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This research examines the transformative potential of artificial intelligence (AI) in general and Generative AI (GAI) in particular in supply chain and operations management (SCOM). Through the lens of the resource-based view and based on key AI capabilities such as learning, perception, prediction, interaction, adaptation, and reasoning, we explore how AI and GAI can impact 13 distinct SCOM decision-making areas. These areas include but are not limited to demand forecasting, inventory management, supply chain design, and risk management. With its outcomes, this study provides a comprehensive understanding of AI and GAI's functionality and applications in the SCOM context, offering a practical framework for both practitioners and researchers. The proposed framework systematically identifies where and how AI and GAI can be applied in SCOM, focussing on decision-making enhancement, process optimisation, investment prioritisation, and skills development. Managers can use it as a guidance to evaluate their operational processes and identify areas where AI and GAI can deliver improved efficiency, accuracy, resilience, and overall effectiveness. The research underscores that AI and GAI, with their multifaceted capabilities and applications, open a revolutionary potential and substantial implications for future SCOM practices, innovations, and research. [ABSTRACT FROM AUTHOR]

ChatGPT and generative artificial intelligence (Gen-AI) are transforming firms and supply chains. However, the empirical literature reporting the benefits, challenges, and outlook of these nascent technologies in operations and supply chain management (OSCM) is limited. This study surveys current projects and perceptions of these technologies in US (n = 119) and UK (n = 181) supply chains. We found that projects range from proof-of-concept to full implementation, with a main focus on operational gains, such as improved customer satisfaction, cost minimisation, and process efficiencies. The main challenges concern data, technological and organisational issues. Expected benefits are dominated by cost savings and enhanced customer experience, but also include increased automation and sustainability. Industries were found to cluster around six groups according to perceived benefits and implementation challenges. Our findings contribute to the emerging literature on Gen-AI use in OSCM, and to management practice by mapping the benefits, challenges, outlook, and maturity level of Gen-AI projects in supply chains. [ABSTRACT FROM AUTHOR]

Modern supply chains are complex, interconnected systems that contain emergent, invisible dependencies. Lack of visibility often hinders effective risk planning and results in delayed discovery of supply chain problems, with examples ranging from product contamination, unsustainable production practices, or exposure to suppliers clustered in geographical areas prone to natural or man-made disasters. Initiatives that rely on manual collection of data often fail due to supply chain complexity and unwillingness of suppliers to share data. In this paper, we propose a neurosymbolic machine learning technique to proactively uncover hidden risks in supply chains and discover new information. Our method uses a combination of graph neural networks and knowledge graph reasoning. Unlike existing research our model is able to infer multiple types of hidden relationship risks, presenting a step change in automated supply chain surveillance. The approach has been tested on two empirical datasets from the automotive and energy industries, illustrating that it can provide inference in multiple types of links such as companies, products, production capabilities, certifications; thereby facilitating complex queries that go beyond who-supplies-whom. As such, additional risk insights can emerge from graph structure, providing practitioners with new knowledge. [ABSTRACT FROM AUTHOR]

International trade, through global supply chains, is central to global sustainable production and consumption. Redistribution of environmental resources impacts through international trade has become apparent in ecological research – and may have long-term design and planning implications for production and supply chain management. However, current trade and production accounting methods are still incapable of providing accurate and reliable results for policymakers and organisational decision makers to manage global and supply chain trade issues. In this study, a blockchain-based conceptual framework for embodied environmental resources accounting in trade is proposed to address global supply chain and trade issues. Framework design, benefits, and challenges are also discussed. Future research and linkage to theory are also provided. This study provides a strong systemic foundation for managing environmental resources at the nexus of international trade, sustainable production, and global supply chains. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has emerged as a complementary technology in supply chain research. However, the majority of AI approaches explored in this context afford little to no explainability, which is a significant barrier to a broader adoption of AI in supply chains. In recent years, the need for explainability has been a strong impetus for research in hybrid AI methodologies that combine neural architectures with logic-based reasoning, which are collectively referred to as Neurosymbolic AI. The aim of this paper is to provide a comprehensive overview of supply chain management literature that employs approaches within the neurosymbolic AI spectrum. To that end, a systematic review is conducted, followed by bibliometric, descriptive and thematic analyses on the identified studies. Our findings indicate that researchers have primarily focused on the limited subset of neurofuzzy approaches, while some supply chain applications, such as performance evaluation and sustainability, and sectors such as pharmaceutical and construction have received less attention. To help address these gaps, we propose five pillars of neurosymbolic AI research for supply chains and provide four use cases of applying unexplored neurosymbolic AI approaches to address typical problems in supply chain management, including a discussion of prerequisites for adopting such technologies. We envision that the findings and contributions of this survey will help encourage further research in neurosymbolic AI for supply chains and increase adoption of such technologies within supply chain practice. [ABSTRACT FROM AUTHOR]

