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In this policy brief, Antonia Hmaidi, Senior Analyst in the Science, Technology and Innovation Program at MERICS, analyzes Huawei, a company that is emerging as the leader of China’s national team in semiconductors, dominating chip manufacturing and seeking to integrate the country’s entire supply chain. Its ambitions stem from both its placement on the U.S. Entity List and strong government support at the national and local level. Internationally, Huawei is coy about these ambitions, hiding its supply chain involvement and often operating under a different company’s name. Meanwhile, Huawei’s experience is also encouraging other Chinese technology companies to support China’s quest for chip self-sufficiency, developing new hardware and software for that purpose. The clandestine nature of Huawei’s involvement—it is not known who serves what role in semiconductor production—makes it more difficult for Western companies and governments to assess China’s progress in technology, vet potential partners and customers, and conduct risk assessments.

ABSTRACT: Section 1502 of the Dodd–Frank Act requires SEC‐registered issuers to conduct supply chain due diligence and submit conflict minerals disclosures (CMDs) that indicate whether their products contain tantalum, tin, tungsten, or gold (3TG) sourced from the Democratic Republic of the Congo (DRC) or its neighboring countries (“covered countries”). Consistent with the reputational cost hypothesis, we find that heightened public attention to CMDs increases responsible sourcing. After Section 1502 takes effect, we find higher demand for 3TG products processed in certified smelters, decreased conflicts in covered countries’ mining regions relative to other regions, and reduced sensitivity of conflict risk to conflict minerals’ price spikes. Finally, we find that conflicts decrease in Eastern DRC territories with prevalent 3T (tantalum, tin, and tungsten) mines but increase in territories with prevalent gold mines. Overall, our findings highlight the real effects of enhanced supply chain transparency regulation.

Several supply chain-related laws have recently been passed in Europe and the United States as a result of successful NGO campaigns, which have addressed the challenges of accountability in a globalized world. Based on the analysis of campaign documents and semi-structured interviews, the article examines the accountability narratives used by NGOs in recent campaigns for an EU Corporate Sustainability Due Diligence Directive (CSDDD). The results show that the campaigns portray European corporations as perpetrators, people in producing countries as mere victims, and NGOs as heroic liberators. NGOs reproduce postcolonial trajectories by advocating a supply chain law in the Global North as the central solution to problems in the Global South. While rescue politics is thus the defining feature of NGO campaigns, there is no evidence of the strategic use of pseudo-causal narratives that are empirically inaccurate. [ABSTRACT FROM AUTHOR]

Academic and industrial research on digital technology has been quite thorough. Nevertheless, scant information exists regarding the supply chain implementation of digital technology in industrial companies. To better understand supply chains, this article will look at why and how manufacturing companies are implementing digital technology. The goal of this paper's literature analysis is to pinpoint current studies and perspectives on how these technologies could help digital supply chains (DSCs) operate better, faster, and more efficiently. The investigation looks at the technologies' directions and challenges in improving the efficiency of digital help confinement, in addition to underlining their significance for supply chains and logistics. It investigates the managerial and practical issues in developing a new integrated paradigm for digital supply chains. Also, possible obstacles to DSCs and procurement will be examined, along with solutions. Consequently, this study pinpoints multiple opportunities for adding value when implementing Internet of Things (IoT) in the supply chain using mobile technology. Additionally, it suggests a method for creating business models for supply chain algorithms. [ABSTRACT FROM AUTHOR]

This special issue addresses the impact of COVID-19 on entrepreneurship. It builds on insights shared at the dedicated session – supported by the Hungarian Academy of Sciences' Post-COVID research grant (MTA PC-II-17/1/2022) – of the 2nd Danube Cup Conference in Belgrade in November 2023, featuring three papers presented there, along with four additional contributions. The goal of this issue is to advance scholarly understanding of post-COVID dynamics in entrepreneurship and share valuable findings with a broad academic audience. To provide a comprehensive overview of current research on this topic, we include an umbrella review examining the COVID-19 crisis' impact on small and medium-sized enterprises (SMEs) from 2020 to 2024. Drawing on 26 systematic literature reviews identified through Scopus, Google Scholar, and Elicit, this review captures key challenges, strategies, and emerging trends affecting SMEs. Major research themes identified include resilience, supply chain management, digitalization, crisis management, and the financial impact of COVID-19. [ABSTRACT FROM AUTHOR]

This study examined factors affecting healthcare supply chain performance in Tanzania. Specifically, the study examined the effect of information technology and inventory control practices on healthcare supply chain performance in Tanzania. The study was conducted in Dar es Salaam region and involved Medical Stores Department (MSD) Headquarters. The study used mixed research approach and a cross-sectional design. Out of 209 populations, 137 respondents were selected as sample size randomly. In data collection, questionnaires and interview were used as tools for collection of data. The study used descriptive and inferential (linear regression) analysis. Findings established that, information technology has positive and statistically significant influence on healthcare supply chain performance. Also, inventory control practices have positive and significant effect on healthcare supply chain performance. The study recommends that, the healthcare sector together with Medical Stores Department (MSD) in Tanzania should consider increasing their investment in information technology infrastructure. This could involve upgrading existing systems, adopting new technologies, and ensuring that IT resources are adequately allocated to support healthcare supply chain operations. Also, healthcare sector and MSD need to ensure seamless integration of different IT systems within and between healthcare organizations. Moreover, MSD should put more emphasis on improving their inventory management systems to ensure that inventory is properly managed and tracked. [ABSTRACT FROM AUTHOR]

