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A complex single-valued neutrosophic (CSVN) set is a very useful tool to handle the uncertainty, inconsistency, and ambiguity of knowledge in a periodic framework. The Schweizer-Sklar (SS) t-norm (TN) and t-conorm (TCN) enhance the flexibility of a procedure for aggregation depending on its parameters, whereas the power aggregation(PA) operator prevents insufficient impact of excessively high or low arguments on the results. Based on the idea of Schweizer-Sklar power aggregation operators, this paper aims to propose a number of aggregation operators such as complex single-valued neutrosophic Schweizer-Sklar power weighted averaging (CSVNSSPWA), complex single-valued neutrosophic Schweizer-Sklar power ordered weighted averaging (CSVNSSPOWA). Weights determination to solve green supply chain management problems in the single valued neutrosophic context is accomplished through the Simple Multi-Attribute Rating Technique (SMART). Furthermore, an example is given to show the uniqueness of the proposed operator and the difference between the proposed work and previous research. [ABSTRACT FROM AUTHOR]

Advanced manufacturing is challenging engineering perceptions of how to innovate and compete. The need for manufacturers to rapidly respond to changing requirements and demands; obtain, store, and interpret large volumes of data and information; and positively impact society and our environment requires engineers to investigate and develop new ways of making products for flexible and competitive production. In addition to the associated operational, technological, and strategic advantages for industry, advanced manufacturing creates educational, workforce, and market opportunities. Thus, this literature review is aimed at investigating the current state and emerging trends in advanced manufacturing. Specifically, this study addresses advances in manufacturing process technologies, focusing on shaping processes (mass reducing, mass conserving, and joining) as well as non-shaping processes (heat treatment and surface finishing), and metal-based additive manufacturing. This literature review finds myriad efforts have been undertaken by researchers in industry, academia, and government labs from around the world, which have supported the development and implementation of new process technologies to improve manufacturing systems extending from unit process and shop floor operations to facility and supply chain management activities. However, as evidenced by recent and emerging global challenges in energy, critical materials, and health care, the manufacturing industry must continue the innovative development of advanced materials, manufacturing processes, and systems that ensure cost-efficient, rapidly flexible, high-quality, and responsible production of goods and services. [ABSTRACT FROM AUTHOR]

With the rise and rapid development of the e-commerce industry, the pressure borne by the supply chain of e-commerce enterprises is increasing, which greatly increases the complexity and uncertainty of inventory management in the e-commerce supply chain. The study integrates system dynamics and collaborative supply chain inventory management to construct a new model. The study first uses the concept of system dynamics to optimize the supply chain inventory management system; then the collaborative supply chain is used to construct a system model by combining the optimized management system. The results show that the collaborative supply chain inventory management model constructed by the study can better accelerate the product turnover rate, improve the overall operational efficiency and market competitiveness of the supply chain, and can provide new support for the development of e-commerce enterprises. [ABSTRACT FROM AUTHOR]

For customer-oriented wood supply, buffering is required for flexibility to handle interactions in the wood procurement system. This includes balancing lead-time and operational cost by using stocks and production capacity as buffers. Despite the well-known challenge to balance the interactions between harvesting and forwarding in Nordic mechaniced CTL-operations, there has been limited research on how the machine groups can be staffed to enable flexibility and more focus on other measures to create flexibility. Therefore, this study explored trade-offs between wood lead-time and harvesting cost in the stump-to-roadside part of the wood supply chain by altering the numer of full-time working operators in the harvesting groups. This was done using discrete-event simulations implemented in Anylogic software. Input data included information about operational conditions in 1500 forest stands. The results revealed that the best balance was to have sufficient harvesting capacity to adjust wood lead times at the expense of increased harvesting costs. Of the tested options, the best balance was achieved when staffing a two-machine group with three operators, and thereby allocating 50% of the used work-shifts to regulating the field wood stock between the two machines. This resulted in the shortest lead times and the smallest harvesting cost increase. Compared to the option with no flexibility for stock adjustment (4 operators), the average lead-time could be reduced to one tenth at a cost increase of 3.4%. These findings have the potential to improve decisions of how harvesting groups are staffed to balance specific objectives of desired lead times and costs, which migh prove to be a valuable addition to the already used measures to manage wood flow. [ABSTRACT FROM AUTHOR]

Purpose: To document the pre-operative rate of clinical deterioration in a cohort of patients with split cord malformation type 1 (SCM 1) and the early- and long-term surgical outcome in these patients. Methods: Data from 41 patients with SCM 1 operated upon by the same surgeon (VR) between January 2008 to June 2023 were retrospectively reviewed with respect to history of clinical deterioration prior to surgery and early and long-term surgical outcomes. Results: The mean age of the patients at presentation was 79.3 months and the male to female ratio was 1:1.93. Twelve (29%) patients had congenital deficits whereas 4 (10%) patients had no neurological deficits. Twenty-six (63%) patients had kyphoscoliosis and 25 (61%) patients had motor dysfunction. Thirty-three (81%) patients (8/12 (67%) with congenital deficits) had clinical deterioration prior to surgery. By the age of 2 years, 56% of patients had clinical deterioration. After surgery, 18 (55%) patients with progressive symptoms had improvement in one or more of their symptoms on long-term follow-up (mean, 63.4 months). There were no predictors of surgical outcome. Conclusions: Since over half of our patients with SCM 1 developed progression of congenital deficits or developed deficits by the age of 2 years, surgery should be performed as soon as possible in these children. On long-term follow-up after surgery, improvement can be expected in over half the patients. [ABSTRACT FROM AUTHOR]

