Search Results (359)

The growing need to improve the management of end-of-life vehicle (ELV) waste and mitigate its environmental impact is a global concern. One promising approach to enhancing the recyclability of these vehicles is leveraging synergies between the automotive and construction industries as part of a circular economy strategy. In this context, ELV waste emerges as a valuable source of secondary raw materials, enabling the development of sustainable innovations that capitalize on its physical and mechanical properties. This paper aims to develop and evaluate construction industry composites incorporating waste from ELV carpets, with a focus on maintaining or enhancing performance compared to conventional materials. To achieve this, an experimental program was designed to assess cementitious composites, specifically subfloor mortars, incorporating automotive carpet waste (ACW). The results demonstrate that, beyond the physical and mechanical properties of the developed composites, the dynamic stiffness significantly improved across all tested waste incorporation levels. This finding highlights the potential of these composites as an alternative material for impact noise insulation in flooring systems. From an academic perspective, this research advances knowledge on the application of ACW in cement-based composites for construction. In terms of managerial contributions, two key market opportunities emerge: (1) the commercial exploitation of composites produced with ELV carpet waste and (2) the development of a network of environmental service providers to ensure a stable waste supply chain for innovative and sustainable products. Both strategies contribute to reducing landfill disposal and mitigating the environmental impact of ELV waste, reinforcing the principles of the circular economy. Full article

The logistics industry faces challenges from evolving consumer expectations, technological advances, sustainability demands, and market disruptions. Logistics collaboration is in theory perceived as one of the most promising solutions to solve these issues, but here are still a lot of challenges that needs to be better understood and addressed. While vertical collaboration among supply chain actors is well advanced, horizontal collaboration among competing service providers remains under-explored. This study developed a novel methodology based on the COM-B behaviour-change framework to better understand the main challenges, opportunities, capabilities and drivers that would motivate competing companies to exploit the potential of horizontal logistics collaboration. A survey was designed and conducted among 71 logistics service providers in Slovenia, chosen for its fragmented market and low willingness to collaborate. Statistical analysis reveals cost reduction (M = 4.21/5) and improved vehicle utilization (M = 4.29/5) as the primary motivators. On the other hand, maintaining company reputation (M = 4.64/5), fair resource sharing (M = 4.20/5), and transparency of logistics processes (M = 4.17/5) all persist as key enabling conditions. These findings underscore the pivotal role of behavioural drivers and suggest strategies that combine economic incentives with targeted trust-building measures. Future research should employ experimental designs in diverse national contexts and integrate vertical–horizontal approaches to validate causal pathways and advance theory. Full article

The livestock sector is a significant contributor to the economy and rural livelihoods, but it is exposed to high risk across the supply chain, which is detrimental and needs to be addressed for sustainable development. Therefore, this study aimed to identify the major risk mitigation strategies (RMSs) and associated factors that affect their adoption. This study conducted a comprehensive literature review to identify the eight major RMSs and prioritized them through an analytical hierarchical process (AHP). Thereafter, a multivariate probit (MVP) model was developed to identify the factors affecting the adoption of major RMSs. The primary RMSs are livestock insurance, vaccination of livestock, and advisory/extension services. Further, the multivariate probit regression analysis shows that ‘age’, ‘social category’, ‘economic status’, ‘educational level’, ‘income level’, ‘the total number of animals’, and ‘perceived risk of foot and mouth disease’ are significant factors that influence the adoption of RMSs. This study’s findings will be useful for livestock supply chain partners to mitigate the risks along the livestock supply chain. This research will also help policymakers to develop policies/plans for incorporating these RMSs by considering the influencing associated factors. Full article