Public procurement plays a significant role in driving innovation within supply chains, yet there are substantial challenges hindering its effective utilisation as a policy tool to enhance innovation. This article explores the role of public procurement in promoting innovation among supply chain practitioners, focusing on the context of Tanzania. Findings reveal limited awareness among stakeholders regarding the potential of public procurement to foster innovation, with prevailing perceptions prioritising compliance objectives over innovation promotion. Strategies to promote innovation, such as alternative bidding, are underutilised, and regulatory frameworks often lack support for innovative procurement approaches. Recommendations emerge to address these challenges, including enhancing awareness through capacity-building programs, revising regulatory frameworks to support innovative procurement, addressing budgetary limitations, fostering a culture of innovation within procuring entities, and streamlining procurement processes. Implementing these recommendations can unlock the full potential of public procurement as a driver of innovation, contributing to economic growth and sustainable development. [ABSTRACT FROM AUTHOR]

Supply chain management is recognized as a crucial element in boosting organizational performance and competitiveness. However, the COVID-19 crisis has demonstrated that many corporations were unprepared and lacked a recovery strategy, which led to significant supply chain disruptions. Hence, the purpose of this study is to evaluate the Supply Chain Performance Measurement System (SCPMS) lifetime under unforeseen situations, particularly in developing nations like Egypt, and its relevance during the pandemic and post-pandemic periods. A systematic questionnaire was used to gather data from 100 manufacturing firms (supply chain and retailers) with large business volume who provided a total of 562 questionnaires. The findings indicated that there were four main measurement systems: SCPMS Design, SCPMS Implementation, SCPMS Use, and SCPMS Review. The results of the AHP method found that the SCPMS implementation was the most important system, while the least important was SCPMS design. [ABSTRACT FROM AUTHOR]

Large vessels that call at European ports will have to pay for their CO2 emissions from transporting cargo that enters or goes from a European port since January 2024. The costs will increase with increasing global trade. This results in a higher pollution level, including greenhouse gas (GHG) emissions like CO2. Based on the gravity model embedded in a global supply chain, we developed a model to evaluate maritime transport pollution in case a new, sufficiently large container port becomes operational. Additionally, we consider how lousy railway connections to European customers increase transportation costs and pollution. The approach to the well-connected sequences of gravity models in the intercontinental maritime chains evaluates the differences in quantities of cargo between ports when a new port is opened, and the waiting time does not change. We also highlight that poor rail connections can reduce this positive effect. We showed how it is possible to estimate the optimal capacity of a new port with a multi-level gravity model and how this would affect the pollution around the port and on the routes from the port to the final consumers. [ABSTRACT FROM AUTHOR]

The shipping industry is featured by high carbon emissions. The 2023 IMO Strategy on Reduction of GHG Emissions from Ships sets forth the global goals of shipping decarbonization. Shipping decarbonization involves complicated issues of economy, technology, policy and law etc., and implies the conflicts between economic interests and environmental interests, between individual interests and public interests, between individual States' interests and international common interests and between current interests and long-term interests. This research suggests that balancing such conflicting interests need to follow the principle of prioritizing the international public environmental interests while taking into account the other interests because protection of environmental interests should be taken as the basic value orientation in shipping decarbonization governance and the principle of collaborating governmental intervention and market mechanisms by reference to the theory on the relationship between government and market in economics. Under the guidance of these principle, by reference to the equilibrium analysis method in economics and following the progressive decision theory in management, this research demonstrates that the main pathways in achieving such balance may include: making strategic plan and basic policy for reducing GHG emissions from ships by the government, implementing economic incentive policies such as tax incentives and fiscal subsidies, implementing ship energy efficiency measures, prudently implementing shipping carbon emissions trading mechanism, accelerating the establishment of alternative marine fuel supply chain, innovating alternative marine fuel technology and ship propulsion technology, and actively engaging in international cooperation. [ABSTRACT FROM AUTHOR]

As the economic environment becomes more complex, improving supply chain resilience is critical for the effective operation and long-term sustainability of businesses. Real-world supply chains, which consist of various components such as goods, warehouses, and plants, often feature intricate network structures that pose challenges for resilience analysis. This paper addresses these challenges by proposing a framework for studying supply chains using multi-layer network community detection. The complex multi-mode supply chain network is transformed into single-mode, multi-layer weighted networks. A multi-layer weighted community detection method is proposed for identifying local clusters within these networks, revealing interconnected groups that highlight flexibility and redundancy in production capabilities across different plants and goods. An empirical study utilizing real data demonstrates that this clustering method effectively detects indirect capacity links between plants and goods. The insights derived from this method are useful for strategic capacity management, allowing businesses to respond more effectively to supply shortages and unexpected increases in demand. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) stands out as a significant technological innovation, driving progress in diverse areas such as big data analysis, supply chain management, energy efficiency, sustainable development, etc. The present study investigates how AI could contribute to the sustainability of the healthcare supply chain (HSC) and managing medical needs. Medical organizations can boost the logistics of their tasks, reduce pharmaceutical trash, and strengthen revenue projections through the adoption of AI tools. This study aims to provide a structured evaluation of AI-driven solutions for enhancing healthcare supply chain robustness, especially under conditions of uncertainty and complex logistics demands. To determine the investment value of AI applications in HSC management, the current research adopted a revolutionary multi-criteria decision-making (MCDM) methodology tailored to the healthcare sector's unique demands, including six critical factors. In light of these criteria, six highly technologically advanced AI-based solutions are examined. The implementation of a circular intuitionistic fuzzy set (CIFS) in the instance discussed provides a versatile and expressive way to describe vague and uncertain information. This study leverages the CIF topology to address data complexities and uncover the underlying structural features of a large dataset. At the outset, we adopted the LOPCOW approach, which includes logarithmic variation to assign weights to criteria, whereas the AROMAN method utilizes a powerful two-step normalization technique to rank alternatives, hence guaranteeing a trustworthy and accurate appraisal. A substantial degree of robustness was confirmed by the technique following a comparison of the operators as well as sensitivity testing. [ABSTRACT FROM AUTHOR]