Summary: White button mushroom (Agaricus bisporus) has a wide nutritional benefit and a major drawback in supply chain management, due to its short shelf‐life of between 3 and 4 days. Postharvest spoilage caused by Trichoderma and Rhizopus including green‐mould and soft‐rot diseases causes an enormous impact on the shelf‐life of mushroom. Research work is designed to isolate the post‐harvest pathogens from mushroom and determine the effects of eight essential oils on the control of the major postharvest pathogens (T. lentinulae and R. arrhizus). Neroli and palmarosa exhibited 100% inhibition of the two pathogens at 3 and 4 μL/plate, respectively. In‐vivo studies showed that fumigation of neroli and palmarosa essential oils at concentrations of 46.2 and 61.6 μL L−1 exhibited a significant effect on the postharvest pathogens. Major components present in neroli and palmarosa are linalool and geraniol respectively. Findings concluded that neroli and palmarosa could be an efficient natural fungicide to reduce postharvest diseases in white button mushroom. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a systematic research of the effects of second source harmonics caused by gate‐source capacitance in the design of a series of continuous mode (SCM) power amplifiers (PAs) is first presented. The research results show that, compared to the conventional SCMs that require the input second harmonic to be short circuited, SCMs under the impact of input nonlinearity have a more flexible input second harmonic manipulation space, and to further improve and maintain the performance of PAs in wideband operations, a new impedance design space is explored through analysis. For practical validation, SCMs PA considering the effects of the input nonlinearity is designed and fabricated with a 10‐W gallium nitride (GaN) device, acquiring 39.1–42 dBm output power and 60.6–71.5% drain efficiency (DE) performance at a 3 dB gain compression level operating over the 0.5–3.5 GHz frequency range with a relative bandwidth of 150%. [ABSTRACT FROM AUTHOR]

In the modern, ever-shifting global agri-food environment, the topmost concern revolves around securing the safety, quality, and authenticity of agri-food products. Blockchain technology is being seen as a revolutionary solution for dealing with these issues, providing a decentralized and transparent ledger for the tracking of agri-food products. By incorporating global positioning system and navigation systems within blockchain-based traceability solutions amplifies the capabilities for real-time monitoring, security, and trust. This paper proposes a layered architecture for an efficient agri-food traceability system. The data layer, manages interactions between various entities in the supply chain management and generates agri-food product-related data. The blockchain layer manages data via transactions and smart contracts, using the interplanetary file system for secure, decentralized storage. The navigation layer, combines navigation with Indian constellation and global positioning system to offer precise real-time positioning and timing services, enhancing product tracking. This integrated approach not only improves food safety but also supports sustainability efforts by reducing food waste and bolstering consumer trust in the agri-food industry. We implement the proposed system using Remix IDE, MetaMask wallet, and the Sepolia test network, summarizing the deployment analysis. Performance evaluation is conducted using the JMeter simulation toolkit.The proposed framework achieves an average throughput of 329.26 transactions per second, latency of 49.3 ms, and response time of 87.9 ms. We conduct a comparative evaluation of the proposed system with related studies. From this comparative analysis, we observed that our proposed framework has better features than other related works. [ABSTRACT FROM AUTHOR]

AbstractThis article proposes an analytical framework of spatial-digital fix to explain how emerging online platform retailers utilize digital technologies to fix their crises in backward and forward value chains—both digitally and spatially—and their subsequent positive and negative impacts on various actors in production and distribution networks. By applying the analytical framework on Shein (an emerging online fast fashion retailer originally based in China), we demonstrate how it utilizes spatial-digital infrastructures to fix various crises/shocks across the entire value chain, from the fashion design and procurement to supply chain management through its in-house algorithmic systems, fostering an ultra-fast rate of capital accumulation. Beyond the inherently crisis-prone nature and the corresponding dark sides highlighted in the literature, we focus on the dynamic processes of capital accumulation and the corresponding fixes that lead to darker (negative) and brighter (positive) sides in various actors, from the constant pressure on cost minimization to synergistic intersections between emerging digital fast fashion retailers, subcontractors, and suppliers in the production networks. Moreover, these spatial-digital fixes are temporary and give rise to new shocks due to their inherently crisis-prone nature, from intellectual property lawsuits to labor and environmental issues. This article complements the conventional case of a race to the bottom among subcontractors by highlighting a continuum between the brighter and darker sides of Shein’s fixes and their disruptive effects on the power relationships and value distributions between incumbent fast fashion retailers, emerging online retailers, and other actors in apparel production networks. [ABSTRACT FROM AUTHOR]

After the onset of the armed conflict between Russia and Ukraine, Poland was forced to change its markets for sourcing raw materials, specifically oil and gas. Simultaneously, as a member of the EU and due to its geographical location in Europe, Poland must meet emission standards and ensure energy security. The aim of this publication is to analyze and evaluate the management of the fuel supply chain (FSC) in Poland in the context of energy security. The main research question formulated is to what extent the management of the FSC can ensure Poland's energy security. The publication employs two models: MAED (Model for Analysis of Energy Demand) and CDM (canonical distribution model). The research is based on data from the Statistical Office and data provided by the fuel industry. Between 2021 and 2023, Poland diversified its supply sources, mainly from Saudi Arabia (45.2%) and Norway (35.2%), which together account for 80.4% of imports. The current fuel storage capacity (15.05 million m3) is capable of securing production logistics in the event of SC disruptions and market uncertainties. The shift in fuel supply logistics during the discussed period, along with the increase in the fuel safety stock coefficient to quantities exceeding current demand in case of further disruptions caused by external factors, affects the security of the Polish state as well as neighboring countries in Central Europe. Distribution logistics are managed domestically through networks of fuel stations operated by Polish and foreign corporations, including a group of independently owned private fuel stations (47.5%). The fuel industry in Poland has risen to the challenge, maintaining the stability of fuel supplies and their prices. [ABSTRACT FROM AUTHOR]

Rare earth permanent magnets are vital in various sectors, including renewable energy conversion, where they are widely used in permanent magnet generators. However, the global supply and availability of these materials present significant risks, and their mining and processing have raised serious environmental concerns. This paper reviews the necessary legislative, economic, and technological measures that must be implemented to address these issues. While it may not be feasible to eliminate the risks associated with the availability of rare earth materials, researchers in the field of electrical generators can play a crucial role in significantly reducing the demand for newly mined and processed such materials, thereby mitigating the negative environmental impacts of their extraction and production. [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]

Septic Cardiomyopathy (SCM) is a syndrome of acute cardiac dysfunction in septic patients, unrelated to cardiac ischemia. Multiomics studies including transcriptomics and proteomics have provided new insights into the mechanisms of SCM. In here, a rat model of SCM was established by intraperitoneal injection of lipopolysaccharide (LPS). Biomarkers of SCM were characterized via a multi-omics analysis. The differentially expressed (DE) mRNAs predominantly appeared in pathways linked to the immune response, inflammatory response, and the complement and coagulation cascades, while DE proteins were mainly enriched in pathways associated with the complement and coagulation cascades. On this basis, the integrated analysis was performed between transcriptome and proteome. The potential biomarkers were further verified by RT-qPCR and WB. The current proteotranscriptomic research has furnished a valuable dataset and fresh perspectives that will enhance our comprehension of the development of SCM. This, in turn, is expected to expedite the formulation of novel approaches for the prevention and management of SCM in patients. [ABSTRACT FROM AUTHOR]

