that are environmentally responsible, socially rational, and economically viable is gaining momentum in order to mitigate carbon footprint. The aviation sector is responsible for a significant fraction of greenhouse gas emissions; for this reason, the decarbonisation of this sector must be investigated using biorefinery models. This study presents a mixed-integer linear programming (MILP) model for optimising the design and configuration of the supply chain in different states of Brazil for the production of sustainable aviation fuel (SAF) and green diesel and gasoline, using microalgae cultivated in sugarcane vinasse as the raw material. The technology of hydrothermal liquefaction was assessed in terms of its capacity to convert microalgae without need for the energy-intensive drying step. The MILP model was developed in the LINGO v.20 software using a library of physical and economic process models. We consider the selection of processes based on the object of total minimum cost, with optimal production plant scaling and regional supply chain design, including an assessment of resources and final product distribution. A case study was implemented in Brazil, considering different regions of the country and its local demands for fuels. São Paulo is the most profitable state, with a cash flow of 1071.09 and an IRR of 36.19%, far outperforming the rest. Transport emissions alone represent between 0.6 and 8.6% of emissions generated by the model. The costs of raw materials, mainly hydrogen (57%) and electricity (27%) represent the main costs evaluated in the model. The production cost (MUS$/TJ biofuel) is in the range of 0.009–0.011. Finally, changes in the cost of electricity have the greatest impact on the model. Full article

As China’s economy transitions to high-quality development, the traditional growth model proves inadequate for current enterprise challenges. Optimizing resource allocation and cultivating new quality productive forces (NQP) constitute critical enablers of green supply chain collaboration and sustainable business practices. Green supply chain (GSC) collaboration synergizes economic-environmental performance while advancing sustainability. Using longitudinal data (2018–2022) from China’s A-share listed firms, this study examines NQP’s catalytic effects on GSC integration. We operationalized NQP through tripartite metrics (labor inputs, labor objects, and digitized labor processes) and developed a multi-dimensional assessment framework for GSC management integrating economic-environmental criteria. The degree of coupling synergy, calculated through the coupling degree and comprehensive development index, serves as a quantitative measure of GSC collaboration, allowing for a precise assessment of NQP advancement effects. Results demonstrate a significant positive association between NQP development and GSC collaborative performance. Heterogeneity analysis revealed differential impacts, with stronger effects in non-SOEs, technology-intensive sectors, and environmentally sensitive industries. Supply chain digitalization exhibited a moderating effect, strengthening NQP’s influence on GSC outcomes. This research addresses methodological gaps in GSC collaboration measurement and provides novel insights into how NQP drives its synergistic integration. Furthermore, it delivers practical guidance for enterprises to accelerate NQP adoption, optimize GSC partnerships, and operationalize sustainability initiatives. Full article

This paper provides a system-level and dimensional analysis of green hydrogen, assessing its realistic deployment potential within broader energy transitions. While green hydrogen—produced via electrolysis using renewable electricity—is often promoted as a versatile decarbonization solution for industry, mobility, and civil applications, its practical implementation is constrained by high energy consumption, conversion inefficiencies, and complex supply chain requirements. This study highlights typical energy demands across key sectors and evaluates the scale of the renewable infrastructure needed to support them, offering quantitative insight into the feasibility of large-scale hydrogen integration. It also reflects current technological maturity, noting that many promising solutions remain far from industrial readiness. Finally, the paper underscores the importance of targeted policies and bankable investment models to foster the development of hydrogen ecosystems, emphasizing that its role should be framed within a selective, evidence-based strategy that focuses on high-impact applications. The analysis identifies key dimensional challenges, including the magnitude of renewable energy capacities required for sector-wide hydrogen integration and the scale of infrastructure investments needed to bridge current gaps. Full article

Hydrogen energy, characterized by its abundant resources, green and low-carbon attributes, and wide-ranging applications, is a critical energy source for achieving carbon peaking and carbon neutrality goals. The operational efficiency of the hydrogen energy industrial chain is pivotal in determining the security of its supply chain and its contribution to China’s energy transition. This study investigates the efficiency of China’s hydrogen energy industrial chain by selecting 30 listed companies primarily engaged in hydrogen energy as the research sample. A three-stage data envelopment analysis (DEA) model is applied to assess the industry’s comprehensive technical efficiency, pure technical efficiency, and scale efficiency. Additionally, kernel density estimation is utilized to analyze efficiency trends over time. Key factors influencing efficiency are identified, and targeted recommendations are provided to enhance the performance and sustainability of the hydrogen energy industrial chain. These findings offer valuable insights to support the development and resilience of China’s hydrogen energy industry. Full article