Blockchain (BC) applications in supply chain management (SCM) have recently received extensive attention. It is important to synthesise the extant literature on the field to identify key research themes and navigate potential future directions. This study thus develops an efficient, scalable data-driven review approach that uses text mining and Latent Dirichlet Allocation (LDA)-based topic modelling for automatic content analysis of full-text documents. Our method overcomes the drawbacks of traditional systematic literature reviews using either manual coding or bibliographic analysis for article classifications, which are highly time-consuming and biased when dealing with large amounts of text. 108 papers published between 2017 and 2022 were analysed which identified 10 key research themes, including revenue management, sustainability, traceability, manufacturing system, scheduling in cloud manufacturing, healthcare SCM, anti-counterfeit system, logistics and transportation, system architecture development, and food & agriculture SC. Five future directions are then suggested, including (1) integration of BC and other emerging technologies for global and scalable SCM, (2) crypto-X applications in SCM, (3) BC-enabled closed-loop SCM, (4) the environmental and social impacts of BC-based SCM and (5) decentralised autonomous organisations in SCM. [ABSTRACT FROM AUTHOR]

Accepted by: Aris Syntetos Machine learning (ML) has evolved into a crucial tool in supply chain management, effectively addressing the complexities associated with decision-making by leveraging available data. The utilization of ML has markedly surged in recent years, extending its influence across various supply chain operations, ranging from procurement to product distribution. In this paper, based on a systematic search, we provide a comprehensive literature review of the research dealing with the use of ML in supply chain management. We present the major contributions to the literature by classifying them into five classes using the five processes of the supply chain operations reference framework. We demonstrate that the applications of ML in supply chain management have significantly increased in both trend and diversity over recent years, with substantial expansion since 2019. The review also reveals that demand forecasting has attracted most of the applications followed by inventory management and transportation. The paper enables to identify the research gaps in the literature and provides some avenues for further research. [ABSTRACT FROM AUTHOR]

This article aims to provide an overview of the current state of research on artificial intelligence in logistics, focusing on identifying key thematic areas addressed by the authors in this field. The article analyzes specific thematic areas that are the subject of individual studies dealing with this issue. Various methodological approaches were used in the analysis, including bibliometric analysis aimed at mapping the development of research and identifying key publications in the field of artificial intelligence in logistics. The PRISMA method was applied to select relevant sources, while qualitative content analysis was used for an in-depth evaluation of the studies' content and for identifying the most frequently covered theoretical areas. The results show that research on artificial intelligence in logistics focuses on diverse thematic areas, such as digital transformation, sustainability and environmental aspects, process optimization within supply chains, and human-machine interaction. This article provides valuable insights for experts and practitioners in the field of logistics and serves as a foundation for further research in this dynamically evolving area. [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]

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]

Efficient risk management within the supply chain is essential for municipal success. This study assesses the supply chain risk management procedures of the Thulamela Municipality to guarantee service delivery. The main objectives were to evaluate the municipality's risk management structure and recommend enhancements in accordance with the MFMA and King IV requirements. The study question examined the implementation of a risk management system by Thulamela to guarantee service delivery. Utilising risk management and institutional theory, the study adopted a mixed-methods approach, applying deductive thematic analysis and SPSS software to examine data regarding the municipality's risk management procedures, team expertise, and framework suitability. The findings reveal that although Thulamela possesses a supply chain risk management framework, enhancements are necessary, specifically in (i) empowering the risk management team, (ii) incorporating technology and maintaining a record of suppliers with a history of non-compliance, and (iii) augmenting staff's risk management expertise. A favourable correlation was observed among effective risk management, institutional theory, supply chain procedures, and service delivery. This report provides essential information for policymakers to improve municipal supply chain risk management. Future research may investigate the impact of technology on mitigating risks such as non-compliance, corruption, and supplier failures, and also analyse the risk management frameworks among South African municipalities. [ABSTRACT FROM AUTHOR]

