Search Results (301)

Supplier selection is a crucial factor for ensuring compliance with the circular economy’s principles. Existing approaches often overlook the integration of circularity and risk assessment in supplier evaluation, limiting their effectiveness in achieving sustainability goals. This paper addresses this gap by applying suitable criteria and proposing a structured decision-making model for circular supplier selection. The model innovatively integrates Multi-Criteria Decision Analysis (MCDA) techniques with risk evaluation, providing a comprehensive framework for assessing suppliers in circular supply chains. By advancing the theoretical understanding of circular supplier selection, this research contributes to both academia and practice, reinforcing the alignment between supply chain decision-making and the Sustainable Development Goal (SDG), particularly Target 12.5. Full article

In 2022, the Russia–Ukraine conflict has severely impacted the EU’s energy supply chain, and the EU’s natural gas import pattern has begun to reconstruct, and exploring the spatiotemporal differentiation of EU natural gas trade and its driving factors is the basis for improving the resilience of its supply chain and ensuring the stable supply of energy resources. This paper summarizes the law of the change of its import volume by using the complex network method, constructs a multi-dimensional index system such as demand, economy, and security, and uses the geographic detector model to mine the driving factors affecting the spatiotemporal evolution of natural gas imports in EU countries and propose different sustainable development paths. The results show that from 2000 to 2023, Europe’s natural gas imports generally show an upward trend, and the import structure has undergone great changes, from pipeline gas dominance to LNG diversification. After the conflict between Russia and Ukraine, the number of import source countries has increased, the market network has become looser, France has become the core hub of the EU natural gas market, the importance of Russia has declined rapidly, and the status of countries in the United States, North Africa, and the Middle East has increased rapidly; natural gas consumption is the leading factor in the spatiotemporal differentiation of EU natural gas imports, and the influence of import distance and geopolitical risk is gradually expanding, and the proportion of energy consumption is significantly higher than that of other factors in the interaction with other factors. Combined with the driving factors, three different evolutionary directions of natural gas imports in EU countries are identified, and energy security paths such as improving supply chain control capabilities, ensuring export stability, and using location advantages to become hub nodes are proposed for different development trends. 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

Exploring the action mechanisms and enhancement pathways of the resilience of agricultural product green supply chains is conducive to strengthening the system’s risk resistance capacity and providing decision support for achieving the “dual carbon” goals. Based on theories such as dynamic capability theory and complex adaptive systems, this paper constructs a resilience framework covering the three stages of “steady-state maintenance–dynamic adjustment–continuous evolution” from both single and multiple perspectives. Combined with 768 units of multi-agent questionnaire data, it adopts Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the influencing factors of resilience and reveal the nonlinear mechanisms of resilience formation. Secondly, by integrating configurational analysis with machine learning, it innovatively constructs a resilience level prediction model based on fsQCA-XGBoost. The research findings are as follows: (1) fsQCA identifies a total of four high-resilience pathways, verifying the core proposition of “multiple conjunctural causality” in complex adaptive system theory; (2) compared with single algorithms such as Random Forest, Decision Tree, AdaBoost, ExtraTrees, and XGBoost, the fsQCA-XGBoost prediction method proposed in this paper achieves an optimization of 66% and over 150% in recall rate and positive sample identification, respectively. It reduces false negative risk omission by 50% and improves the ability to capture high-risk samples by three times, which verifies the feasibility and applicability of the fsQCA-XGBoost prediction method in the field of resilience prediction for agricultural product green supply chains. This research provides a risk prevention and control paradigm with both theoretical explanatory power and practical operability for agricultural product green supply chains, and promotes collaborative realization of the “carbon reduction–supply stability–efficiency improvement” goals, transforming them from policy vision to operational reality. Full article