The conventional logistics' paradigm is being replaced with smarter ways of supply chain management to readily serve the customers with quick modes of delivery in affordable operational costs. The weak infrastructure in rural terrain and congested roads in urban cities act as a big impediment in the successful accomplishment of last mile delivery down the lane across the complete chain of logistics. The traditional logistics has been evolved and improved in many respects, the last mile delivery is still plagued by security and privacy risks in logistics. The use of drones for package deliveries may offer promising gains in terms of efficiency. Nonetheless, drones undergo security and privacy risks besides physical threats for being deployed in public places communicating on open channels. Thus, more efforts are needed to secure the communication of inducted drones in delivery assignments. We propose a novel PUF-enabled drone access control mechanism PDAC-SL for smart logistics. By the careful employment of symmetric crypto-primitives, the contributed protocol not only supports low end devices but stands resistant to physical drone and other known threats besides preserving anonymity and untraceability features. The RoR model-based formal security analysis and performance analysis demonstrate distinct security properties and applicability of the PDAC-SL. [ABSTRACT FROM AUTHOR]

This study aims to explore allocation strategies for idle emergency supplies in a "demander–platform–supplier" supply chain system along with government regulation during the post-disaster recovery period. Allocation of emergency supplies is a complex task that encompasses resource allocation before and after disasters. It is essential to reduce losses in disaster-stricken areas and support development during post-disaster recovery. However, there is often an excessive supply of emergency materials and a mismatch between supply and demand sides in downstream supply chains, which may lead to severe waste and difficulties in recovering surplus materials. This paper takes idle emergency resource sharing level and corporate social responsibility goodwill as endogenous variables. The allocation approaches are dynamically evaluated by incorporating random elements that influence the endogenous variables. Three stochastic differential games are introduced to examine the interactions between the players. The centralized decision-making satisfies the consistency of overall and individual rationalities at any time in the emergency material allocation process, promoting the optimal sharing levels of emergency materials and overall profits. The decentralized decision-making with cost-sharing contracts achieves local optima and increases the dual marginal effect of the emergency industry chain. This paper incorporates the sharing economy into emergency management, showing how technology-driven sharing platforms can optimize resource utilization. The results suggest introducing cost-sharing contracts between demanders and suppliers can enhance collaboration and effort, leading to better resource allocation and increased efficiency. It contributes to sustainability by promoting efficient resource utilization through idle emergency resource sharing. By optimizing allocation strategies and enhancing corporate social responsibility, the study fosters the long-term viability and resilience of the supply chain system in post-disaster management. [ABSTRACT FROM AUTHOR]

The growth in carbon emissions is increasingly exacerbating global warming. As the principal source of carbon emissions, companies can effectively enhance their emission reduction levels through the vertical spillover of emission reduction technologies to investigate the impact of vertical spillover rates, consumers' low-carbon preference coefficients, emission reduction cost coefficients on optimal supply chain decisions, and profits in centralized and decentralized decision-making environments. Considering consumers' preferences for low-carbon options, this paper constructs a Stackelberg game model under centralized and decentralized supply chain decision-making scenarios. It examines the effects of considering the vertical spillover effects of emission reduction versus not taking them into account. Using backward induction, this study optimizes the emission reduction levels of leading suppliers and manufacturers. The results indicate that an increase in consumers' low-carbon preference levels and vertical spillover rate not only enhances the emission reduction levels of suppliers and manufacturers but also increases their profits. Conversely, an increase in emission reduction cost coefficients impedes emission reductions, with a more pronounced effect under vertical spillover conditions. In centralized decision-making, increases in vertical spillover rates, consumers' low-carbon preferences, and decreases in emission reduction cost coefficients create a synergistic effect, resulting in greater increases in emission reduction levels and profits for suppliers and manufacturers compared to the sum of the effects of changes in individual coefficients. This finding provides new insights for governments in formulating relevant policies to promote corporate emission reductions. [ABSTRACT FROM AUTHOR]

China's "Going Out" strategy and the "Belt and Road" initiative have significantly propelled the expansion of overseas contractual engagements, with a pronounced impact in the Engineering, Procurement, and Construction (EPC) sector. EPC contracting is increasingly recognized for its superior resource allocation and integration efficiency. Within the EPC framework, procurement is pivotal, exerting a direct influence on project cost, schedule, and quality parameters. The biblio-metric analysis of this paper reveals the research trend of EPC projects in the past decade, especially in supply chain integration, procurement management, and stakeholder management. This indicates an increasing interest in efficient project management and supply chain optimization in international engineering EPC projects. Although the application of supply chain integration in the manufacturing industry has been a successful experience, its practical application in construction and EPC projects is still insufficient. Integration strategies mentioned in the literature, such as achieving supply chain transparency through digital platforms, reducing operating costs, and optimizing delivery time, are directions that need to be further explored in this field. Effective supply chain integration and increased maturity of procurement management in EPC projects are still less involved areas. In addition, there is also a lack of research on how to manage high-risk and unpredictable risks in large international engineering projects. This article suggests that future research should focus on developing flexible supply chain management tools and practices to adapt to a project-oriented supply chain environment. [ABSTRACT FROM AUTHOR]