Traditional seed supply chains face several hidden risks. Certain regulatory departments tend to focus primarily on entity circulation while neglecting the origin and accuracy of data in seed quality supervision, resulting in limited precision and low credibility of traceability information related to quality and safety. Blockchain technology offers a systematic solution to key issues such as data source distortion and insufficient regulatory penetration in the seed supply chain by enabling data rights confirmation, tamper-proof traceability, smart contract execution, and multi-node consensus mechanisms. In this study, we developed a system that integrates blockchain and neural networks to provide seed traceability services. When uploading seed traceability information, the neural network models are employed to verify the authenticity of information provided by humans and save the tags on the blockchain. Various neural network architectures, such as Multilayer Perceptron, Recurrent Neural Network, Fully Convolutional Neural Network, and Long Short-term Memory model architectures, have been tested to determine the authenticity of seed traceability information. Among these, the Long Short-term Memory model architecture demonstrated the highest accuracy, with an accuracy rate of 90.65%. The results demonstrated that neural networks have significant research value and potential to assess the authenticity of information in a blockchain. In the application scenario of seed quality traceability, using blockchain and neural networks to determine the authenticity of seed traceability information provides a new solution for seed traceability. This system empowers farmers by providing trustworthy seed quality information, enabling better purchasing decisions and reducing risks from counterfeit or substandard seeds. Furthermore, this mechanism fosters market circulation of certified high-quality seeds, elevates crop yields, and contributes to the sustainable growth of agricultural systems. Full article

In the face of economic, social, and environmental pressures, the issue of sustainable development has garnered widespread attention in the Logistics Service Supply Chain (LSSC) with risk attitudes under Technical Output Uncertainty. In this regard, this paper first constructs an optimal emission reduction investment game model for an LSSC composed of Logistics Service Integrators (LSIs) and Logistics Service Providers (LSPs) against the backdrop of Technical Output Uncertainty. To this end, it quantifies the participants’ risk attitudes using a mean-variance model to analyze optimal emission reduction investment decisions for centralized and decentralized LSSC under different levels of risk tolerance. Subsequently, it designs a joint contract with altruistic preferences for sharing emission reduction costs in the LSSC. This contract analyzes the parameter constraints for achieving Pareto optimization within the supply chain. Finally, the study employs a case simulation to analyze the changes in expected revenues for centralized LSSC and joint contracts under different risk tolerance levels. The study reveals that (1) in a centralized LSSC, under risk-neutral attitudes, there exists a unique optimal emission reduction investment, which yields the highest expected return from emission reduction. However, under risk-averse attitudes, the expected return is always lower than the optimal expected return under risk neutrality. (2) In a decentralized LSSC, the emission reduction investment decisions of the Logistics Service Providers are similar to those in a centralized LSSC. (3) Under risk-neutral attitudes, the cost-sharing and altruistic preference-based joint contract can also coordinate the risk-averse LSSC under certain constraints, and by adjusting the cost-sharing and altruistic preference parameters, the expected returns can be reasonably allocated. Full article

This study investigates the resilience of service supply chains and its role in promoting sustainable regional development in China. Based on data from 31 provinces between 2017 and 2023, we develop a multidimensional evaluation framework grounded in the structure, relationship, and subject model. Using entropy weighting, fuzzy-set qualitative comparative analysis, necessary condition analysis, and OLS regression, we identify three dominant configurations: cost-adaptive, cost-growth, and technology-driven. Among them, the cost-adaptive path remains statistically significant when tested against updated 2023 data. The findings reveal persistent regional disparities and demonstrate how context-specific strategies can shape service resilience under institutional and market variations. This study contributes to supply chain sustainability research by integrating recent empirical evidence with configurational analysis, offering practical policy insights for balancing efficiency, adaptability, and inclusive development. Full article