What motivates industrial companies to decarbonise? While climate policy has intensified, the specific factors driving corporate decisions remain underexplored. This article addresses that gap through a mixed-methods study combining qualitative insights from a leading automotive supplier with quantitative data from over 800 manufacturing companies in Germany. The study distinguishes between internal motivators—such as risk reduction, future-proofing, and competitive positioning—and external drivers like regulation, supply chain pressure, and investor expectations. Results show that internal economic logic is the strongest trigger: companies act more ambitiously when decarbonisation aligns with their strategic interests. Positive motivators outperform external drivers in both influence and impact on ambition levels. For instance, long-term cost risks were rated more relevant than reputational gains or regulatory compliance. The analysis also reveals how company size, energy intensity, and supply chain position shape motivation patterns. The findings suggest a new framing for climate policy: rather than relying solely on mandates, policies should strengthen intrinsic motivators. Aligning business interests with societal goals is not only possible—it is a pathway to more ambitious, resilient, and timely decarbonisation. By turning external pressure into internal logic, companies can move from compliance to leadership in the climate transition. Full article

As Chinese firms play pivotal roles in global supply chains, multinational corporations face increasing pressure to ensure ESG accountability across their sourcing networks. Current ESG rating systems lack transparency in incorporating China’s unique industrial, economic, and cultural factors, creating reliability concerns for stakeholders managing supply chain sustainability risks. This study develops an explainable artificial intelligence framework using SHAP and permutation feature importance (PFI) methods to predict the ESG performance of Chinese firms. We analyze comprehensive ESG data of 1608 Chinese listed companies over 13 years (2009–2021), integrating financial and non-financial determinants traditionally examined in isolation. Empirical findings demonstrate that random forest algorithms significantly outperform multivariate linear regression in capturing nonlinear ESG relationships. Key non-financial determinants include patent portfolios, CSR training initiatives, pollutant emissions, and charitable donations, while financial factors such as current assets and gearing ratios prove influential. Sectoral analysis reveals that manufacturing firms are evaluated through pollutant emissions and technical capabilities, whereas non-manufacturing firms are assessed on business taxes and intangible assets. These insights provide essential tools for multinational corporations to anticipate supply chain sustainability conditions. Full article

With the growth of international trade, concerns over the safety of imported agricultural products in South Korea have intensified due to factors such as the COVID-19 pandemic, radiation contamination risks, and the prevalence of GMOs. In response, this study develops two composite indices—the Agricultural Product Safety Index (APSI) and the Imported Food Safety Index (IFSI)—to quantitatively assess food safety risks across major exporting countries and apply them to Korea’s import structure. The indices integrate production and distribution risk indicators based on publicly available data and adhere to five key principles, including applicability, reliability, boundedness, independence, and representativeness. Empirical results from 2014 to 2021 indicate that Australia consistently demonstrates the highest food safety level, followed by the United States, Argentina, Ukraine, and Brazil. While the indices provide a structured and transparent framework for monitoring import-related safety, their scope is limited to selected countries and excludes biological hazards due to data limitations. Future research should expand the geographical coverage and incorporate empirical validation techniques. These findings contribute to the development of evidence-based policy instruments aimed at enhancing food safety governance in global supply chains. Full article

In recent years, the intensifying frequency of natural disasters such as floods and typhoons has brought severe disruptions to the global supply chain system, making supply chain resilience an important academic research and practical application topic. This study explores the influencing factors and allocation effects of supply chain resilience under the risk of natural disasters, with a particular focus on its impact on sustainability. This paper conducts an empirical study on supply chain resilience in the context of natural disasters by using the Structural Equation Model (SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA). Based on 407 valid questionnaires, the study found that supply chain flexibility, foresight, visibility, cooperation, and support significantly positively affected the enhancement of supply chain resilience. Furthermore, through the fsQCA method, this study identified a single configuration approach that leads to high supply chain resilience and clarified the complexity of resilience formation under different conditions. This research not only enriches the theoretical framework of supply chain resilience but also provides targeted strategies for enterprises and governments to enhance their resilience to natural disasters, thereby suggesting potential pathways to support economic stability, social well-being, and environmental protection, though further empirical validation is needed. Full article