The increasing demand for sustainable business practices has highlighted the need for a robust and risk-aware green supplier selection framework. Traditional supplier evaluation methods primarily focus on cost, quality, and delivery performance but often fail to incorporate sustainability and risk factors effectively. This study proposes an improved AHP-FMEA method that integrates the Analytic Hierarchy Process (AHP), entropy weight method, and Failure Mode and Effects Analysis (FMEA) to enhance decision-making in green supplier selection. The AHP method determines subjective criteria weights, while the entropy method adjusts these weights objectively to reduce bias. The FMEA approach incorporates risk assessment by identifying and quantifying potential supplier failures, ensuring a more comprehensive evaluation. A case study is conducted to validate the proposed model, comparing it with classical AHP and AHP-Entropy methods. The results show that incorporating risk factors significantly influences supplier ranking, demonstrating the model’s ability to provide a more scientific, objective, and risk-conscious evaluation. The proposed approach enhances the accuracy and reliability of green supplier selection, making it a valuable tool for sustainable supply chain management. Full article

The building sector accounts for one-third of global greenhouse gas emissions, representing a significant environmental challenge in the 21st century. Green supply chain management is considered an effective approach to achieving green transformation in the construction industry. However, the green building supply chain (GBSC) involves multiple stakeholders, necessitating integrated consideration of various participants to ensure efficient GBSC implementation. In this context, and accounting for consumer green preferences, this paper identifies the government, enterprises, and consumers as key stakeholders. A tripartite evolutionary game model is established, and the influence of the participants’ strategic choices on the system equilibrium is analyzed. The model’s validity was assessed through sensitivity analysis and by comparing its outputs with findings from the existing literature. The findings show that: (1) Significant interdependence exists among GBSC participants. (2) The system will eventually tend toward an equilibrium characterized by active enterprise implementation and consumer green consumption, reducing the need for government intervention. (3) The sensitivity analysis shows that green consumption is significantly affected by the extra cost and perceived environmental benefits. These conclusions suggest that governments should build a collaborative governance system, implement dynamic and precise supervision of enterprises in stages, and optimize the incentive design for consumers to promote the implementation of the green building supply chain. Full article

The demand for green hydrogen (H₂) and related technologies is expected to increase in the coming years, driven by climate changes and energy security of supply issues, amid the European and global energy crises. The European Green Deal and REpowerEU Plan have identified H₂ as a key pillar for reaching climate neutrality by 2050 and for the intensification of hydrogen delivery targets, bringing the large-scale adoption of hydrogen production and applications, and stressing the need for a skilled workforce in emergent H₂ markets. To that end, the H2Excellence project will establish a Platform of Vocational Excellence in the field of fuel cells and green hydrogen technologies, with an educational and training scheme to tackle identified skill gaps and to implement life-long learning opportunities. This project aims to become a European benchmark in training and knowledge transfer, incorporating the entire hydrogen value chain. The work is supported by the Knowledge Triangle Model, integrating education, research, and innovation efforts to build a dynamic ecosystem in the green hydrogen sector. In this work, activities conducted so far by LNEG as a project partner and expected impacts are highlighted. Those activities are based on a stakeholder needs assessment conducted by project partners and on the knowledge and experience accumulated in research activities developed in the Materials for Energy research area. Full article

As an important pillar of the national economy, the green transformation of SMEs is the key to promoting sustainable economic development. However, SMEs generally face issues such as information opacity and high operational risks, which make it difficult for them to obtain traditional financing support, thereby hindering green development. Green Supply Chain Finance has opened up new financing channels for SMEs, but the accuracy of credit risk evaluation remains a bottleneck that limits its widespread application. This paper constructs a credit risk evaluation index system that integrates multiple sources of information, covering factors such as the situations of SMEs themselves, stakeholder feedback, and expert ratings. It compares and analyzes the performance of the genetic algorithm-optimized random forest model (GA-RF), the BP neural network, the support vector machine, and the logistic regression model in credit risk evaluation. The empirical results indicate that the GA-RF model is significantly better than the other models in terms of accuracy, precision, and F1 score, and has the highest AUC value, making it more effective in identifying credit risk. In addition, the GA-RF model reveals that the asset–liability ratio, the time of establishment, the growth rate of operating revenue, the time of collection of accounts receivable, the return on net assets, and daily shipments are the key indicators affecting the credit risk assessment. Full article