The document discusses the transition from Industry 4.0 to Industry 5.0, focusing on integrating human-centered touchpoints with advanced digital technologies. It emphasizes the importance of human-AI collaboration, data security, managing technological complexity, and maintaining workforce adaptability. The text also highlights the need for practical research to develop frameworks and tools for Industry 5.0 technologies, offering insights into various research directions and challenges in operations research and supply chain management. The document aims to provide researchers and managers with new perspectives and practical applications for the evolving digital operations research landscape. [Extracted from the article]

Supplier selection (SS) has emerged as a critical challenge for companies aiming to enhance the operational management of their supply chains, a task that has grown in complexity with the advent of Industry 4.0 and the ongoing digital transformation. Recognizing the gaps in current literature—specifically, the lack of consideration for stakeholders' expectations in guiding SS, as well as the inadequate handling of epistemic and stochastic uncertainties—this paper introduces a multiple-criteria Quality Function Deployment (QFD)-based model for SS. To address epistemic uncertainty, we put forward a novel subjective judgment representation method, which is named as linguistic term set integrated with discrete subjective probability distribution (LTS-DSPD), to enable decision-makers to express their judgments in a manner that is both simpler and more nuanced. Furthermore, we also give the elicitation methods and computing techniques for LTS-DSPD. Then, we integrate stakeholders' requirements, along with their preferences and expectations for these requirements to inform and guide SS. To effectively operationalize this guidance, we design the QFD-based methods to transform stakeholders' inputs into the assessment criteria for SS, the weights of criteria, and the expectations for the performances of suppliers on each criterion, respectively. To address stochastic uncertainty, we have developed an innovative methodology for characterizing it, and adopt prospect theory to quantify the overall utility of alternative suppliers. The paper concludes with a case study to demonstrate its practical application and effectiveness in streamlining SS process. [ABSTRACT FROM AUTHOR]

Supply chain efficiency is critical to enterprises and can affect their competitiveness. The supply chain faces an uncertain and complex external market environment, facing the problem of supply chain efficiency optimization; the traditional optimization method is ineffective, which can better face the current environment and deal with problems. It has advantages in optimizing supply chain efficiency and has been widely used. This paper first expounds on the importance of supply chain management status, the limitations of traditional supply chain management methods, and reinforcement learning in the application of supply chain optimization. Then, through experiments, reinforcement learning, supply chain optimization problems, and the analysis of related algorithm design, the optimal algorithm focuses on inventory management optimization. Finally, this paper points out the future research directions and development trend of the supply chain efficiency optimization algorithm based on reinforcement learning. [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]

The paper presents a novel framework for implementing decentralized algorithms based on non-fungible tokens (NFTs) for digital twin management in aviation, with a focus on component lifecycle tracking. The proposed approach uses NFTs to create unique, immutable digital representations of physical aviation components capturing real-time records of a component's entire lifecycle, from manufacture to retirement. This paper outlines detailed workflows for key processes, including part tracking, maintenance records, certification and compliance, supply chain management, flight logs, ownership and leasing, technical documentation, and quality assurance. This paper introduces a class of algorithms designed to manage the complex relationships between physical components, their digital twins, and associated NFTs. A unified model is presented to demonstrate how NFTs are created and updated across various stages of a component's lifecycle, ensuring data integrity, regulatory compliance, and operational efficiency. This paper also discusses the architecture of the proposed system, exploring the relationships between data sources, digital twins, blockchain, NFTs, and other critical components. It further examines the main challenges of the NFT-based approach and outlines future research directions. [ABSTRACT FROM AUTHOR]

Since Kraljic's strategic matrix was applied to supply chain management, classification of items, suppliers, and customers has become of increasing interest to research and companies. The aim of this research is to develop an easily interpretable multicriteria classification matrix method and validate it in real-world scenarios with a robustness analysis. This method assigns alternatives to one of four classes defined by critical dimensions that integrate several evaluation criteria. Initially, a global search pre-classifies the alternatives using the PROMETHEE net flows. Then, two local searches are carried out that make use of the discriminant properties of the net flow signs to improve the quality of the assignments. This approach is specifically applied to pre-classified alternatives near the boundary between two or more categories. The method has been validated by segmenting thousands of customers. Four customer segments were identified: strategic, collaborative, transactional, and non-preferred. A comparison was made between the results and those derived from an alternative method. Through an extensive sensitivity analysis, the proposed method was shown to be robust to parameter variation, highlighting its reliability in real dynamic contexts. The method provides valuable, easily interpretable information, which constitutes the basis for developing personalised strategies to enhance customer relationship management. [ABSTRACT FROM AUTHOR]

The development of green production types such as personalized production and shared manufacturing, which use additive technologies in city multifloor manufacturing clusters (CMFMCs), has led to an increase in last-mile parcel delivery (LMPD) activity. This study investigates the integration of electric vehicles and crowdshipping systems into smart CMMCs to improve urban logistics operations related to the distribution of products to consumers. The aim of this study is to improve the LMPD performance of these integrated systems and to provide alternative solutions for sustainable city logistics using the potential of crowdshipping and vehicle sharing fleets (VSFs) in the city logistics nodes (CLNs) of CMFMCs. The issues presented by the loading–unloading operations and sustainable crowdshipping scenarios for LMPD in CMFMCs are considered. This paper presents a new performance evaluation model for crowdshipping LMPD in CMFMCs using VSFs. The case study shows that the proposed model enables the analysis of LMPD performance in CMFMCs, taking into account their finite production capacity, and that it facilitates the planning of cargo turnover and the structure of VSFs consisting of e-bicycles, e-cars, and e-light commercial vehicles (e-LCVs). The model is verified based on a case study for sustainable LMPD scenarios using VSFs. The proposed model enables the planning of both short- and long-term logistics operations with the specified performance indicator of VSF usage in CMFMCs. The validity of using the integrated potential of crowdshipping and vehicle sharing services for LMPD under demand uncertainty in CMFMCs is discussed. This study should prove useful for decision-making and planning processes related to LMPD in CMFMCs and large cities. [ABSTRACT FROM AUTHOR]

