Supply Chain Management Research Articles

Exploring the Power of Artificial Intelligence in Supply Chain Management: A Literature Review on the Artificial Intelligence Applications and Tools Used in Supply Chains and Their Distribution According to the SCOR Method

Since the beginning of the 21st century, supply chains have witnessed rapid and significant changes along with considerable developments due to the convergence between technology and globalization. The present study aims primarily to provide insight into the artificial intelligence (AI) tools used in Supply Chain Management Processes using the Supply Chain Operations Reference (SCOR) approach. It also seeks to examine the way AI tools can be applied to the outputs of each process and each application. The study follows a four-step systematic review approach that mainly involves literature collection between the years 2000 and 2022, descriptive analysis, category selection, and material evaluation. The main purpose of this work is to improve the capacity of making the most appropriate decisions through the use of the most suitable AI tools for each function and each process within supply chains in order to ensure the best management of these chains.

Construction of Cross-Border E-Commerce Supply Chain of Agricultural Food Products based on Blockchain Technology

The European Union has for several years been a critical export market and a significant source of imports for us, and the US has, in general, kept closed domestic players vis-à-vis the EU. However, given the variety of alternative market conditions and EU forms, the attractiveness of cross-border electronic commerce (CBEC) between China and the EU has fallen far short, and there is an urgency to create a harmonious and uniform environmental environment for the exchange of information to facilitate the convenience of cross border electronic commerce. This study examines the CBEC of agricultural goods and its cooperative management technique inside the logistical supply chain. It details the complete transaction model and fundamental components and presents a theoretical framework for the CBEC distribution network. The Block Chain can effectively bridge the obstacles to CBEC in Chinese and European countries by providing a valuable source of benefits from decentralization, trust, anti-counterfeiting, consensus, innovative procurement, and extraordinary techniques, which will provide the basis for building an Embedded Provider Platform for Electronic Commerce, Risk Management System for Deposit Risk Management, Supply Chain (SC) Management System, Cross Border Logistic System, Customs Supervisory Computer, etc. The paper examines how blockchain science can assemble CBEC SC computing devices for agricultural goods between global places in Central Europe. Firstly, it expounds on the theory and characteristics of the blockchain. Then, the paper introduces the troubles that arise in the CBEC supply chain. Then, the thesis proposes a blockchain-based CBEC SC structure, analyzes the aspects and relations among each other, and provides a framework for developing a China-European blockchain cross-border electronic Commerce. The test findings indicate that the system satisfies the criteria for tracking agricultural items and enhances fresh farm commodities' quality and security.

A novel algorithmic approach to model uncertainties associated with sustainable supply chain management using complex spherical fuzzy soft settings

A novel algorithmic approach to model uncertainties associated with sustainable supply chain management using complex spherical fuzzy soft settings

Role of supplier engagement to reduce Scope 3 emissions in circular supply chains

AbstractPurchasing firms/buyers committed to driving environmental change in their supply chains must address emissions from all three scopes, particularly Scope 3 emissions. Hence, supplier engagement has emerged as a critical strategy for achieving net‐zero emissions. However, studies about how purchasing firms engage with suppliers and how such engagement mitigates Scope 3 emissions are relatively scant. This study fills this important gap in supply chain management literature. The study employs a multiple‐case study approach. Overall, 42 semi‐structured interviews with senior managers from four purchasing and four supplying firms are undertaken. The results unveil six of the best strategies that purchasing firms have deployed to effectively engage suppliers and bring them on track to reduce Scope 3 emissions. These include effective communication, building trust, providing support and guidance, using suppliers' data effectively, refining engagement programs through consistent feedback, and developing supplier incentive programs. The study offers both theoretical insights and practical implications. For instance, it suggests that effective engagement with suppliers will help suppliers mitigate Scope 3 emissions, and buyers can also overcome conflicting targets to reduce Scope 3 emission targets in procurement. The paper concludes with a discussion of limitations and suggestions for future research.