As environmental sustainability gains importance, enhancing supply chains to minimize environmental hazards is essential, particularly in industries using residual biomass. This study tackles this by investigating the integration of sustainability criteria into supply chain optimization for a biomass energy company in Portugal, using a combination of simulation modeling through anyLogistix software (version: 2.15.3.202209061204) and multi-criteria decision-making. Four supply chain scenarios were designed and simulated, differing in their number of distribution centers, the adoption of green logistics, and split-by-ratio distribution strategies over a 305-day period. Through the weighted sum model, Scenario C emerged as the optimal configuration, achieving a balance between operational efficiency and sustainability by reducing CO2 emissions by up to 90% and lowering transportation costs without compromising revenue. Sensitivity analysis further highlighted the trade-offs between cost efficiency, lead times, and environmental impact, showing that the strategic placement of distribution centers and the use of eco-friendly vehicles significantly improve the sustainability of the biomass supply chain. These findings provide practical insights for decision-makers, demonstrating how digital modeling tools can enhance supply chain management by optimizing environmental and operational goals simultaneously. This research contributes to the fields of sustainable logistics and supply chain management by validating the effectiveness of green logistics strategies and multi-criteria decision-making approaches in reducing environmental impact while maintaining economic viability. [ABSTRACT FROM AUTHOR]

This study examines the operational problems that a mid-sized food production factory faces. It utilizes system dynamics (SD) and lean thinking approaches to analyze various challenges that these companies encounter. Through extensive data analysis and managerial meetings, this study identifies several factors affecting the company's performance: cash management, delivery delays, product quality impact on customer satisfaction, debt burden from raw materials purchase, and poor product planning. Various scenarios are simulated to significantly improve sales' stability and liquidity. This paper offers insights into how effective cash flows can be attained, as well as customer satisfaction, managing debts, and strategic plans that lead to business success. Additionally, the potential for extending SD to address similar challenges in the food industry is explored through detailed financial modeling and actionable plans. [ABSTRACT FROM AUTHOR]

Managing delivery risks is a critical challenge in modern supply chain management due to the increasing complexity and interdependencies of global supply networks. Existing methods often rely on correlation-based approaches, which fail to uncover the true causes behind delivery delays. This limitation makes it difficult for supply chain managers to identify actionable factors that can mitigate risks effectively. To address these challenges, we propose a novel method that integrates causal discovery with reinforcement learning to identify the root causes of delivery risks. Unlike traditional correlation-based methods, our approach uncovers both the direction and strength of causal relationships between variables, allowing for more accurate identification of the key drivers behind delivery delays. By applying causal strength quantification, we further measure the impact of each factor on delivery performance. Using real-world supply chain data, our results demonstrate that the proposed method reveals hidden causal relationships between factors such as shipping mode, order size, and delivery status. These insights enable supply chain managers to implement more targeted interventions, significantly improving risk mitigation strategies. [ABSTRACT FROM AUTHOR]

This paper discusses the Benders decomposition approach on the multi-objective adjustable robust counterpart optimization model with polyhedral uncertainty set for sugar distribution supply chain problems. It focused on the optimization modeling of sugar distribution among producers, local food hubs, and consumers in sub-districts. This problem is considered a multi-objective mixed integer linear programming problem with two objective functions: to maximize demand fulfillment and minimize logistics costs. Uncertain data was collected from real-life scenarios and analyzed using the adjustable robust counterpart methodology with polyhedral uncertainty set assumption. The uncertain data consisted of the adjustable and non-adjustable variables. This research was carried out in northern Bandung City, Indonesia. The result shows that the evaluation of the two-stage supply chain optimization model with adjustable robust counterpart methodology is effectively solved using the benders decomposition approach. [ABSTRACT FROM AUTHOR]

Based on the spring, spring MVC and MyBatis structures of the cloud platform SSM framework, an information management platform for power grid material supply chain is built. The data layer uses a variety of sensors to collect power grid material supply chain information, and the information is fed back to the data storage layer after being integrated by the logical reorganization function of the persistence layer. The data storage layer uses the multi-sensor supply chain information fusion method based on paste progress to fuse the information and store it in the database. The business logic layer calls the information in the database and uses the improved k-means clustering algorithm to detect the abnormal supply chain data information. After calculation and data control by the control layer, the data management results are displayed through the presentation layer. The experimental results show that the absolute error of data fusion is very low. It can effectively cluster data information and distinguish outlier anomaly information at the same time, and the effect of information management is good. [ABSTRACT FROM AUTHOR]