The Fourth Industrial Revolution has transformed industries and supply chains by integrating advanced operations, tools, and logistics services. Despite these advancements, challenges persist, particularly in ensuring data dependability, security, and operational efficiency. Digital twins (DTs), which replicate real-world components and processes, have emerged as essential tools for enhancing predictive analytics, simulation, and product lifecycle management in Industry 4.0. However, traditional DT development relies on centralized systems, which are vulnerable to data tampering and security breaches, especially in the management of transaction logs and historical data. To address these challenges, this review provides a comprehensive analysis of the current state of integrating blockchain with DTs. Using a qualitative research methodology, including desk research, case studies, and interviews with industry experts, we analyze various blockchain-based DT applications across industries and specifically in supply chain management. The findings reveal that blockchain-enhanced DTs can significantly improve data integrity, traceability, and security, thus boosting operational efficiency and quality control in supply chains. Additionally, this study identifies key integration techniques and the role of blockchain in automating processes through smart contracts. This review provides insights into the practical implications of blockchain-based DTs, highlighting their potential to enhance the reliability and scalability of Industry 4.0 operations. [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]

Background: In the pursuit of sustainable energy sources, residual biomass has emerged as a promising renewable resource. However, efficiently managing residual biomass poses significant challenges, particularly in optimizing supply chain operations. Advanced modeling approaches are necessary to address these complexities. This study aims to develop a comprehensive methodological framework for creating simulation models tailored to agroforestry residual biomass supply chains. Methods: The study employs a hybrid simulation approach, integrating geographic information system mapping with a case study analysis. The simulation was conducted over a 365-day period, using the anyLogistix software (version 2.15.3.202209061204) to model various supply chain dynamics. The framework also accounts for financial, operational, customer satisfaction, and environmental metrics. Results: The simulation results showed a total expenditure of EUR 5,219,411.3, with transportation being the primary cost driver, involving 5678 trips and a peak capacity of 67.16 m3. CO2 emissions were measured at 487.7 kg/m3. The model performed as expected, highlighting the need for sustainable logistics strategies to reduce costs, lower losses, and improve productivity. Conclusions: This study presents one of the first detailed methodological frameworks for simulating agroforestry residual biomass supply chains. It provides valuable managerial insights into the financial, operational, and environmental aspects of supply chain management. The findings may stakeholders make informed decisions to enhance the sustainability of biomass utilization in energy production. [ABSTRACT FROM AUTHOR]

At present, the financial situation of China's supply chain finance is still relatively unstable, and there are still some problems between supply chain enterprises and banks such as asymmetric information, insufficient model innovation and high operational risks. Based on this, this paper proposes and constructs a risk control model of financial big data analysis based on collaborative filtering algorithm. The purpose of this study is to realize the resource integration of supply chain enterprises and optimize the logistics chain, financial chain and information chain through the analysis of financial big data based on collaborative filtering algorithm, provide quality services for supply chain enterprises and good support for solving the financing problems of small and medium-sized enterprises. In order to verify the feasibility of the model, an experimental analysis is carried out. The experimental results show that this model has good scalability and operability, and the algorithm itself also has good scalability. The results of empirical analysis further verify that the design method in this paper has a good recommendation effect in terms of matching degree and user satisfaction. Compared with other risk control models, it is more practical and feasible. This research has certain practical significance for the financial management of supply chain enterprises. [ABSTRACT FROM AUTHOR]

Public sector infrastructure construction has been adversely impacted by recent shocks and stresses associated with global change, conflicts, and supply chain breakdowns. To address these challenges, this article presents novel methodologies to quantify past project delays and anticipate potential future disruptions from global shocks. These methodologies are then applied to over 2,000 projects executed by the US Army Corps of Engineers between 2011 and 2021. The results show that cost and time overruns in 2021 are double the baseline amount observed in the last 10 years. In some districts, a greater than 50% reduction in the number of contractors is also observed, despite an increased volume of work. Further, this article finds that many projects significantly rely on Russian-sourced minerals, suggesting that these challenges will likely accelerate as commodity scarcities from the Russia-Ukraine War unfold. This early-stage intelligence could significantly improve supply chain resilience in an increasingly unstable world. [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]