Heilongjiang Province, as China’s principal gateway for Russian timber imports, faces structural inefficiencies in the localization of wood-processing enterprises—characterized by ecological sensitivity, resource–industry mismatches, and uneven spatial distribution. To address these challenges, this study proposes a two-stage site selection framework that integrates Geographic Information Systems (GIS) with an enhanced Non-dominated Sorting Genetic Algorithm II (NSGA-II). The model aims to reconcile ecological protection with industrial efficiency by identifying optimal facility locations that minimize environmental impact, reduce construction and logistics costs, and enhance service coverage. Using spatially resolved multi-source datasets—including forest resource distribution, transportation networks, ecological redlines, and socioeconomic indicators—the GIS-based suitability analysis (Stage I) identified 16 candidate zones. Subsequently, a multi-objective optimization model (Stage II) was applied to minimize carbon intensity and cost while maximizing service accessibility. The improved NSGA-II algorithm achieved convergence within 700 iterations, generating 124 Pareto-optimal solutions and enabling a 23.7% reduction in transport-related CO₂ emissions. Beyond carbon mitigation, the model spatializes policy constraints and economic trade-offs into actionable infrastructure plans, contributing to regional sustainability goals and transboundary industrial coordination with Russia. It further demonstrates methodological generalizability for siting logistics-intensive and policy-sensitive facilities in other forestry-based economies. While the model does not yet account for temporal dynamics or agent behaviors, it provides a robust foundation for informed planning under China’s dual-carbon strategy and offers replicable insights for the global forest products supply chain. Full article

The latest research highlights the need for circularity in modern industrial supply chains, which is reflected in the decisions of European and global policymakers, as well as in the strategies of major stakeholders. Digital Twins are considered a principal catalyst in the transition to circularity, while real-world, accurate and timely data is a key factor in these supply chains. This emphasis on data highlights the central role of data analytics in extracting key insights and utilizing machine learning to propose sustainability initiatives in decentralized production ecosystems. In consequence, commercial solutions are being developed; however, a single solution might not address all requirements. In this work we present a comprehensive modular, scalable and secure analytics architecture, designed to expand the available components in commercial solutions by providing an intelligent layer to Digital Twins. Our approach integrates with the latest standards for international data spaces, interoperability and process models in distributed environments where multiple actors engage in co-opetition. The proposed architecture is implemented in a market-ready solution and demonstrated in two case studies, in Spain and in Greece. Validation results confirm that the analytics service delivers accurate, timely and actionable insights, while following open communication standards and sustainability guidelines. Our research indicates that companies implementing digital twin solutions using standardized connectors for interoperability can benefit by customizing the proposed solution and avoiding complex developments from scratch. Full article

Digital agriculture has rapidly developed in the last decade in many countries where the share of agricultural production is a significant part of the total volume of gross production. Digital agroecosystems are developed using a variety of IT solutions, software and hardware tools, wired and wireless data transmission technologies, open source code, Open API, etc. A special place in agroecosystems is occupied by electronic payment technologies and blockchain technologies, which allow farmers and other agricultural enterprises to conduct commodity and monetary transactions with suppliers, creditors, and buyers of products. Such ecosystems contribute to the sustainable development of agriculture, agricultural engineering, and management of production and financial operations in the agricultural industry and related industries, as well as in other sectors of the economy of a number of countries. The introduction of crypto solutions in the agricultural sector is designed to create integrated platforms aimed at helping farmers manage supply lines or gain access to financial services. At the same time, there are risks of illegal use of computing power for cryptocurrency mining—cryptojacking. This article offers a thorough risk assessment of cryptojacking attacks on endpoint systems, focusing on identifying critical vulnerabilities within IT infrastructures and outlining practical preventive measures. The analysis examines key attack vectors—including compromised websites, infected applications, and supply chain infiltration—and explores how unauthorized cryptocurrency mining degrades system performance and endangers data security. The research methodology combines an evaluation of current cybersecurity trends, a review of specialized literature, and a controlled experiment simulating cryptojacking attacks. The findings highlight the importance of multi-layered protection mechanisms and ongoing system monitoring to detect malicious activities at an early stage. Full article