Designing sustainable farming systems in mountainous regions is particularly challenging because of complex economic, social, and environmental factors. Production models prioritizing sustainability and environmental protection require integrated assessment methodologies that can address multiple criteria and incorporate diverse stakeholders’ perspectives while ensuring accuracy and applicability. Life cycle assessment (LCA) and multi-actor multi-criteria analysis (MAMCA) are two complementary approaches that support “eco-design” strategies aimed at identifying the most sustainable options, including on-farm transformation processes. This study presents an integrated application of LCA and MAMCA to four supply chains: rye bread, barley beer, cow cheese, and goat cheese. The results show that cereal-based systems have lower environmental impacts than livestock systems do, although beer’s required packaging significantly increases its footprint. The rye bread chain emerged as the most sustainable and widely preferred option, except under high-climatic risk scenarios. In contrast, livestock-based systems were generally less favorable because of greater impacts and risks but gained preference when production security became a priority. Both approaches underline the need for a deep understanding of production performance. Future assessments in mountain contexts should integrate logistical aspects and cooperative models to enhance the resilience and sustainability of short food supply chains. Full article

The global port and maritime industry is experiencing a new paradigm shift known as the artificial intelligence transformation (AX). Thus, domestic container-terminal companies should focus beyond mere automation to a paradigm shift in AI that encompasses operational strategy, organizational structure, system, and human resource management. This study proposes a resilience-based AX strategy and implementation system that allows domestic container-terminal companies to proactively respond to the upcoming changes in the global supply chain, thus securing sustainable competitiveness. In particular, we aim to design an AI-based governance model to establish a trust-based logistics supply chain (trust value chain). As a research method, the core risk factors of AX processes were scientifically identified via text-mining and fault-tree analysis, and a step-by-step execution strategy was established by applying a backcasting technique based on scenario planning. Additionally, by integrating social control theory with new governance theory, we designed a flexible, adaptable, and resilience-oriented AI governance system. The results of this study suggest that the AI paradigm shift should be promoted by enhancing the risk resilience, trust, and recovery of organizations. By suggesting AX strategies and policy as well as institutional improvement directions that embed resilience to secure the sustainable competitiveness of AI-based smart ports in Korea, this study serves as a basis for establishing strategies for the domestic container-terminal industry and for constructing a global leading model. Full article

Disruptions in a single supplier’s operations can trigger cascading effects across the entire supply chain, highlighting the critical importance of effective supplier-focused risk management. While supply chain risk management (SCRM) frameworks encompass diverse dimensions—such as supply, products, demand, and information—risks specifically related to suppliers demand tailored strategies and analytical focus. Despite the growing volume of publications on this topic, the literature still lacks updated conceptual guidance on how to manage these risks, particularly in light of emerging challenges and practices. This study addresses this gap, with the primary objective of developing a contemporary conceptual framework for supplier risk management, reflecting recent academic and practical advances. The research methodology combines bibliometric analysis, the PRISMA systematic review protocol, and visualization tools including CiteSpace and CitNet Explorer. Key findings include the evolution of thematic clusters over time, with “supplier selection” identified as the most dominant theme, and simulation as the prevailing research method. The automotive industry emerges as the most frequently studied empirical context. Moreover, the study expands existing frameworks by introducing two emerging dimensions—environmental, social, and governance (ESG) and information technology (IT)—as key factors in supplier risk management. This framework contributes to theory and practice by offering an updated lens for understanding supplier-related risks and providing decision-makers with structured insights to enhance resilience in complex supply networks. Full article