The Role of Green Risk Management Approaches in Promoting Green and Sustainable Supply Chain Management

This study assesses how advanced technologies like AI, blockchain, and big data facilitate green risk management in the automotive and electronics industries in the EU. When applied to environmental risk assessment, green purchasing, and eco-design activities, these technologies will optimize Economies of Scale (EoS) and contribute to advancing GSSCM in companies. This review uses systematic literature review and thematic analysis and focuses on using various peer-reviewed sources to understand how these technologies support GSSCM and also reveal gaps and challenges such as the integration of innovative waste disposal technologies and sustainable partnership schemes. Research proves that actual assessment of environmental risk is possible through the implementation of AI in risk assessment; On the other hand, blockchain makes sustainable procurement and reverse logistics more transparent. Thus, some problems like high costs, limited time, and problems with the alignment of stakeholder goals remain. It is recommended that these gaps be overcome by innovating, partnering with industries, and implementing policies that can further improve the position of information systems as the foundation of GSSCM. Thus, policymakers have been urged to explore options like grants or subsidies in an attempt to promote the adoption of these technologies as a way of creating a circular economy. Consequently, this research offers insights that may be beneficial for industry managers and policymakers seeking to improve sustainability within the EU automotive and electronics sectors.

Discrete-event simulation in logistics and supply chain management: a scientometric perspective

ABSTRACT This paper has been designed in the form of a systematic literature review intended for evaluating the state-of-the-art of discrete-event simulation (DES) usage in the logistics and supply chain management fields under a scientometric perspective. With this primary aim in mind, 127 papers published between 2009 and 2022 are analysed, with the specific purposes of: 1) providing an overview of DES studies in logistics and supply chain management, map the main topics covered within this stream of literature and their evolution in time; 2) providing a robust ranking of the journals and authors in the field; 3) evaluating the rigor in the implementation of DES models in the logistics and supply chain management literature; and finally 4) correlating, through statistical elaborations, all the previous aspects to the success of these papers, measured as the citations received per year, taking inspiration from scientometric disciplines.

BLOCKCHAIN TECHNOLOGY: A NEW ERA OF TRANSACTION PROCESSING - (DECENTRALIZED, SECURE LEDGER TRANSFORMING GLOBAL TRANSACTION PROCESSES)

Blockchain technology has emerged as a disruptive force in the realm of transaction processing, heralding a new era marked by decentralization, security, and transparency. By leveraging distributed ledgers, blockchain eliminates the need for intermediaries, enabling peer-to-peer transactions that are secure and immutable. This shift towards decentralized networks not only ensures trust in transactions but also streamlines processes across industries, offering a paradigm shift in how transactions are conducted and verified. Furthermore, the implementation of smart contracts within blockchain technology adds a layer of automation and enforceability to agreements, revolutionizing the way contracts are executed. These self-executing contracts facilitate efficient and reliable transactions, minimizing the potential for fraud and human error. As a result, blockchain technology is not only transforming traditional financial systems but also finding applications in supply chain management, healthcare, and various sectors where secure and transparent transactions are paramount. KEYWORDS Blockchain technology, Decentralization, Distributed ledger, Smart contracts, Transaction security, Transparency, Peer-to-peer transactions, Immutable ledger, Cryptographic principles, Supply chain management, Scalability challenges, Regulatory uncertainty, Interoperability, Energy consumption, Tokenization, Digital trust, Automation

Supply chain management and the performance of small and medium scale enterprises in Nigeria

This paper examined the relationship between supply chain management practices (SCM) and performance of small and medium enterprises (SMEs) in Nigeria. It aimed to explain how SCM practices like strategic suppliers’ alliances, information sharing, and collaborative governance impacts the performance of SMEs in Nigeria. SME success was measured using a continuum of operational efficiency, customer satisfaction, and profitability. To reach the study's goal, a survey research approach was used, with a sample of 352 respondents representing the owners and senior management members of registered SMEs in Nigeria. Because the study depended on quantitative analysis, respondents' opinions were collected using a standardised closed-ended questionnaire. The gathered data was analysed using IBM SPSS 28 and IBM AMOS. The study found a positive and substantial correlation between chosen SCM practices and the performance of SMEs in Nigeria, as shown by the coefficients and p-values (SSA = 0.544; P <.001; IFS = 0.621; P <.001; CGV = 0.673; P <.001). It is therefore argued that SCM techniques such as strategic partnerships with suppliers, information sharing, and collaborative governance have a favourable and significant influence on the performance of SMEs in Nigeria. Consistent with the findings and current literature, this study recommends that Nigerian SMEs form strategic supplier relationships by sharing continuous improvement programs with important suppliers and include key suppliers in their planning and goal-setting processes. Keywords: Supply Chain Management, Strategic Supplier Alliance, Information Sharing, Collaborative Governance, Performance.

Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers

The application of Supply Chain Management (SCM) principles has gained considerable attention across various industries to enhance operational efficiency and business performance. In the construction sector, SCM can guide managers in strategic planning and foster collaboration with suppliers, leading to more effective project execution. Despite its importance, limited research has focused on designing sustainable supply chains for construction materials under uncertain conditions. This study aims to bridge this gap by introducing a robust optimization framework that incorporates sustainable development criteria, specifically the minimization of harmful environmental effects and the reduction of worker unemployment. Additionally, the research introduces an innovative concept of horizontal transfers between downstream members, which not only reduces supply deficiencies but also indirectly increases profitability for these members. This article is a part of a Doctoral dissertation. It follows a two-step approach. First, suppliers of construction materials are ranked based on sustainable development criteria using a multi-criteria decision-making method. The best-ranked supplier is then integrated into a mathematical model for optimizing the supply chain design. Given the NP-hard nature of the problem, the CPLEX 12.1 solver with the epsilon constraint method is used to solve small-scale models. For larger-scale problems, three meta-heuristic algorithms are developed: multi-objective ant-lion, multi-objective gray wolf, and multi-objective dragonfly. The results show that while both the ant-lion and gray wolf algorithms deliver comparable average performance, the gray wolf algorithm excels in terms of solution time, making it more effective for real-time problem-solving. This makes the gray wolf algorithm the most efficient choice for addressing large-scale, multi-objective supply chain challenges. This research introduces a novel framework for designing sustainable construction supply chains under uncertain conditions. By focusing on criteria such as minimizing harmful environmental effects and reducing worker unemployment, this study addresses key aspects of sustainable development. Additionally, the innovative horizontal transfer mechanism and the insights into algorithmic performance provide valuable contributions to the field, especially for real-world applications in the construction industry.

Blockchain Consensus Mechanisms: A Bibliometric Analysis (2014–2024) Using VOSviewer and R Bibliometrix

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.

The role of big data analytics in the footwear supply chains: a multiple case study perspective

Purpose This paper aims to analyze the importance of big data analytics (BDA) and supply chain analytics for sustainable supply chain management in all types of enterprises in the footwear industry. The importance and implementation of BDA in supply chain management have been discussed in this research paper, and a conceptual framework is proposed for the implementation. Design/methodology/approach The previous research indicates that the application of BDA and supply chain analytics is the key point to establishing sustainable supply chain management. Even though there are several types of research on the implications of BDA, there is still a gap in practical implications in organizations. For a better understanding, comparison of frameworks has been done for literature support. Further, 11 in-depth, semi-structured interviews have been conducted with four organizations from the footwear industry, and a conceptual framework has been proposed. Findings This research demonstrates an important gap in the literature through a thorough investigation of how firms can improve operational efficiency and productivity through the framework application and whether it is feasible to apply this within the global footwear industry or not. In conclusion, the research has denoted that despite lack of understanding related to sustainability agendas and not having proper ERP or BDA systems, the organizations operating in Pakistan still met some standards of sustainability and are moving toward achieving more. Research limitations/implications The research has pointed out the importance of the integration of all stakeholders in the supply chain through a proposed framework that aligns and guides the stakeholders so that the policies and other constraints may be taken into consideration while revising sustainable supply chain strategies. Practical implications This study will help increase sustainability through the application of BDA technology, which will benefit various stakeholders, particularly those in the footwear industry. Originality/value This study has proposed a framework based on three stages of the implementation of BDA in the existing supply chain to maintain and achieve sustainability in the organization in the footwear industry. This three-stage framework covers many aspects that were not covered in the literature before.

The Value of Applying Big Data Analytics in Health Supply Chain Management

The use of big data analytics (BDAs) allows for the collection, management, and analysis of large volumes of data, which helps in making real-time decisions. This study aims to assess how the application of BDA impacts the performance of healthcare supply chain management (HCSCMP). Through a systematic literature review, the research explores how BDA enhances efficiency within healthcare supply chains (HCSCs) and identifies the critical factors enabling successful BDA implementation. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs' efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

Optimizing Supply Chain Transparency and Customer Compatibility with AI-Driven Models

As global supply chains become increasingly complex, the adoption of artificial intelligence (AI) technologies has emerged as a critical strategy for enhancing operational transparency and improving customer compatibility. This study investigates the application of AI-driven models in optimizing supply chain performance, focusing on predictive analytics, real-time data integration, and customer-centric personalization. A comprehensive experimental framework was employed, evaluating five distinct AI configurations against four key performance criteria: operational transparency, customer compatibility, cost efficiency, and delivery performance. Results demonstrated that the Real-Time Data Integration Model achieved a 20% improvement in operational transparency, allowing for enhanced visibility into inventory management and more agile responses to dynamic demand fluctuations. Additionally, the Customer-Centric Personalization Model increased customer satisfaction by 10%, emphasizing the critical role of tailored service delivery in modern supply chain management. The Cost Optimization Model yielded significant cost reductions, improving cost efficiency by 18%, though it showed a marginal decrease in customer compatibility. The findings highlight the trade-offs between cost efficiency and customer-centric strategies, suggesting that a balance is required to achieve a well-rounded and sustainable supply chain model. This research underscores the transformative potential of AI in driving efficiency, transparency, and customer satisfaction. Future work should explore the integration of advanced technologies such as 5G and further investigate scalable AI solutions capable of addressing the evolving challenges faced by global supply chains.