The world is facing unprecedented sustainability challenges, and the circular economy (CE) can provide some solutions to promote more sustainable practices among companies. This study aimed at exploring, discovering, analyzing and synthetizing approaches related to the 10R principles, the CE principles and CE business models in the shipping sector in Finland. The research approach was based on qualitative research that aimed at identifying approaches related to the selected three main elements: (1) the 10R principles; (2) the CE principles; and (3) CE business models. The findings of this study suggest that most approaches that were identified were related to the following 10R principles: (1) replacement of products or making of products redundant (R0); (2) rethinking of products (R1); and (3) reduction in the use of resources in the manufacturing and use of products (R2). Only a few approaches could be identified that were related to the reuse of products (R3), the recycling of materials (R8) and recovery of materials (R9). There were typically no or only a few approaches identified that were related to the repair of products (R4), refurbishment of products (R5), remanufacturing of products (R6) and repurposing of products and their parts (R7). For many companies, there were no identified approaches related to the R3–R7 principles. Regarding the CE principles, the findings of this study suggest that quite a number of approaches were identified that were related to the circulation of products and materials and that many approaches were identified that were related to the elimination of waste and pollution. Typically only a few approaches were identified for the regeneration of nature. Regarding the CE business models, the findings suggest that quite a number of approaches were identified that were related to the circular supply models, supply chains and inputs, and there were many approaches for resource recovery. Only a few approaches were identified that were related to product use/life extension, sharing and sharing platforms, and product-as-a-service and product-service systems. Full article

Designing a sustainable supply chain network for perishable products is challenging due to their short shelf life and sensitivity to environmental conditions. These factors necessitate strict quality control and efficient logistics. The emergence of Internet of Things (IoT) technology has significantly improved supply chain operations by enabling real-time monitoring of environmental conditions. This helps maintain product quality and ensures timely deliveries. Additionally, using mixed fleets—comprising both electric and conventional vehicles—can reduce carbon emissions without compromising operational reliability. While previous studies have explored the application of IoT to enhance delivery efficiency and the use of mixed fleets to address environmental concerns, few have examined both technologies within a unified modeling framework. This study proposes a sustainable multi-period supply chain network for perishable products that integrates IoT technology and mixed fleets into an optimization framework. We develop a multi-objective location-inventory-routing model. The first objective minimizes total costs, including production, facility operation, inventory, transportation, carbon emissions, IoT deployment, and energy use. The second objective aims to maximize service levels, which are measured by product quality and on-time delivery. The model is solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). A case study based on real-world data demonstrates the model’s effectiveness. Sensitivity analysis indicates that balancing the emphasis on quality and delivery reliability leads to improved cost and service performance. Furthermore, while total costs steadily increase with higher demand, service levels remain stable, showcasing the model’s robustness. These results provide practical guidance for managing sustainable supply chains for perishable products. Full article

This paper presents a joint optimization framework for multi-period planning in a Manufacturing–Remanufacturing–Transport Supply Chain (MRTSC), focusing on carbon emission reduction and economic efficiency. A novel Mixed Integer Linear Programming (MILP) model is developed to coordinate procurement, production, remanufacturing, transportation, and returns under environmental constraints, aligned with carbon tax policies and the Paris Agreement. To address uncertainty in future demand and the number of returned used products (NRUP), a two-stage approach combining forecasting and optimization is applied. Among several predictive methods evaluated, a hybrid SARIMA/VAR model is selected for its accuracy. The MILP model, implemented in CPLEX, generates optimal decisions based on these forecasts. A case study demonstrates notable improvements in cost efficiency and emission reduction over traditional approaches. The results show that the proposed model consistently maintained strong service levels through flexible planning and responsive transport scheduling, minimizing both unmet demand and inventory excesses throughout the planning horizon. Additionally, the findings indicate that carbon taxation caused a sharp drop in profit with only limited emission reductions, highlighting the need for parallel support for cleaner technologies and more integrated sustainability strategies. The analysis further reveals a clear trade-off between emission reduction and operational performance, as stricter carbon limits lead to lower profitability and service levels despite environmental gains. Full article