Tea, as a key cash crop, demands year-round monitoring including the rainy months. Our study in Dehradun, Uttarakhand, India, leverages Synthetic Aperture Radar (SAR) data for its cloud-penetrating capabilities. Radar Vegetation Index (RVI) from Sentinel-1 and the Normalized Difference Vegetation Index (NDVI) from Sentinel-2 on the Google Earth Engine (GEE) platform was used. Results indicate that RVI can detect stages of tea plantation growth, even during the rainy season, while NDVI provides detailed insights into cultural operations, except rainy seasons. This method supports effective tea plantation monitoring and supply chain management across seasons. [ABSTRACT FROM AUTHOR]

Previous studies have advanced the conceptual framing of a "supply chain" to describe and examine key steps, inputs, and flows related to the production and use of seed and plant material in ecological restoration. However, these studies have paid less attention to investigating interrelationships among social actors throughout the "supply chain" stages for ecological restoration and allied activities. We applied social network analysis metrics to evaluate the number, kind, and strength of relationships among 157 social actors in the nine‐state region of the Northeastern United States, where rapid growth in restoration activities is driving a demand surge for native seed and plant materials. Restoration supply chains are more complex than previous conceptualization suggests, and we argue that the term "restoration supply networks" is more illustrative of this complexity. Results highlighted interdependency among different sectors, marked variation in input and output flows across spatial–temporal scales, and interplay among linear and nonlinear supply chain steps. The restoration supply network in the study area had a core–periphery structure, with a core comprising end‐users such as government agencies, design and build contractors, and non‐profit organizations surrounded by a periphery of seed and plant material suppliers. It is important to avoid oversimplifying seed and plant material supply chains as linear systems with strong linkages. Understanding relationship patterns among supply network actors can enhance communication, coordination, and collaboration among actors in all key restoration supply chain steps, a prerequisite to overcoming seed and plant material bottlenecks and meeting global restoration goals in the coming decades. [ABSTRACT FROM AUTHOR]

The blockchain model exposed its adaptability in various areas, including inter-banking, supply chain management, international payment, etc. The anomaly intrusion in blockchain mostly threatens the privacy and security of information, thus secure intrusion detection technique is highly essential. Presently, blockchain is incorporated into intrusion detection model for improving the overall system performance. However, the existing methods are not sufficient for detecting recent network attacks. Therefore, the blockchain-enabled intrusion detection is developed in this paper based on the Battle Royale Dingo optimization (BRDO) driven deep stacked network model. Here, a deep stacked network is applied for detecting the intrusion, and it is trained based on the optimization model for enhancing detection performance. The designed BRDO-based deep stacked network achieved improved performance than traditional techniques with regards to testing accuracy, True Positive Rate (TPR), and False Positive Rate (FPR) of 0.9106, 0.9180, and 0.9186. [ABSTRACT FROM AUTHOR]

This study highlights both theoretical as well as practical contributions to improving traceability in supply chain management with special focus on the fish supply chain. As a theoretical contribution, it highlights how blockchain technology can contribute to improving supply chain transparency in various sectors by providing real-time visibility. Concerning practical contributions, this study adopted a case study approach in the Philippines to track and trace the fish supply chain from bait to plate. It deploys a project titled 'Tracy', a blockchain-based information technology artifact to support fishermen in the Philippines, who are facing numerous challenges in the seafood industry such as different standards and regulations, requirements for international exports, catch certification, etc. This study specifically contributes to developing a smartphone app through the Tracy project that allows fishermen to view the history of their fish captures and exchanges (such as the name of the fish species, weight, and length of the fish, date of capture, and vessel name). The update of transaction histories, the identity of the fishermen, and the amount of fish that has to be sold are additional updates also made possible by this app. This research study concludes with overall study outcomes and limitations with future research. [ABSTRACT FROM AUTHOR]

Innovation continues to be a strategic priority of corporate competitiveness. Despite there is a sizable body of research that addresses how innovations influence various business outcomes, little is known as to whether and how process and product innovation may fuel/hinder the supply chain strategic fit (SCSF) and the business performance of focal small and medium-sized enterprises (SMEs). Employing structural equation modelling on data collected from 258 Korean SMEs, we find that both process and product innovations positively impact SCSF, and that improved SCSF positively influences on SME performance. Our study also suggests a non-monotonic contingency effect of environmental uncertainty on the relationship between SME innovation and SCSF. Specifically, we find that environmental uncertainty strengthens the positive effect of process innovation on SCSF but weakens the positive impact of product innovation on SCSF. Our study contributes to the innovation and supply chain management literature with novel theoretical and managerial knowledge on how to manage innovation and SCSF under different environmental conditions. [ABSTRACT FROM AUTHOR]

Problem Blood is a rare perishable substance with limited life in the real world and blood supply chain management is a vital subject. Hence, it is trying to design an efficient supply chain network to create a balance between blood supply and demand, particularly in deficient conditions. One effective solution for blood deficiency compensation is the use of incentive programs at the right times to encourage people for blood donation. The novel aspect of this study considers a new mathematical model to design a blood supply chain network with the location of temporary centers for collecting donated blood, in addition to incentive programs in the right periods to actualize the goal of creating blood supply-demand equilibrium and minimizing the cost of the network. Method In this paper, four methods have been used in different dimensions to solve the proposed model. In this case, augmented epsilon constraint (AEC/EC) was used for small dimensions, while electromagnetic algorithm (EM), Non-dominated ranked genetic algorithm (NRGA), and non-dominated sorting genetic algorithm (NSGA-II) were used for large dimensions due to the inherent complexity of the problem. Results The performance of algorithms was analyzed based on the four standard indicators. Then, their outputs were evaluated using statistical assumption tests at the significance level of 0.05. In three considered indicators (SNS, MID, and TIME indicators), the NSGA-II algorithm outperformed the NRGA and EM algorithms. This case indicated the superiority of the NSGA-II algorithm over the NRGA and EM algorithms especially for problem solution time, which is one of the most significant indicators used in metaheuristic algorithms. [ABSTRACT FROM AUTHOR]

In today's globalized world, characterized by complex supply chain networks, integrating sustainability supply chain risks into the corporate assessment models seems crucial. To tackle the global challenges this paper presents a Sustainability Risk Assessment Framework that allows measurement of environmental and social risks upstream and downstream, along global supply chains, using a combination of quantitative methods (environmental and social footprint computing tools) and qualitative methods (hotspots analysis) from three dimensions (by scenarios, by product components, by lifecycle stage). To test this framework this study focuses on the mobile phone industry, due to the importance of its environmental and social impacts. The results show the low impact of recycling strategies in environmental terms and social terms on the mobile phone industry. Fostering re-use strategies by companies will substantially improve their impacts. This framework overcomes some of the weaknesses of the corporate sustainability risk assessment methodologies, combining quantitative methods and qualitative methods. [ABSTRACT FROM AUTHOR]