Background: Supply chains operate under the changing influences of multiple external and internal factors. Sustainable supply chain development requires an assessment of these factors, as well as drivers and barriers. Various sustainability assessment criteria, methods, and models based on the consideration of the influence of different factors are used depending on the type and structure of the supply chain. Methods: The combination of DEMATEL and CRADIS multi-criteria methods is applied to rank the efficiency of drivers for achieving sustainable development goals, both for the supply chain as a whole and for each of its structural elements. Results: This study proposes a system of drivers for sustainable supply chain development. The peculiarity of the used supply chain model is the universality of its structure, which ensures the realization by the structural elements of the chain of all known functional areas of logistics. A framework for sustainable supply chain drivers’ multi-criteria assessment based on the use of the original two-level system of drivers’ assessment criteria is developed. Conclusions: The results of the supply chain sustainability drivers’ ranking and the framework developed by the authors are intended to justify decisions on the green logistics methods and instrument selection. Full article

Emerging social, economic, and environmental concerns bring operational challenges and the worldwide economy has seen magnifying pressure to incorporate environmental performance (EP) as a part of strategic decision. Studies in the field of environmental management and, particularly, in the areas of green practices, zero waste, and green innovation have suggested that, if executed properly, these organizations are able to promote EP. Under these conditions, organizations’ practices and mechanisms that ensure the enhancement of the EP of these business organizations have gained the wider attention of researchers and management. Focused on the environment and social responsibility, this study explores the complex relationships within sustainable green supply chain management (GSCM) and explores whether GSCM practices significantly impact both zero waste management and green innovation. The analysis also studies whether there are possible beneficial links between zero waste management, green innovation and environmental performance (EP). Additionally, through assessing the level to which these items come together in sustainable strategic actions, the paper shows the correlation among four important topics: GSCM practices, green innovation (GI), zero waste management, and EP. This study explores the relations between zero waste management and EP as well as green innovation and EP, examining whether these aspects of green practices have a positive relationship with effective waste management techniques in the presence of GSCM practices. The paper analyses interactions between GSCM practices and EP, and the mediation role of zero waste management and GI. Moreover, the moderating role of green knowledge sharing (GKS) also been tested. A total of 389 managers in the manufacturing sector completed the survey and the results were analyzed applying SPSS 25.0 and partial least squares structural equation modeling (PLS-SEM). The findings confirmed a significant association among GSCM practices, GI, zero waste management, GKS, and EP. Furthermore, findings also revealed that zero waste management GI has a positive intervention role between GSCM practices and EP. GSCM practices facilitate the promotion of EP by incorporating eco-design, green purchasing, new techniques for production or processes, and green marketing that ensures waste reduction and recycling practices. Full article

The evaluation and selection of green suppliers, as an important part of the process of creating a green supply chain, has received attention from enterprises and scholars. However, the evaluation and selection of green suppliers is a complex multi-criteria decision-making problem, and the evaluation information provided by experts is often ambiguous, so it is difficult to obtain reasonable and accurate assessment results. Therefore, this paper proposes a green supplier evaluation model of Pythagorean fuzzy approximation of ideal solution ranking (Technology for Order Preference by Similarity to Ideal Solution, or TOPSIS). The model utilizes Pythagorean fuzzy sets to deal with fuzzy expert opinions and the TOPSIS method to obtain the ranking of alternative suppliers. In addition, the model calculates the criterion weights using the entropy weighting method in the fuzzy environment. Finally, the model proposed in this paper is used to help Company A determine the optimal green supplier selection object, and the effectiveness and superiority of the model are verified through a comparative analysis with existing green supplier evaluation models. Full article

This research presents a system dynamics model to study the interaction among demand and supply evolutions, government regulations, sustainable adoption trends, investments in different decarbonization technologies, and environmental requirements for the European Aluminum Rolled Product Supply Chain (ARPSC). It allows stakeholders to assess the quantitative impact of investing in decarbonization technologies on supply chain sustainability. Investing in decarbonization technologies reduces greenhouse gas (GHG) emissions. The most substantial GHG emission reductions can be achieved if upstream ARPSC actors invest according to an aggressive investment strategy between 2031 and 2040. However, even with an aggressive investment strategy, investing in decarbonization technologies alone is likely to be insufficient to achieve the European Green Deal goals. Furthermore, barriers to investment in decarbonization technologies and a low rate of progress in doubling the European Union’s circularity rate may put extra stress on achieving the European Green Deal goals for the European ARPSC. Instead, ARPSC actors will additionally need to optimize the recycling of aluminum rolled products and adopt strategies for resource sufficiency, e.g., by sharing cars and using packaging multiple times. Full article