Today, dental tourism is regarded as one of the most important tourist industries due to its high demand and financial transactions. Sustainable development has become increasingly important because of the depletion of natural resources, health problems, and waste management. Contrary to the previous works, we firstly develop a multi-objective mathematical model seeking to reach and optimize sustainable objectives in the dental tourism supply chain. To achieve these aims, optimal locations of dental clinics and accommodation facilities and their required number and capacities are found. Besides, transportation activities and waste treatment facilities are optimized based on supply and demand. Biological risks, job vacancies creation, environmental issues, and costs and profits are considered in our work. Also, an improved goal programming is employed to solve the model. In addition, this model is implemented and analyzed by a real case study of the dental tourist industry to validate the proposed model. The government and practitioners of private sectors would derive great benefits from the real case outputs to build a thriving business from sustainable perspectives. [ABSTRACT FROM AUTHOR]

Prefabricated construction has shifted a portion of environmental responsibilities (ERs) from on-site to off-site, prompting a focus on the entire supply chain. As an issue emerging alongside the prefabricated construction, ERs are yet to be clearly allocated along the supply chain. This study aims to explore the optimal allocation of ERs between the agents involved in a prefabricated construction supply chain (PCSC), considering two distinct types of government subsidies, namely, subsidies based on ER levels (EL subsidy) and subsidies based on ER incremental costs (EC subsidy). Additionally, it aims to compare the influence of two types of government subsidies on this allocation process. A three-stage supply-chain Stackelberg model involving the government, a supplier, and a contractor was established to analyze their optimal decisions and a numerical analysis based on a case was further exploited to validate the results. The study revealed a positive correlation between ER levels of the entire supply chain and the ER managerial efficiency of both agents under each type of subsidy. The ER allocation between the two agents varied depending on the subsidy type. With EL subsidies, the allocation of one's ER level was contingent on its own ER managerial efficiency, while under EC subsidies, the optimal allocation of ERs between the two agents was equal. No subsidy could simultaneously render both agents more profitable than the alternative subsidy, but optimal profits were largely determined by the ER managerial efficiency of the involved agents. By comparing subsidy effectiveness indicators, it was found that EL subsidies are deemed more beneficial for the construction environment than EC subsidies. The findings can serve as a valuable reference for government authorities to incentivize ER behaviors and help enterprises in the supply chain achieve a win-win situation. [ABSTRACT FROM AUTHOR]

Research on agrifood supply chains has grown in recent years; however, little attention has been given to the effect of the choice of distribution channel on the sustainable and resilient performance of the network. This research proposes a system dynamics model to evaluate different distribution channels for a fresh food supply chain in a developing country. Among the main results is that the use of food hubs in a channel distribution produces long-term environmental, social and resilience benefits for the entire network, while short supply chains are the most economically viable alternative. [ABSTRACT FROM AUTHOR]

As port authorities and cargo operators seek strategies to reduce carbon emissions while ensuring operational efficiency, some are turning to the concept of green corridors. These solutions aim to establish formalized partnerships among ports, carriers, shippers, and countries. During the process, the stakeholders must consider four priority areas (alternative fuels, bunkering infrastructure, vessel decarbonization pathways, and cargo demand dynamics) from seven angles (environmental, economic, infrastructure, regulatory, operational, technological, and social). This study explores the prioritization of these criteria for establishing a green maritime corridor between two major ports in Portugal and Angola, which would be a significant step toward promoting sustainable global trade. Utilizing the fuzzy AHP, this research analyzes all these factors and their associated sub-criteria derived from a comprehensive literature review and consultations with stakeholders from the Ports of Sines and Luanda. The findings show the dominance of environmental compatibility and economic viability, while social acceptance shows the lowest score. This framework guides the decision-making process for developing a sustainable shipping corridor. The results offer valuable insights for policymakers which can guide them in fostering resilient maritime transport routes, accelerating the adoption of decarbonization strategies and playing a critical role in achieving the IMO's zero-emission targets by 2050. [ABSTRACT FROM AUTHOR]

Businesses may face different challenges in the realization and management of supply chain activities. To cope with these challenges and be successful in supply chain management, companies need supply chain strategies that are suitable for their product structures and objectives and strategic collaborations based on co-operation among supply chain members. In addition, to control and improve the results of the activities and strategies, the performance of logistics activities, which have a large share in the economic development of companies, should be measured and managed correctly. Therefore, supply chain strategies, supply chain integration, and logistics performance measurements have a critical importance in supply chain management, where the competition of companies is experienced and complexity is increasing day by day. In this framework, this study aims to investigate the relationship between the supply chain strategies and logistics performance of an enterprise and whether supply chain integration has a mediating role in this relationship. For this purpose, 417 data samples were collected and analyzed from the top 1000 exporter companies determined by the Turkish Exporters Assembly by a survey method, and the findings are analyzed and discussed. In the literature, there is no study that analyzes the relationship between the variables determined in this research from a mediator variable perspective. Therefore, this study presents original research in this field, and it is expected that the findings of the research will provide important benefits to companies and researchers and offer a new perspective to the literature. As a result of the analysis, it was determined that there is a significant and positive relationship between the supply chain strategies determined by companies and their logistics performance and supply chain integration. There is also a significant and positive relationship between supply chain integration and logistics performance. In addition, it has been concluded that supply chain integration plays a partial mediating role in the relationship between supply chain strategies and logistics performance. These results suggest the importance of supply chain strategies and supply chain integration in improving logistics performance. Therefore, in line with the research results, it is suggested that, to use supply chains for competitive advantage, managers should ensure supply chain integration by determining the right supply chain strategies in accordance with their objectives and product structures, and thus increase their logistics performance. [ABSTRACT FROM AUTHOR]