Background: Sustainable supply chain management encompasses the strategic coordination and control of material, information, and financial flows, as well as the collaborative efforts among the entities engaged in the medicinal supply chain. This research proposes a dynamic and sustainable supply chain management model tailored explicitly for the inpatient pharmacies of Medical Centers and Hospitals affiliated with Iran University of Medical Sciences. Methods: This is a quantitative study in terms of research objective and a qualitative study based on the stages in the conceptual development of the model. Therefore, the current study can be considered a mixed-methods approach. After identifying the key factors influencing the sustainability of the medicine supply chain, we conducted a dynamic analysis of the problem using system dynamics methodology. In order to simulate the system's behavior over 24 months, we utilized a combination of existing documentary information and expert opinions. The developed model was implemented using Vensim PLE software, allowing us to simulate and analyze the impact of various policies on the system. Results: Medicine disposal exhibited an upward trend, particularly during the second 12-month period. Conversely, the trend of medicine expirations remained relatively stable in the initial months but showed an upward trajectory after that. The cost associated with disposed medicine experienced a consistent increase, with a higher rate observed during the second 12-month period. In contrast, sales of low-consumable medicine experienced a significant initial surge followed by a slower growth rate. Finally, the pharmacy's profit demonstrated an overall increasing trend, although the rate of increase was higher during the first 12 months. Conclusion: Among the various scenarios considered, namely "increasing the adequacy of human resources," "increasing the speed of response," and "utilizing pharmacists in the drug prescribing team," it was found that these interventions had a substantial effect on both enhancing the pharmacy's profit and reducing medication waste. Therefore, these scenarios were identified as having the most significant impact. The proposed model can serve as a valuable tool for forecasting and informing policy-making, providing insights into addressing the challenges associated with the sustainable drug supply chain in hospital pharmacies. [ABSTRACT FROM AUTHOR]

Background: When running a randomized controlled trial (RCT), a clinical site may face a situation when an eligible trial participant is to be randomized to the treatment that is not available at the site. In this case, there are two options: not to enroll the participant, or, without disclosing to the site, allocate the participant to a treatment arm with drug available at the site using a built-in feature of the interactive response technology (IRT). In the latter case, one has employed a "forced randomization" (FR). There seems to be an industry-wide consensus that using FR can be acceptable in confirmatory trials provided there are "not too many" instances of forcing. A better understanding of statistical properties of FR is warranted. Methods: We described four different IRT configurations with or without FR and illustrated them using a simple example. We discussed potential merits of FR and outlined some relevant theoretical risks and risk mitigation strategies. We performed a search using Cortellis Regulatory Intelligence database (IDRAC) (www.cortellis.com) to understand the prevalence of FR in clinical trial practice. We also proposed a structured template for development and evaluation of randomization designs featuring FR and showcased an application of this template for a hypothetical multi-center 1:1 RCT under three experimental settings ("base case", "slower recruitment", and "faster recruitment") to explore the effect of four different IRT configurations in combination with three different drug supply/re-supply strategies on some important operating characteristics of the trial. We also supplied the Julia code that can be used to reproduce our simulation results and generate additional results under user-specified experimental scenarios. Results: FR can eliminate refusals to randomize patients, which can cause frustration for patients and study site personnel, improve the study logistics, drug supply management, cost-efficiency, and recruitment time. Nevertheless, FR carries some potential risks that should be reviewed at the study planning stage and, ideally, prospectively addressed through risk mitigation planning. The Cortellis search identified only 9 submissions that have reported the use of FR; typically, the FR option was documented in IRT specifications. Our simulation evidence showed that under the considered realistic experimental settings, the percentage of FR is expected to be low. When FR with backfilling was used in combination with high re-supply strategy, the final treatment imbalance was negligibly small, the proportion of patients not randomized due to the lack of drug supply was close to zero, and the time to complete recruitment was shortened compared to the case when FR was not allowed. The drug overage was primarily determined by the intensity of the re-supply strategy and to a smaller extent by the presence or absence of the FR feature in IRT. Conclusion: FR with a carefully chosen drug supply/re-supply strategy can result in quantifiable improvements in the patients' and site personnel experience, trial logistics and efficiency while preventing an undesirable refusal to randomize a patient and a consequential unblinding at the site. FR is a useful design feature of multi-center RCTs provided it is properly planned for and carefully implemented. [ABSTRACT FROM AUTHOR]

In the rapidly evolving digital era, efficiency and transparency are key to gaining a competitive edge in business. Blockchain technology has emerged as a revolutionary solution with the potential to enhance transparency, security, and efficiency in the supply chain. While many large companies have adopted it for various benefits, challenges such as scalability, interoperability, and legal uncertainties still hinder the widespread adoption of blockchain. This research utilizes a literature review to explore the challenges and benefits of implementing blockchain in the supply chain, as well as strategies to enhance data security, transparency, and efficiency. The findings indicate that blockchain can improve transparency, security, and efficiency in the supply chain, but there are still challenges to be addressed. Nonetheless, with proper investment and development, the potential benefits of blockchain in supply chain management (SCM) are significant. [ABSTRACT FROM AUTHOR]

The semiclassical particle-rotor model (SCM) has been used for the calculation of reduced electric quadrupole transition rates B(E2) for the ν h 1 1 / 2 negative parity band in 1 0 1 Ru. The B(E2) values are found to exhibit a decreasing behavior with increasing spin values in the range 27/2 ℏ ≤ I ≤ 47/2 ℏ. For the higher spin states, the experimental dynamic moment of inertia ℑ (2) is also in the range of AMR bands. The calculation of spin (ℏ) versus frequency (MeV) for the π (g 9 / 2) − 2 ⊗ ν [ h 1 1 / 2 (g 7 / 2) 2 ] configuration with the core contribution of 2 ℏ is found to be in good agreement with the experimental results and favors the possibility of AMR phenomenon in ν h 1 1 / 2 negative parity band in 1 0 1 Ru. [ABSTRACT FROM AUTHOR]