Sustainability has become part of agri-food supply chain management via short-, medium- and long-term strategies that balance different economic, social and environmental performance functions. However, within the supply chain, events known as risks are generated. These risks become obstacles to achieving sustainability. From a risk perspective, resilience must be developed within the supply chain to manage disruptions throughout the network and achieve the expected performance associated with different sustainability metrics. Although sustainability and resilience have been studied within the context of agrifood supply chains, each presents challenges when addressed independently. Consequently, several authors argue that it is essential to investigate the interaction between these two concepts. Thus, this research proposes a framework for managing the supply chain that integrates both resilience and sustainability into the food supply. The methodology used in the study is based on a literature search following the PRISMA protocol. This research reveals a significant overlap between the indicators used to measure both resilience and sustainability within agrifood supply chains, illustrating that these concepts can be assessed from multiple dimensions. Building on this premise, a framework is proposed that integrates both sustainability and resilience, aiming to support a comprehensive and multidimensional understanding of agrifood supply chain management. [ABSTRACT FROM AUTHOR]

A substantial amount of wastewater is generated during the extraction of oil and gas. Wastewater that is generated as a result of oil and gas extraction activities is known as produced water (PW), and managing PW is one of the greatest challenges faced by the oil and gas industry. Effective management of PW requires an understanding of the complex impact it may have on both oil production and water treatment operations. Here, a numerical model has been applied to a real-world case study, that of Kuwait Oil Company (KOC), to examine the relationships among various input and output factors in PW supply chain management. Specifically, the numerical model is a multi-objective optimisation model for the management of PW supply chains that takes into account economic as well as environmental objectives. A global sensitivity analysis has also been performed to assess the economic and operational factors that can influence the management of PW in KOC. The findings of this study show that the operational costs, treatment costs and environmental impacts can be assessed and used to guide the management of the PW supply chain in KOC. [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]

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]

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]

Recycled plastics value chains are being collaboratively constructed amid calls for greater responsibility of the corporates driving today's plastic waste crisis. The resulting 'responsibility fix' bolts new arrangements onto linear production processes, offering a mechanism to push linear processes towards circularity, while starting to patch up some of the social and economic injustices associated with waste-picking work within contemporary systems of capitalist production and consumption. This research draws upon semi-structured interviews to trace international collaborations within recycled plastics value chains to identify how new, low-disruption, circular business models are being built. [ABSTRACT FROM AUTHOR]

In the modern world, effective and successful supply chain management is among the most significant strategies for all organizations and public/private companies. Nowadays, recommending new tools and attitudes to improve supply chain efficiency is a challenging topic in organizational management. Another important goal of organizational management is to allocate costs logically and conveniently. Even though there are numerous studies on fixed costs and many tools for addressing this issue, data envelopment analysis (DEA) is a powerful technique for fair allocation. Therefore, the present study aimed to investigate the allocation of fixed costs in four-level supply chains using DEA models. The proposed model was examined by implementing a common set of weights and cost allocations according to the size of the decision-making unit. Additionally, the goal programming technique was applied to minimize the deviation between efficient allocation and size-based allocation. The proposed model is linear and provides a unique fixed allocation for each stage of the supply chain. Given that this model is always feasible, it can always provide an optimal allocation for each stage of the supply chain in different industries. In this paper, we focused on the allocation of personnel costs in a cement supply chain in Iran. The results show that the allocation amount to the customer stage (fourth stage) of the supply chain is much higher than other stages and the lowest allocation is obtained in the supplier stage (first stage). [ABSTRACT FROM AUTHOR]

It is encouraging to see blockchain technology take off as a practical means of improving supply chain management. Blockchain can help to lower fraud, boost efficiency, and improve the trust of those involved in the supply chain by offering a secure, decentralized, and transparent platform for tracking and verifying transactions. Additionally, blockchain can help with the creation of smart contracts, which can automate the completion of some transactions and improve the supply chain's overall efficiency. Despite ongoing challenges like scalability and interoperability, blockchain technology has the potential to transform supply chain management and build a more robust, sustainable, and reliable global economy. To increase transparency, accountability, and trust in the supply chain, this article suggests using a Proof of Reputation (PoR) consensus protocol in a blockchain-based supply chain management system. The protocol gives each participant a reputation score based on their previous actions and behavior, and uses this score to securely and decentralized validate transactions and add new blocks to the blockchain. The article offers a collection of Fair-Exchange Assessment Metrics for assessing node reputation as well as an assessment model for choosing the best consensus protocol based on particular needs and objectives. The proposed model, BCSC, outperforms the current model, BRBC, in terms of interference ratio, fair data exchange ratio, and process overhead, according to experimental results. The suggested method has the potential to boost the security, scalability, and effectiveness of supply chain blockchain systems. [ABSTRACT FROM AUTHOR]