Background: The transportation of petroleum products via multimodal logistics systems is a complex process subject to operational inefficiencies and elevated risk exposure. The efficient and resilient transportation of petroleum products increasingly depends on multimodal logistics systems, where operational risks and process inefficiencies can significantly impact safety and performance. This study addresses the research question of how an integrated risk-based and workflow-driven approach can enhance the management of oil products logistics in complex port environments. Methods: A dual methodological framework was applied at the Port of Midia, Romania, combining a probabilistic risk assessment model, quantifying incident probability, infrastructure vulnerability, and exposure, with dynamic business process modeling (BPM) using specialized software. The workflow simulation replicated real-world multimodal oil operations across maritime, rail, road, and inland waterway segments. Results: The analysis identified human error, technical malfunctions, and environmental hazards as key risk factors, with an aggregated major incident probability of 2.39%. BPM simulation highlighted critical bottlenecks in customs processing, inland waterway lock transit, and road tanker dispatch. Process optimizations based on simulation insights achieved a 25% reduction in operational delays. Conclusions: Integrating risk assessment with dynamic workflow modeling provides an effective methodology for improving the resilience, efficiency, and regulatory compliance of multimodal oil logistics operations. This approach offers practical guidance for port operators and contributes to advancing risk-informed logistics management in the petroleum supply chain. Full article

Background: Short food supply chains are commonly perceived as more sustainable and safer alternatives to conventional production systems, often linked to organic, free-range livestock practices. Materials and methods: This study investigates, for the first time, the distribution of antimicrobial resistance genes (ARGs) and characterizes the microbial communities’ composition, using 16S rRNA sequencing and real-time PCR, respectively. Eleven fecal, 76 slaughterhouse surface, 11 cecal, and 11 carcass samples, from 11 poultry farms belonging to the same short food chain, were analyzed in the study. Results: While cleaning and disinfection procedures appeared to reduce the bacterial load on slaughterhouse surfaces, diverse and potentially resistant bacteria, including genera such as Staphylococcus and Streptococcus, persisted both before and after slaughter. ARGs conferring resistance to high-priority critically important antimicrobials (HPCIAs), such as fluoroquinolones and third-generation cephalosporins, were frequently detected on carcasses, with qnrS (76.15%, 95%CI 68.02-84.28%) and bla_CMY2 (57.8%, 95%CI 48.38-67.22%) being the most prevalent. The slaughtering process emerged as a critical step for ARG dissemination via intestinal bacteria, such as genus Lactobacillus. Additionally, the detection of mcr genes and bla_NDM on carcasses but not in the bird gut samples suggests possible anthropogenic contamination. Discussion: These findings highlight that the evisceration process, slaughterhouse environment, and personnel are all contributing factors in ARG spread and underscore the need for enhanced hygiene protocols and reduced gut ARG carriage in domestic birds to mitigate the risk for the consumer. Full article

The development of the supply chain’s outsourcing and globalization has intensified the requirement for sustainable transport. The evaluation of the transport providers’ maturity, which is crucial to all and any achievements in this context, is hampered by a myriad of factors ranging from the transport ecosystem complexity, self-contradictory and unverifiable data and the ceaseless march of modern technology. This study argues for an agile and smart approach to evaluate the maturity level of transport providers, particularly for high-risk areas like hazardous materials transport. Such models should include holistic analysis frameworks of all performance indicator measurement systems with their data collection methods and technology tools to be employed. The need to involve all stakeholders within the supply chain is said to require diverse collaboration. With regard to the solution, collaborative participation between transport providers and relevant institutions is vital to reduce the environmental impacts and improve the efficiency of the entire sector. Full article

The eyeglass lens manufacturing industry has become increasingly vulnerable to supply chain risks due to overlapping global disruptions, including the COVID-19 pandemic, the Suez Canal blockage, the Russia–Ukraine conflict, Red Sea shipping insecurity, and recent U.S. import tariffs. These events have challenged inventory planning, supplier coordination, and cost control across the industry. This study aims to evaluate how five operational constructs—stock system, inventory optimization, standardized methodology, production capability, and logistics performance—influence inventory resilience during global crises. Using an empirical case study, data were collected from 215 supply chain professionals at a multinational lens manufacturer in Southeast Asia and analyzed via Structural Equation Modeling (SEM). The results show that inventory optimization (β = 0.93) is the most influential factor in mitigating supply–demand imbalances, followed by logistics performance and production capability. This study offers practical recommendations, including real-time demand tracking, modular production systems, and scalable logistics strategies, to enhance inventory resilience. These findings contribute to both theory and practice by providing a validated framework tailored to high-precision manufacturing under persistent global risk. Full article