Over the past few decades, sustainability has attracted massive attention at the local, regional, and national levels. Building and construction industry is one of the main areas in which, due to its nature of activities, prioritizing and identifying its key supply chain parameters are of core elements of sustainable development programs. In this paper, economic, social, and environmental indicators are investigated using a developed hybrid model based on BWM, AHP, SWARA to identify and prioritize the significant parameters in this field. 21 different indicators are analyzed by Likert scale according to their role in progress toward sustainable development. The criteria weights are achieved through a survey of 10 academic and industrial experts whose research interests are sustainability and supply chain management. The Copeland methodology has been used to integrate the output of three models and draw the final result. The results showed that from economic point of view 'Tech-econ evaluation', in social aspects 'Employees' health and safety', and in environmental aspects 'Developing green technologies in supply chain' have reported the highest final dominant scores in Copeland methodology respectively. The proposed model is expected to help industrial experts and managers to identify key sustainable parameters of supply chain in construction industry and set their goals toward sustainability accordingly. [ABSTRACT FROM AUTHOR]

This study aims to analyze the effect of Procurement Digitalization Capability, Collaborative Supply Chain Management, Operational Capability through Competitive Advantage on Sustainable Business Performance at Geothermal Energy Company Partners. The method used in this research is quantitative method, where this research uses surveys and questionnaires distributed to vendors or partners of the Geothermal Energy Company as the object of research. The research sample was selected using purposive sampling with the acquisition of 115 respondents. This study uses data testing methods using validity and reliability tests on each variable studied. While the data analysis method used in this research is the Structural Equation Model (SEM) with AMOS software. The results showed that the direct relationship between the Procurement Digitalization Capability variable had a positive effect on Competitive Advantage. Collaborative Supply Chain Management variables have no positive effect on Competitive Advantage. While Operational Capability has a positive effect on Competitive Advantage and finally Competitive Advantage has a significant positive effect on Sustainable Business Performance. Based on the results of this study, it is recommended for further research to be able to develop research in different industries and with a broader scope. [ABSTRACT FROM AUTHOR]

This research focuses on determining the level of inventory in a downstream supply chain for fuel products in Indonesian oil and gas company prespective. The variability in supply and demand is a problem in maintaining the stability of services to the consumers. High inventory costs that are completely borne by the company are also a problem that needs to be controlled. Therefore, determining inventory levels is very important to mitigate the variability of supply and demand that occurs with optimum inventory costs. This research designs a probabilistic model by considering variability in supply and demand to determine safety stock so that the correct level of Fuel Product inventory at each Storage Point can be determined. This research method is quantitative research based on empirical data. It is hoped that the research results will be able to obtain inventory control which can be taken into consideration by oil and gas company in managing the downstream supply chain of fuel products. [ABSTRACT FROM AUTHOR]

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]

This research note explores how logistics, though often overlooked, is a central element in space fantasy science fiction narratives. In Frank Herbert's Dune, the spice--essential for interstellar travel--demonstrates how logistics influences space geopolitics. Star Wars highlights the logistical challenges involved in managing an intergalactic empire, from constructing the Death Stars to coordinating rebel fleets. In Star Trek, space exploration depends on intricate logistics to sustain ships, space stations, and diplomatic relations. Finally, Isaac Asimov's Foundation illustrates how the collapse of logistics can lead to the downfall of an intergalactic empire. These films and novels reveal that logistics extends beyond mere materials and operations management; it becomes a key question of survival, power, and stability within these fictional universes. Science fiction narratives not only offer insights into future logistics but also prompts reflection on contemporary challenges in supply chain and infrastructure management. [ABSTRACT FROM AUTHOR]

Purpose: The ability of a business to outperform its rivals is known as its competitive edge, and it presents special difficulties in the context of the "digital revolution," or the fourth industrial revolution. To obtain a competitive edge in the startup operations 4.0 era, this study aims to examine the organizational, technological and competence-related challenges presented by Industry 4.0. It does this by concentrating on the tools, competencies, methods, approaches, tools and strategies that are crucial. Using the Total Interpretive Structural Modeling (TISM) technique, the goal is to find, analyze and classify enablers for startup operations 4.0. Design/methodology/approach: A closed-ended questionnaire and planned interviews were used in the data collection process. In startup operations 4.0, the cross-impact matrix multiplication applied to classification method is used to rank and categorize competitive advantage factors, whereas the TISM technique is used to analyze how components interact. Findings: The study highlights the critical significance of the "Internet of Things (IoT)," "information technologies," "technological platforms," "employee empowerment," "augmented reality (AR)" and "operational technologies" in its identification of 12 enablers for startup operations 4.0. Research limitations/implications: The main focus of the study is on the variables that affect startup operations 4.0's competitive advantage. Practical implications: Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research. Originality/value: Large businesses have been profoundly impacted by Industry 4.0 principles; however, startup operations 4.0's competitive advantage has not received as much attention. This paper offers a fresh take on the concept of competitive advantage in startup operations 4.0 research. [ABSTRACT FROM AUTHOR]

Blockchain consensus mechanisms play a critical role in ensuring the security, decentralization, and integrity of distributed networks. As blockchain technology expands beyond cryptocurrencies into broader applications such as supply chain management and healthcare, the importance of efficient and scalable consensus algorithms has grown significantly. This study provides a comprehensive bibliometric analysis of blockchain and consensus mechanism research from 2014 to 2024, using tools such as VOSviewer and R's Bibliometrix package. The analysis traces the evolution from foundational mechanisms like Proof of ork (PoW) to more advanced models such as Proof of Stake (PoS) and Byzantine Fault Tolerance (BFT), with particular emphasis on Ethereum's "The Merge" in 2022, which marked the historic shift from PoW to PoS. Key findings highlight emerging themes, including scalability, security, and the integration of blockchain with state-of-the-art technologies like artificial intelligence (AI), the Internet of Things (IoT), and energy trading. The study also identifies influential authors, institutions, and countries, emphasizing the collaborative and interdisciplinary nature of blockchain research. Through thematic analysis, this review uncovers the challenges and opportunities in decentralized systems, underscoring the need for continued innovation in consensus mechanisms to address efficiency, sustainability, scalability, and privacy concerns. These insights offer a valuable foundation for future research aimed at advancing blockchain technology across various industries. [ABSTRACT FROM AUTHOR]