Spatial Analysis of Middle-Mile Transport for Advanced Air Mobility: A Case Study of Rural North Dakota

Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using the mostly rural and small urban U.S. state of North Dakota as a case study. The analysis utilized geographic information system (GIS) and spatial optimization models to strategically assign underutilized airports as multimodal freight hubs to facilitate the shift from long-haul trucks to middle-mile air transport. Key findings demonstrate that electronics, because of their high value-to-weight ratio, are ideally suited for air transport. Comparative analysis shows that transport by drones can reduce the average cost per ton by up to 60% compared to traditional trucking. Optimization results indicate that a small number of strategically placed logistical hubs can reduce average travel distances by more than 13% for last-mile deliveries. Cost analyses demonstrate the viability of drones for middle-mile transport, especially on lower-volume rural routes, highlighting their efficiency and flexibility. The study emphasizes the importance of utilizing existing infrastructure to optimize the logistics network. By replacing truck traffic with drones, AAM can mitigate road congestion, reduce emissions, and extend infrastructure lifespan. These insights have critical implications for supply chain managers, shippers, urban planners, and policymakers, providing a decision support system and a roadmap for integrating AAM into logistics strategies.

A mathematical model for potash supply chain management with a strategic logistics perspective

Abstract Accepted by: M. Zied Babai This paper introduces a novel Integer Linear Programming model designed to enhance the efficiency and sustainability of the potash supply chain, a crucial element supporting global agriculture. The developed mathematical optimization model focuses on fleet selection (private/outsource) and incorporates the concept of ‘inter-warehouse collaboration’, which addresses key logistics considerations. Integrating mining, processing, storage and transportation, the model encompasses decision variables like extracted carnallite amount, production, storage levels and shipped potash amount. Illustrated through a case study on the Arab Potash Company in Jordan, the results showcase the model’s proficiency in meeting local and international market demands. The model ensures resilient and sustainable supply chain performance by emphasizing logistics optimization, particularly in fleet selection. The study attains the highest ‘warehouse-to-warehouse’ support for Standard and Granular potash types in the international demand scenario, contributing to efficient production planning and fleet management. In conclusion, the presented mathematical model is a valuable tool for potash industry stakeholders, offering insights for strategic decision-makers involved in production planning and fleet management.

Adaptive Strategies and Sustainable Innovations of Chinese Contractors in the Belt and Road Initiative: A Social Network and Supply Chain Integration Perspective

As global economic integration and rapid technological advancements transform international business, international engineering contracting has become essential for achieving sustainable development goals (SDGs). This paper investigates the significant impact of China’s strategic initiatives, notably the “Going Global” strategy and the Belt and Road Initiative (BRI), on the operational practices of Chinese enterprises involved in overseas investments. Central to this transformation is the Engineering, Procurement, and Construction (EPC) model, which emphasizes the integration of supply chain management and stakeholder collaboration to enhance performance in international EPC projects and underscores the crucial role of these elements in promoting sustainability. Incorporating insights from social network data analysis, this study reveals that contractors collaborating with various stakeholders—such as owners/consulting engineers, domestic and foreign customs departments, and group headquarters/design parties—exhibit a high degree of similarity in personnel profiles. This suggests that the internal organizational structure and personnel allocation of contractors could be optimized to enhance operational efficiency, aligning with the collaborative patterns identified. This study addresses a critical research gap by exploring how effective supply chain management and collaborative stakeholder engagement within multinational EPC projects contribute to sustainable outcomes. Employing advanced social network analysis software, the research examines the complex interactions among stakeholders and their influence on procurement dynamics. Findings indicate that strong relational networks and strategic collaborations significantly enhance procurement efficiency and project success, underscoring the importance of supply chain integration. Ultimately, integrating supply chain management principles into the EPC model not only offers innovative perspectives for advancing sustainability in international projects but also provides actionable insights for improving project outcomes within the BRI framework. This research underscores the pivotal role of supply chain organization and stakeholder cooperation in achieving sustainability objectives, thereby enriching the discourse on sustainable enterprise operation and supply chain management in the context of global initiatives.