(1) Background: With the deep integration of e-commerce and video technology, live-streaming marketing has emerged globally and maintained rapid growth. However, most of the current research on live-streaming e-commerce marketing focuses on merchants’ sales strategies and consumers’ purchase intentions, and there is relatively little research related to the risks of live-streaming e-commerce marketing. Nevertheless, with the development of live-streaming e-commerce marketing and its integration with technologies such as artificial intelligence and virtual reality (VR), live-streaming e-commerce marketing still faces challenges such as unclear subject responsibility, difficulty in verifying the authenticity of marketing information, and uneven product quality. It also harbors problems such as the ethical misbehavior of AI anchors and the excessive beautification of products by VR technology. (2) Methods: This study systematically analyzes the scenarios of live-streaming marketing to elucidate the mechanisms of risk formation. Utilizing fault tree analysis (FTA) and risk checklist methods, risks are identified based on the three core elements of live-streaming marketing: “people–products–scenes”. Subsequently, the Delphi method is employed to refine the initial risk indicator system, resulting in the construction of a comprehensive risk indicator system comprising three first-level indicators, six second-level indicators, and 16 third-level indicators. A hesitant fuzzy multi-attribute group decision-making method (HFMGDM) is then applied to calculate the weights of the risk indicators and comprehensively assess the live-streaming marketing risks in live broadcast rooms of three prominent celebrity anchors in China. Furthermore, a detailed analysis is conducted on the risks associated with the six secondary indicators. Based on the risk evaluation results, targeted recommendations are proposed. This study aims to enhance consumers’ awareness of risk prevention when conducting live-streaming transactions and pay attention to related risks, thereby safeguarding consumer rights and fostering the healthy and sustainable development of the live-streaming marketing industry. (3) Conclusions: The results show that the top five risk indicators in terms of weight ranking are: Ethical Risk of the AI Anchor (A4), VR Technology Promotion Risk (F3), Anchor Reputation (A1), Product Quality (D1), and Logistics Distribution Service Quality (D2). The comprehensive live-streaming marketing risk of each live broadcast room is Y > L > D. Based on the analysis results, targeted recommendations are provided for anchors, MCN institutions, merchants, supply chains, and live-streaming platforms to improve consumer satisfaction and promote sustainable development of the live-streaming marketing industry. Full article

The shipping industry, a cornerstone of global trade, faces emissions reduction challenges amid tightening environmental policies. Blockchain technology, leveraging distributed symmetric architectures, enhances supply chain transparency by reducing information asymmetry, yet its dynamic interplay with emissions strategies remains underexplored. This study employs symmetry-driven differential game theory to model four blockchain scenarios in port-shipping networks: no blockchain (N), port-led (PB), shipping company-led (CB), and a joint platform (FB). By solving Hamilton–Jacobi–Bellman equations, we derive optimal emissions reduction efforts, green investments, and blockchain strategies under symmetric and asymmetric decision-making frameworks. Results show blockchain adoption improves emissions reduction and service quality under cost thresholds, with port-led systems maximizing low-cost profits and shipping firms gaining asymmetrically in high-freight contexts. Joint platforms achieve symmetry in profit distribution through fee-trust synergy, enabling win–win outcomes. Integrating graph-theoretic principles, we have designed dynamic state equations for emissions and service levels, segmenting shippers by low-carbon preferences. This work bridges dynamic emissions strategies with blockchain’s network symmetry, fostering economic–environmental synergies to advance sustainable maritime supply chains. Full article

Cross-border e-commerce (CBEC) is rapidly growing as a global trade engine. Simultaneously, its rapid expansion also poses environmental challenges and worsens supply chain sustainability. Advanced information technology (IT) significantly enhances supply chain visibility and promotes cooperation, thereby improving the efficiency and sustainability of CBEC supply chains. However, the application of IT is accompanied by an increase in service costs, necessitating a comprehensive balance for enterprises. This paper constructs a CBEC supply chain consisting of an overseas supplier and two merchants, where one merchant adopts advanced IT to provide differentiated services. A game-theoretic model is employed to analyze the IT application decisions under price and service competition in supply chain members’ cooperative and non-cooperative scenarios. The results indicate that service differentiation generated by advanced IT is influenced by consumer preferences. Merely applying advanced IT may not necessarily improve competitiveness and efficiency, and may even lead to negative utility. When the products sold are similar and the service cost coefficient is constant, those who apply advanced IT to provide higher service levels can gain competitive advantages and obtain more profits. When the service differentiation between merchants is constant, CBEC supply chains implementing centralized strategies can achieve greater profits. Full article