This scientific attempt is dedicated to model and solve the production inventory system (PIS) in supply chain (SC). The original problem is modelled by an Optimal Control Problem (OCP) with disturbance term and stochastic deterioration in two levels SC that it is possible to return the goods. As we know, this research is the first attempt for modelling and resolving such a PIS in supply chain management (SCM) with stochastic deterioration. The SC model contains two-level; Each level consists of a firm and each firm has a manufacturing factory and a recycling. Also, items are broken down according to Weibull distribution and returned to the firm for recycling. The SC is modelled as a dynamic system and then is reformulated as an OCP. The OCP is changed to a system of equations so that an artificial neural network (ANN) is provided to solve it. For demonstrating the proposed scheme's effectiveness, performance, and efficiency of the model a real-world problem and an example are given. The results of validation and sensitivity analysis show the convergence of the variables' response to the target values and their logical behavior against the change of parameters. [ABSTRACT FROM AUTHOR]

Integrated photovoltaic-fuel cell (IPVFC) systems have the potential to contribute to sustainable energy production for grid and off-grid applications. While there are studies focusing on fundamental science and designs for IPVFC systems, there are few studies that have focused on the manufacturability of IPVFC systems, which is certainly the pathway for the commercialisation of the systems. This study explores manufacturing strategies that can be considered for exploiting a family of eleven IPVFC systems. A survey and systems thinking approach were used to investigate the potential modularisation and supply chain management of the systems to achieve an optimal lean and agile manufacturing strategy. Results show that the Photovoltaic-Thermal-Separate Converter-Inverter-Battery System received 25% of the responses. The optimal manufacturing strategy depends on the overall business strategy of the firm. The 17% preference for System 1 was significant compared to four members of the family of IPVFC systems (Systems 2, 6, 8 and 9) that received only 2% of the responses, and there is a likelihood that the demand for System 1 will be among the top 42% of the total demand of all the systems. Overall, this study provides new insights into how the family of IPVFC systems can contribute to realising greater access to cleaner energy, by extension contributing to net-zero efforts using solar energy and solar hydrogen. [ABSTRACT FROM AUTHOR]

The maritime operations present several pain points, such as low transparency, poor paperless efficiency, and difficult trust management among supply chain participants. Blockchain is emerging as an innovative technology that solves pain points of maritime operations. Blockchain adoption in the maritime literature remains scarcely investigated, especially in identifying potential factors that may affect blockchain adoption intention. Based on the technological-organizational-environmental (TOE) framework, this study develops the research model to examine the determinants of blockchain adoption intention. Data collected from 161 firms in Taiwanese maritime industry were used to test the hypotheses in the research model. The findings revealed that knowledge absorption capability is the most important enablers of blockchain adoption in the organizational context, followed by perceived relative advantage in the technological context, and trading partner influence in the environmental context. Unexpectedly, perceived complexity does not appear to be decisive in predicting blockchain adoption intention. This study also discusses theoretical and managerial implications by providing valuable insights into the determinants of blockchain adoption intention. [ABSTRACT FROM AUTHOR]

The supply chain forms the backbone of the modern consumer economy, weaving an intricate network of stakeholders across geographical and socioeconomic divides. While new technologies have enhanced supply chain management, the market dynamism and network complexities continue to challenge decision-makers. This study employs social network analysis and text mining to unravel technological patterns within the patent landscape of supply chain management. The analysis draws on a dataset of over 32,000 supply chain patents from Lens.org spanning 2000–2022. Network analysis reveals cooperation patterns and key players, while text mining and clustering identify five technology clusters: secure access control, manufacturing, logistics, data management, and RFID. Technology life cycle analysis indicates that secure access control, data management, and RFID have reached maturity, while logistics is still growing and manufacturing faces saturation. The findings highlight that despite maturity, these technologies warrant continued investment to resolve persistent challenges. The technology trends and maturity insights uncovered can help enterprises make informed strategic decisions by aligning R&D initiatives with technology lifecycles. This pioneering study bridges innovation research and technology management, offering a nuanced understanding of supply chain technologies. The framework presented can be extended to analyze other domains, opening avenues for further research. Overall, this study decodes the patent landscape to decode the future. [ABSTRACT FROM AUTHOR]

PurposeMethodology/approachFindingsResearch implicationsPractical implicationsOriginality/value/contributionThis study aims to investigate the underlying psychological mechanism and the boundary conditions of the effects supplier customization (SC) on its performance in supply chain management (SCM).Based upon the contract theory, the study explores how SC influences its performance by revealing mediating role of customer entitlement (CE), and examines the boundary conditions of contractual governance (CG). The dyadic questionnaire survey data of 111 supplier and customer firms in China were used to validate a moderated mediation model.It is found that SC enhances its performance through the increased CE. Furthermore, the above consequential link is moderated by both contractual completeness (CCP) rather than contractual enforcement (CEF). Specifically, CCP negatively moderates the indirect effect of SC on SP through CE. However, CEF negatively moderates the direct effect of SC on CE.This research are really limitations, including its focus on single industry; single-country system; its cross-sectional design; and the oversight of the possible impact of relational governance (RG) on the link between buyers and sellers.Executives should always attach importance to the development of psychological contract (PC), and managers should identify the underlying psychological mechanisms of a customization strategy in B2B and use contractual design and execution with caution.The study extends the literature of the psychological mechanism and more granular characterization of CG, and provides insights for managers to recognize reasonable governance tactics in the context of SCM. [ABSTRACT FROM AUTHOR]

Purpose: Sagittal imbalance is common in degenerative and congenital spinal diseases. Some studies have examined spinal deformities in the spina bifida. However, sagittal spinopelvic parameters in tethered cord syndrome (TCS) and split cord malformation (SCM) have been poorly evaluated in the literature. In this study, we investigated sagittal spinopelvic differences in TCS due to fatty filum terminale and SCM patients. Material and Methods: A total of 78 patients with spina bifida occulta (30 SCM and 48 TCS due to fatty filum terminale) were included in the study. Radiological images of these patients were retrospectively evaluated. We evaluated the pelvic incidence, pelvic tilt, sacral slope, sagittal vertical axis (SVA), T1 pelvic angle, lumbar lordosis (LL), thoracic kyphosis, thoracolumbar alignment, and change in those parameters with age. Results: Correlation coefficients between age and LL, T1 pelvic angle, and the SVA in patients with TCS due to fatty filum terminale were statistically significant. In addition, correlation coefficients between age and LL and the SVA in patients with SCM were statistically significant. Notably, LL was increased at a statistically significant level with age in patients with TCS and SCM. Conclusion: Improved knowledge of spinal balance parameters in patients with TCS and SCM may be helpful in understanding the clinical course of these pathologies, and provide information regarding the success of surgery at the follow-up period. [ABSTRACT FROM AUTHOR]