After the COVID-19 epidemic, the recovery of tourism growth faced more pressure on carbon emissions. As an important sector of tourism economic recovery, the tourist hotels' carbon emissions cannot be ignored. This study combined the EEIO (the environmentally extended input–output) model and Super-SBM (slacks-based measure) model to measure carbon emissions and its efficiency including indirect carbon emissions from the supply chain in China in 2002–2022. The results indicate that: Tourist hotels in most eastern provinces exhibit the U-shaped pattern in terms of carbon emissions. the majority of indirect carbon emissions from these hotels originate from the food and tobacco processing sectors. Indirect carbon emissions of tourist hotels in recent years might be decoupling with economic growth because of its decreasing trend. The implementation of energy-saving technology can enhance the carbon efficiency of tourist hotels, while regional economy growth can benefit the carbon emissions efficiency indirectly. Environmental pollution control investment and employment population are external driving factors affecting carbon emissions from tourist hotels. The objective of this study is to establish a scientific framework that promotes low-carbon development within the accommodation industry, both in China and comparable regions globally. [ABSTRACT FROM AUTHOR]

This study leverages a Discrete Event Simulation (DES) model to optimize the sweet potato supply chain in Zimbabwe, focusing on production, distribution, and market dynamics under varying climate conditions. The integration of climate data into the simulation model reveals significant insights into the resilience of different sweet potato varieties, particularly highlighting the suitability of yellow-skinned sweet potatoes for harsh climates due to their high resilience and drought resistance. However, market preferences still favor white-skinned varieties despite their vulnerability to climate extremes. The DES model identifies key bottlenecks, particularly in cultivation and transportation, that hinder supply chain efficiency. To address these challenges, the study emphasizes the importance of targeted interventions, such as improving access to irrigation, strengthening pest management, and adopting community-based resource-sharing approaches. These strategies are critical for enhancing both the resilience and efficiency of the supply chain. Additionally, the study highlights the urgent need for adaptive strategies to mitigate the effects of drought on agricultural productivity, especially in regions that heavily rely on crops like sweet potatoes. Overall, this research offers strategic insights for policymakers and stakeholders aiming to improve food security and agricultural productivity in Zimbabwe, as well as in other countries with similar climate challenges. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) enables smart devices to connect, share and exchange data with each other through the internet. Since an IoT environment is open and dynamic, IoT participants may need to collaborate with unknown entities with no proven track record. To ensure successful collaboration among these entities, it is important to establish a mechanism that ensures all entities operate in a trustworthy manner. We present a trust and reputation model that can be used to select the best service provider in an IoT environment. Our proposed model, IoT-CADM (Comprehensive Agent-based Decision-making Model for IoT) is an agent-based decentralised trust and reputation model that can be used to select the best service provider for a particular service based on multi-context quality of service. IoT-CADM is developed using a smart multi-agent IoT environment where information about entities is collected and evaluated using a trust and reputation algorithm. We evaluated the performance of the proposed model against some other well-known models in a simulated smart factory supply chain system. Our experimental results showed that the proposed IoT-CADM achieved the best performance. [ABSTRACT FROM AUTHOR]

We examine whether the risk of losing proprietary information through the supply chain affects relationship‐specific investment (RSI) decisions by supply chain partners. Using state courts' staggered adoption of the Inevitable Disclosure Doctrine (IDD) as a shock to the firm's ability to protect proprietary information, we find that customers increase RSI when their supplier is headquartered in a state that adopts IDD. The effect is more substantial for customers who face a higher risk of losing proprietary information and with suppliers that are difficult to substitute. IDD also plays a more prominent role in the absence of alternate mechanisms that reduce contracting frictions, such as shared directors, common ownership, or joint ventures. Our results are robust to using cross‐citation measures of RSI and alternative estimations that mitigate potential biases arising from the staggered difference‐in‐difference approach. Our findings suggest that proprietary information protection enables firms to reduce contracting frictions arising in supply chain relations. [ABSTRACT FROM AUTHOR]

In the context of global carbon emission reduction (CER) targets and slowing economic growth, it is imperative for suppliers to make informed choices regarding CER and financing strategies. However, limited research has explored the impact of financing strategies on CER. This paper develops a supply chain model that includes a supplier, a manufacturer, an E-commerce platform (E-C platform), and consumers with a preference for low-carbon products. The supplier sets the wholesale price, while the manufacturer controls both the production quantity and the unit amount of CER. We examine whether the manufacturer will invest in CER with sufficient capital or under various financing scenarios, namely (1) traditional production with sufficient capital (Scenario ST); (2) CER implementation with sufficient capital (Scenario SG); (3) CER implementation with E-C platform financing (Scenario EG); (4) CER implementation with bank financing (Scenario BG). Through comparative analysis, the analysis reveals that, regardless of the financing method chosen, the supplier's profit and the manufacturer's production quantity increase when the manufacturer invests in CER technology innovation compared to the traditional scenario. Furthermore, in terms of the manufacturer's profit, if the service cost of bank financing exceeds a certain threshold, the manufacturer should either seek financing from the E-C platform or abandon the CER investment. Additionally, with respect to CER outcomes, Scenario BG outperforms Scenario EG. These findings provide a theoretical foundation and decision-making support for supply chain participants when addressing carbon reduction and financing strategy decisions. [ABSTRACT FROM AUTHOR]