Purpose: Good management strives to align and corporate processes for more attention being paid to supply chain management. Firms realize that greater co-operation and improved coordination can help to manage the entire supply chain more efficiently. The imperfect quality item is one of the most important issues that affect the expected profit of green supply chain. The imprecise cost with screening process of poor quality items posed in supply chain is the subject of this study. Design/methodology/approach: The present study explores production model for imperfect items having uncertain cost parameters with three-layer supply chain encompassing supplier, manufacturer and retailer. The model is considering the impact of business tactics such as order size, production rate, production cost and appropriate times in various sectors on collaborative marketing systems. Due to imprecise cost parameters, the pentagonal fuzzy numbers are set to fuzzify the total cost and defuzzifition by using graded mean integration. Findings: This study offers an explicit condition in uncertain environment to manage the imperfect quality item to increase the potential profit of the supply chain. The influence of changes in parameter values on the optimal inventory policy under fuzziness is provided managerial insights. Originality/value: This model makes a significant contribution to fuzzy inference. The results of the study provide a trading strategy for the industry to avoid losses. The prescribed study can be suitable for the industries like sculpture, jewelry, pottery, etc. [ABSTRACT FROM AUTHOR]

The synergy between the concepts of circular economy and Industry 4.0 enables a greater movement toward a sustainable society and addresses environmental and economic issues in organizational operations. This study seeks to implement circular economy and Industry 4.0 for waste reduction and resource optimization in Yazd glass factories. It is significant because Iranian factories are not efficient from this point of view and produce a considerable amount of waste. For this purpose, the mixed methodology has been employed. In the qualitative part, 15 enablers are identified by using the meta‐synthesis method, which are categorized into four economic, human resources, organizational‐managerial, and infrastructure dimensions. In the quantitative stage, the cause‐and‐effect relationship between enablers is identified by using the Fuzzy DEMATEL method, and forward and backward scenarios are formulated using fuzzy cognitive map technique. While the research practical contributions include identification of key enablers in implementing circular supply chain management 4.0, formulation of forward and backward scenarios to guide strategic decision‐making in sustainable practices, and offering actionable insights for waste reduction and resource optimization in the glass industry leading to improved operational efficiency, it has theoretical contributions such as highlighting the significance of specific enablers in the successful implementation of circular supply chain management 4.0, demonstrating the interplay between different enablers and their impact on key aspects, and advancing knowledge on sustainable practices within the context of the glass industry, contributing to environmental sustainability and operational excellence in Iranian factories. [ABSTRACT FROM AUTHOR]

Blockchain is a technology that combines a set of properties to guarantee network security, transparency, and visibility, including a decentralized structure, distributed notes and storage mechanism, consensus algorithm, intelligent contracts, and asymmetric encryption. Supply chain management activities, including supply chain management provenance, business process reengineering, and security enhancement, have enormous potential to be transformed by blockchain. This research uses the integrated interpretive structural modeling–cross‐impact matrix multiplication applied to classification (ISM‐MICMAC) technique to ascertain the hierarchical relationships and to comprehend the severity of interrelationships among various components in tackling our research questions. In MICMAC analysis, the enablers were classified into four categories based on their dependence and driving powers. The combined ISM‐MICMAC methodology employed for this study relies on experts' individual evaluations and subjective assessments. Therefore, even with extreme caution, it is impossible to guarantee that the results are entirely devoid of personal biases. To further validate the linkages discovered in this study, we suggest employing more multiple‐criteria decision‐making (MCDM) methodologies and comparing the results with those of our research. Another method for confirming the results of the current study is to use an empirical research design based on survey methods. [ABSTRACT FROM AUTHOR]