Comparison of deep and conventional machine learning models for prediction of one supply chain management distribution cost

Strategic supply chain management (SCM) is essential for organizations striving to optimize performance and attain their goals. Prediction of supply chain management distribution cost (SCMDC) is one branch of SCM and it’s essential for organizations striving to optimize performance and attain their goals. For this purpose, four machine learning algorithms, including random forest (RF), support vector machine (SVM), multilayer perceptron (MLP) and decision tree (DT), along with deep learning using convolutional neural network (CNN), was used to predict and analyze SCMDC. A comprehensive dataset consisting of 180,519 open-source data points was used for analyze and make the structure of each algorithm. Evaluation based on Root Mean Square Error (RMSE) and Correlation coefficient (R2) show the CNN model has high accuracy in SCMDC prediction than other models. The CNN algorithm demonstrated exceptional accuracy on the test dataset, with an RMSE of RMSE of 0.528 and an R2 value of 0.953. Notable advantages of CNNs include automatic learning of hierarchical features, proficiency in capturing spatial and temporal patterns, computational efficiency, robustness to data variations, minimal preprocessing requirements, end-to-end training capability, scalability, and widespread adoption supported by extensive research. These attributes position the CNN algorithm as the preferred choice for precise and reliable SCMDC predictions, especially in scenarios requiring rapid responses and limited computational resources.

Stakeholders’ perspectives and performance outcomes of sustainable market-focused manufacturing system in Indian manufacturing organizations

Sustainability and the ever-changing customer demands are the key drivers for innovation across product, process, system, and supply chain management. Sustainability innovations aim to improve organizational environmental, social, and economic performance. Given the complexity of sustainability and ever-changing business and stakeholders’ requirements, organizations must focus their innovation in the direction of meeting the requirements of their stakeholders and business. Integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) is a sustainable market-focused manufacturing system. It provides a sustainability and market-oriented business model and meets the perspectives of the various stakeholders. This study aims to identify and rank the various performance outcomes of ISGLSAMS. The study also explores the correlations among the various performance outcomes of ISGLSAMS. The study helps the practitioners to better understand the ISGLSAMS and stakeholders’ perspectives of ISGLSAMS. This research provides a foundation for practitioners, policymakers, organizations, and value chain partners (i) to formulate policies and roadmaps for the successful adoption of ISGLSAMS and (ii) for fostering a more sustainable development of manufacturing organizations in India.

Application Analysis of Supply Chain Finance in Construction Industry -Take A Platform as an Example

With the development of globalization, competition between enterprises has increased, and supply chain management has become an important means for enterprises to gain competitive advantages. At present, the research on supply chain finance mainly focuses on risk management and effect analysis, and the research objects are concentrated on commercial banks and agricultural development, while the application of the construction industry is relatively small. This article uses case analysis and SWOT-PEST analysis method. Take A supply chain platform as an example to analyze the impact of the internal and external environment on the construction industry supply chain platform. Studies have found that many factors such as policy support, technological updates, economic fluctuations, and competition affect the development of the A platform. The development of the construction industry supply chain platform needs to grasp the direction of government strategy, fully understand user needs, seek technological innovation and establish a risk prevention mechanism.

Digital Supply Chain and Business Performance: The Case of the Oil and Gas Industry

A competitive global business competition requires a firm to formulate a competitive strategy in supply chain management. The transformation from manual to digital management is also necessary for the oil and gas industry. A digital supply chain is a management approach that uses technology to manage the flow of goods, information, and finance across the entire supply chain. This study attempts to evaluate the impact of the digital supply chain on business performance in the oil and gas industry. The study sample was 523 PETRONAS staff members who were involved in operating two main units, namely, a gas processing and oil refinery. The results of multiple regression analysis found that the digital supply chain significantly and positively influences firm performance across the three study samples, namely gas processing, oil refinery, and the overall sample. Technology-driven supply chain management has had a significant positive impact on every aspect of the supply chain. This can be observed in enhanced efficiency, improved visibility, time savings, and increased company competitiveness. Nonetheless, the influence of the digital supply chain is not absolute because other factors such as communication, competence, transparency, and training empirically affect the firm's performance. All of these factors are complementary to the effectiveness of digital supply chain implementation. In line with this, steps are being taken to optimize digital applications across all aspects of the supply chain, along with certain elements related to human capital, to create a unique resource capable of fostering competitive advantage and enhancing firm performance.