The winter storm of late 2022 caused difficulties for many US-based airlines, but none more so than Southwest Airlines. Like other airlines, Southwest canceled flights in the early stages of the storm. Their attempted recoveries failed due to procedural and technology issues. The airline was unable to cope with the magnitude of canceled flights, aircraft and crews in the wrong places, disrupted passenger plans, and luggage separated from its owners. Over the next several days, Southwest canceled tens of thousands of flights, called in thousands of additional staff to support manual operations, and flew a reduced schedule for a time before returning to normal operations. The case provides numerous scenarios for you to analyze and research, to strengthen your understanding of the underlying concepts. [ABSTRACT FROM AUTHOR]

Early warnings of enterprise credit risk based on supply chain scenarios are helpful for preventing enterprise credit deterioration and resolving systemic risk. Enterprise credit risk data in the supply chain are characterized by higher‐dimension information and class imbalance. The class imbalance influences the feature selection effect, and the feature subset is closely related to the predictive performance of subsequent learning algorithms. Therefore, ensuring the adaptivity of feature selection and the subsequent class imbalance–oriented classification model is a key issue. We propose an AdaBoost ensemble model with fast nondominated feature selection (AdaFNDFS). AdaFNDFS uses the FNDFS method in the AdaBoost algorithm to iteratively select features and uses the classifier to evaluate the performance of feature subsets to train the class imbalance–oriented classifier and the best‐matched feature subset, ensuring the adaptivity of feature selection and subsequent classifiers. The further use of the differential sampling rate (DSR) method enables AdaFNDFS to integrate more training models with different knowledge and to obtain higher accuracy and better generalization ability for prediction tasks facing high‐dimensional information and class imbalance. A test using credit risk data from Chinese listed enterprises containing supply chain information demonstrates that the prediction scoring indicators, such as AUC, KS, AP, and accuracy, of the AdaFNDFS are better than those of basic models such as LR, LDA, DT, and SVM and multiple hybrid models that use SMOTE, feature selection, and ensemble methods. AdaFNDFS outperforms the basic models by at least 0.0073 (0.0344, 0.0349, and 0.0071) in terms of the AUC (KS, AP, and accuracy). AdaFNDFS has outstanding advantages in predicting enterprise credit risk in the supply chain and can support interested decision‐makers. [ABSTRACT FROM AUTHOR]

With increased globalisation supply chain (SC) disruption significantly affects people, organisations and society. Supply chain network design (SCND) reduces the effects of disruption, employing mitigation strategies such as extra capacity and flexibility to make SCs resilient. Currently, no systematic literature review classifies mitigation strategies for SCND. This paper systematically reviews the literature on SCND, analysing proposed mitigation strategies and the methods used for their integration into quantitative models. First to understand the key failure drivers SCND literature is categorised using geography, with local, regional or global disruptions linked to vulnerable sections of a SC. Second, the strategies used in mathematical models to increase SC resilience are categorized as proactive, reactive, or SC design quality capabilities. Third, the relative performance of mitigation strategies is analysed to provide a comparison, identifying the most effective strategies in given contexts. Forth, mathematical modelling techniques used in resilient SCND are reviewed, identifying how strategies are integrated into quantitative models. Finally, gaps in knowledge, key research questions and future directions for researchers are described. [ABSTRACT FROM AUTHOR]

Transport and distribution management is a crucial aspect of supply chain logistics, as it allocates resources to optimize delivery times for finished products. This study proposes a vehicle routing system to minimize delivery times for milk to customers and retailers in the dairy supply chain in Magangué and Mompóx, Department of Bolívar, Colombia. The research involves using mathematical models to optimize routes and the utilization of the vehicle fleet. Two mathematical vehicle routing models were developed: the first addresses the Traveling Salesman Problem (TSP) for a single vehicle. In contrast, the second model deals with the capacitated vehicle routing problem (CVRP) for multiple vehicles. Both models were solved using the IBM ILOG CPLEX Optimization software. The study successfully identified viable CVRP and TSP mathematical models for milk distribution, resulting in minimized delivery times to meet the demands of the TSP model. [ABSTRACT FROM AUTHOR]

This research employs numerical simulations and scenario analysis to assess a supply chain model's economic and environmental performance operating under stochastic market demand, with inventory levels managed by a periodic review (R, s, S) inventory system. The inventory model in this research is designed to determine the minimal inventory levels required to achieve predefined fill rates across various operational constraints. The supply chain's inventory model simulates optimal responses to normally distributed market demand within 365-day periods characterized by mean and two levels of demand variability through two fill rate levels, two workweek schedules, 15 review periods, and 16 lead times. By conducting an extensive analysis of the 192000 simulation experiments of the supply chain under periodic review (R, s, S) inventory system, complex influences between system variables and economic outcomes of supply chain operation measured by ordering, transportation, holding, penalty, and total costs along with greenhouse gas emissions arising from inventory-related transportation according to the ISO 14083 standard are analyzed. The insights from this research have significant practical implications, providing valuable guidance for supply chain managers, researchers, and freight companies offering guidance for improving economic and environmental performance. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background/Objectives: This study investigates consumer perceptions and acceptance of ionizing radiation (IoR) as a perishable food stabilisation technology. Consumers' preferences influence the success of emerging food technologies. Therefore, a comprehensive understanding of consumers' behavioural responses and their development over time is essential. Methods: This research employs a mixed-methods approach, surveying 313 young adults in New Zealand on their views of both irradiated (IoR) and genetically modified (GM) highly perishable foods. This study explored both participants' attitudes towards these two technologies and also their willingness to consume these foods. Results: The qualitative research revealed a preponderance of "affective" associations over "cognitive" associations with regard to both IoR and GM technologies. The quantitative research indicated that where consumers were given time to reflect, evaluations of GM improved, while those of IoR did not (p < 0.01). There was a gender divide, with females being more positively inclined towards GM and males towards IoR (p < 0.01). Both technologies were significantly disfavoured compared to non-treated products (p < 0.01). There was a significant discrimination when the two technologies were presented as concepts and as products. GM was more favourably received as a concept than as a product (p < 0.01), while IoR was disfavoured in either form. The two food neophobia scales that were tested showed a divergence in performance, with the more affectively based scale showing a higher level of correlation with behaviour. Conclusions: This research reveals that a largely affective (visceral) distrust of both IoR and GM exists within this young food consumer sample. As it is affective in nature, this position will be very resistant to education efforts, particularly if they are "cognitively" based. However, a significant softening of these affective attitudes towards GM products indicates that such efforts may be effective, given time and investment. [ABSTRACT FROM AUTHOR]