Advanced manufacturing is challenging engineering perceptions of how to innovate and compete. The need for manufacturers to rapidly respond to changing requirements and demands; obtain, store, and interpret large volumes of data and information; and positively impact society and our environment requires engineers to investigate and develop new ways of making products for flexible and competitive production. In addition to the associated operational, technological, and strategic advantages for industry, advanced manufacturing creates educational, workforce, and market opportunities. Thus, this literature review aims to investigate the current state and emerging trends in advanced manufacturing. Specifically, this study addresses advances in manufacturing from manufacturing systems perspective, concentrating on emerging trends in process sensing and monitoring, equipment control and automation, machine tools, sustainable manufacturing, and green supply chain management. This review finds myriad efforts have been undertaken by researchers in industry, academia, and government labs from around the world, which have supported the development and implementation of new process technologies to improve manufacturing systems extending from unit process and shop floor operations to facility and supply chain management activities. However, emerging global challenges remain in various domains including energy (e.g., resource scarcities and global warming), critical materials vulnerable to supply disruptions due to crisis and rapid changes in demand, and services (e.g., healthcare supply chains during COVID-19 pandemic). Thus, manufacturing industry must continue the innovative development of advanced materials, manufacturing processes, and systems that ensure cost efficient, rapidly flexible, high quality, and responsible production of goods and services. [ABSTRACT FROM AUTHOR]

Resilience is a topic that has recently emerged concerning the basics of the construction project supply chain and we can consider it as a response to disruption in the supply chain of the project. Disruption also is an unavoidable reality in today's complex and dynamic construction supply chain, the occurrence of which can cause irretrievable damages to the system, such as financial losses. Successful companies seek to minimize disruption and maintain adequate supply chain performance before disruption occurs, rather than looking for costly and challenging post-disruption solutions. This paper covers this gap by proposing a scenario-based mixed integer-programming model aiming to minimize logistics costs and delays, while scheduling projects to address selecting the appropriate supplier at risk of disruption. So far, this quantitative view was not presented in discussions about disruptions in the project supply chain, therefore different scenarios are applied in the process to validate the model. To improve its resilience level, this model benefits from back-up suppliers' strategy. This study focuses on providing the required materials for the project site in an emergency without incurring additional costs using a back-up supplier. Results reveal the model's suitability in confronting the unavailability of a supplier due to disruption. [ABSTRACT FROM AUTHOR]

A drug supply chain comprises the entire process starting from producing a drug using raw materials to delivering it to the consumer. To ensure safe and reliable delivery of drugs to consumers, a well-managed Supply Chain Management (SCM) system is needed. In traditional SCM systems, tracking a drug throughout the chain is difficult, which increases the chances of counterfeiting drugs. Moreover, traditional SCM systems face the scalability issue because they can process limited information. In this paper, a blockchain-based scheme is proposed by using the InterPlanetary File System (IPFS) to solve the problems of traditional SCMs. Here, the information generated during the manufacturing of drugs, as well as the details of transactions, are stored in the IPFS, so that no data can be tampered with at any time. In the proposed scheme, smart contracts are implemented to automate the execution of the entire SCM system, and the Proof of Work (PoW) consensus algorithm is used to validate the transactions. Many experiments are performed to evaluate the performance of the proposed scheme in terms of throughput, communication cost, and many more. Security analysis and performance analysis of the proposed scheme show its efficiency compared to the well-known existing schemes. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has struck the construction industry gravely. Accordingly, numerous studies reported the impact of COVID-19 on various aspects of the construction industry and projects. However, there exists no framework that can guide the evaluation of holistic impact of COVID-19 on a construction project specifically for developing countries. To fulfill this knowledge gap, this study conducted state-of-the-art review of recent related journal articles from developing countries and developed an eight-dimensional assessment framework to assess the impact of COVID-19 on construction projects. These eight dimensions include: (1) on-site safety measures, (2) productivity, (3) supply chain management, (4) transportation, (5) labor issues, (6) time and cost performances, (7) contractual implications, and (8) social impact. Additionally, to demonstrate the usefulness of the framework, the study utilized the framework to assess four projects in three developing countries: Saudi Arabia, Pakistan, and Bangladesh. Finally, the study presented the best practices to mitigate the impacts of any future wave of COVID-19 on construction projects. The developed framework holds potential applications ranging from policy planning to construction operations under COVID-19 and similar pandemics. It can be implemented to assess the impacts of COVID-19 on the construction industry, evaluating project performance across eight dimensions. Moreover, it aids in the development of COVID-19 impact management actions to control project performance. Additionally, the framework assists in building organizational resilience for managing construction projects under the challenges posed by COVID-19 or similar pandemic scenarios. [ABSTRACT FROM AUTHOR]

The ongoing research employs both the neutrosophic set and the Decision Making and Evaluation Method (DEMATEL) to analyze and determine the factors influencing supplier selection within the realm of Supply Chain Management (SCM). Recognized as a proactive strategy for enhancing performance and securing competitive advantages, DEMATEL guides this investigation. The study utilizes neutrosophic set Theory to refine overall assessments, introducing a novel scale to distinctly represent each value. Through a practical case study focusing on selecting the optimal supplier for a distribution company, the proposed methodology's application is illustrated. The research framework integrates a neutrosophic DEMATEL approach for data collection, incorporating surveys among experts and interviews with professionals in management, procurement, and production. In addressing application-oriented challenges characterized by multiple criteria marked by ambiguity and varying degrees of accuracy, Smarandache introduced Treesoft sets an extension of hypersoft sets to effectively navigate through ambiguous and imprecise options. [ABSTRACT FROM AUTHOR]

The ultimate bearing capacity of a strip footing placed horizontally over the edge of a sloping rock mass has been determined on the basis of the stress characteristics method (SCM) using the generalized Hoek–Brown yield criterion. The effect of footing–rock interface roughness on the results has also been analyzed. The problem has been solved, in addition, with the usage of the adaptive mesh–based finite-element limit analysis (FELA) method. The results are provided in the form of nondimensional bearing capacity factor (Nσ) as a function of different input material parameters for several slope inclinations. After analyzing all the results, an expression on the basis of the regression analysis has also been generated to compute the factor Nσ as a function of different input variables. The bearing capacity obtained from the SCM has been found to lie between the lower and upper bounds of the FELA, and the failure patterns from the two sets of analyses match quite closely with each other for both smooth and rough footings. The results are also found to be in good agreement with the existing solutions from the literature. [ABSTRACT FROM AUTHOR]