The maritime transport sector is confronted with a multitude of operational risks that demand the implementation of efficacious management strategies. It is often the case that traditional frameworks prove inadequate, particularly in the context of integrating innovative technologies such as blockchain. This research underscores the potential of blockchain technology to mitigate the aforementioned risks by addressing challenges such as inefficiencies in documentation, a lack of transparency, security vulnerabilities, and regulatory compliance issues. Blockchain offers a decentralized, immutable ledger that facilitates documentation, reduces errors, prevents fraud, and enhances transparency and traceability. This encourages more effective collaboration among stakeholders and enhances security measures, particularly in the context of cybersecurity. Furthermore, it facilitates regulatory compliance through transparent record-keeping and automated reporting via smart contracts. While blockchain technology has the potential to optimize supply chain management and enhance data analytics for proactive risk management, the successful implementation of such solutions requires the collaboration of industry stakeholders, regulatory support, and ongoing innovation. Further research should investigate the scalability of blockchain technology, its integration with other digital technologies, its long-term impact, and the establishment of standardized protocols. The complete potential of blockchain technology in the management of maritime operational risks has yet to be fully actualized. [ABSTRACT FROM AUTHOR]

This special issue of the International Journal of Production Research, focuses on the 'Carbon Neutrality' and 'SCM'. Nine articles have been selected for this special issue, and they cover various aspects to understand the manifestation of 'Carbon Neutrality' in supply chains, and to further illuminate how to achieve 'Carbon Neutrality' with supply chain innovation. This editorial provides a brief overview of the research domain, then introduces each article in the context of the state-of-the-art and highlights the contributions of selected papers to the field. Finally, the research perspectives are discussed. [ABSTRACT FROM AUTHOR]

Carbon neutrality and resilience are two of important goals pursued by supply chains today. This study seeks to determine how carbon footprint reduction (CFR) can be achieved in a resilient supply chain from a process integration perspective. Based on contingency theory, we employed the decision-making trial and evaluation laboratory (DEMATEL) approach to examine the critical influencing factors of process integration using evaluations from academic and professional experts. Our findings reveal that, first, at the strategic level, supply chain collaboration (SCC) and supply chain agility and responsiveness (SCAR) have the highest contributions to process integration. Second, process and control risks have the highest contributions in supply chain risk management; herein, collaborative planning, forecasting, and replenishment (CPFR) holds the highest contribution in the SCC, visibility and velocity have the highest contributions in the SCAR, and supply chain efficiency holds the highest contribution in supply chain flexibility (SCF). Finally, CPFR has a significant influence on both supplier and customer engagement, with supply chain intelligence influencing customer engagement in the SCC. Both the standardisation and parallel processes influence supplier spending in the SCF. These findings provide a new conceptual framework for empirical research and an action plan for supply chains to pursue carbon neutrality. [ABSTRACT FROM AUTHOR]

We draw on complementarity and performance landscape perspectives to reason why and how supply chains should shift from a rugged to a smooth performance landscape. We analysed the organisation of supply chain-oriented firms by conceptualising them as a set of interdependent elements whose complementarity interaction generates desirable performance outcomes. We collected perceptual data from 139 firms. After establishing the psychometric properties of the measures, we employed two econometric methods that enabled us to examine the complementary interaction using performance differences among five SCM practices. Overall, we find empirical evidence for complementarity among the SCM practices. We also find interesting results from the two econometric approaches allowing us to articulate the distinction between practice contextuality and interaction contextuality. Our study offers empirical evidence for supply chain managers to find a promising position in the rugged supply chain performance landscape. In addition, we offer noteworthy managerial insights on managing the supply chain towards a smoother supply chain performance landscape. [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]

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]

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]

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Space exploration, with its enormous distances and extreme environments, is a challenge to technology, human habitation, sustainability, and supply chains. On the flip-side, however, it can provide a new vantage point on how to improve human life and planetary prosperity. This objective requires the development of economic and sustainable supply chains and a governance framework to guarantee fundamental human needs and well-being under the limitations of distant and inhospitable environments. This review describes learnings for human habitation in space from remote communities on Earth that have developed and survived over generations. These include a long history of human survival strategies on Tristan da Cunha, Pitcairn Islands, Nauru, and Easter Island. Their supply chain management solutions and their problems can guide the implementation of logistics systems for the efficient use of resources in space, to satisfy vital needs of human survival but also to ensure social and governance in space, e.g., build-up of thriving communities, mobility, and industrial activities. This review demonstrates that there are significant gaps in recent space supply chain studies with respect to the space environment, social and governance. Analysis of established practices and concepts from remote regions on Earth can readily respond to these deficiencies and thus supplement space exploration. This review recommends extending the assessment of supply-chain assets from the near future to long-term strategic. This implies going far beyond current space supply chain reports to include aspects of social responsibility and governance, such as sustainable health systems, product quality management, and local decision-making. [ABSTRACT FROM AUTHOR]