With the rapid development of e-commerce in China, "live broadcast + e-commerce" has become an emerging mode of the e-commerce industry. The speedy growth of the digital economy has also provided a favorable external environment for fresh agricultural products to ride on the e-commerce express train. As a result, more and more suppliers of fresh agricultural products choose to sell their products on e-commerce platforms and conduct live streaming. This paper utilizes the e-commerce supply chain field survey data, takes tomato as the specific analyzed variety, and studies the revenue distribution pattern of each subject in the supply chain. The purpose of this paper is to explore the optimization strategy of the revenue distribution of an agricultural e-commerce supply chain, and the results show that the agricultural e-commerce supply chain effectively promotes the matching of supply and demand of medium- and high-end agricultural products, realizes the quality premium of medium- and high-end agricultural products, and significantly improves the overall revenue level of the supply chain. The field survey found that under the supply chain model of "farmers + cooperatives + e-commerce platform", farmers, cooperatives, and e-commerce platforms gained $2865, $3098, and $1111, respectively, for operating one mu of tomatoes in a year. According to the traditional Shapley value method, from the point of view of the contribution to the cooperative income, part of the income of the farmers and cooperatives should be compensated to the e-commerce platform, and the specific results are as follows: the income of the farmers should be reduced from $2865 to $2729, the income of the cooperatives should be reduced from $3099 to $2955, and the income of the e-commerce platform should be increased from $1111 to $1390. According to the Shapley value method based on the risk coefficient correction, from the perspective of risk compensation, part of the earnings of the e-commerce platform should be compensated to farmers and cooperatives, so as to establish a more equitable and reasonable pattern of earnings distribution, with the specific results: the earnings of farmers should be increased to $3205, the earnings of cooperatives should be increased to $3148, and the earnings of the e-commerce platform should be reduced to $722. [ABSTRACT FROM AUTHOR]

This article presents the results of a study focused on collaboratively developing an Innovation Management Model (MGI) for the leather agro-industrial chain in Colombia. This study integrates the participation of interested parties, the prioritization of variables, the literature review, and the validation of the model, emphasizing sustainability considerations throughout the process. The methodology involved a literature review, using Scopus and Google Scholar, focusing on innovation management models, open innovation, and sustainability of the leather sector. In addition, three surveys were conducted to prioritize the established variables, using Likert scale questions, to assess relevance and congruence. Key findings included 26 critical variables covering aspects such as agricultural and technological innovation in platforms and projects, capacity development, R&D activities, supply chain dynamics, innovation management processes, knowledge and technology integration, business model adaptation for sustainable development, and environmental impact assessment. The prioritized innovation model aims to guide stakeholders to define open innovation strategies, sustainable and regenerative innovation generation, and improvement of strategic and technological capabilities. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The selection of suppliers represents a pivotal aspect of supply chain management and has a considerable impact on the success and competitiveness of the organization in question. The selection of a suitable supplier is a multi-criteria decision making (MCDM) problem based on a number of qualitative, quantitative, and even conflicting criteria. The aim of this paper is to propose a novel MCDM approach dedicated to the supplier evaluation problem using an ordered fuzzy decision making system. This study uses a fuzzy inference system based on IF–THEN rules with ordered fuzzy numbers (OFNs). The approach employs the concept of OFNs to account for potential uncertainty and subjectivity in the decision making process, and it also takes into account the trends of changes in assessment values and entropy in the final supplier evaluation. This paper's principal contribution is the development of a knowledge base and the demonstration of its application in an ordered fuzzy expert system for multi-criteria supplier evaluation in a dynamic and uncertain environment. The proposed system takes into account the dynamic changes in the value of assessment parameters in the overall supplier assessment, allowing for the differentiation of suppliers based on current and historical data. The utilization of OFNs in a fuzzy model then allows for a reduction in the complexity of the knowledge base in comparison to a classical fuzzy system and makes it more accessible to users, as it requires only basic arithmetic operations in the inference process. This paper presents a comprehensive framework for the assessment of suppliers against a range of criteria, including local hiring, completeness, and defect factors. Furthermore, the potential to integrate sustainability and ESG (environmental, social, and corporate governance) criteria in the assessment process adds value to the decision making framework by adapting to current trends in supply chain management. [ABSTRACT FROM AUTHOR]