Supply Chain Nodes Research Articles

Integrating Blockchain and Homomorphic Encryption to Enhance Security and Privacy in Project Management and Combat Counterfeit Goods in Global Supply Chain Operations

The proliferation of counterfeit goods and data privacy concerns in global supply chain operations poses a significant risk to organizations and end-users alike. This paper explores the integration of blockchain technology and homomorphic encryption as dual mechanisms to enhance security and privacy in project management and supply chain operations. Blockchain offers an immutable, decentralized ledger that provides traceability and authenticity across supply chain nodes, while homomorphic encryption enables secure data processing and analysis without compromising sensitive information. The synergy of these technologies presents a robust framework to address counterfeit risks, facilitating end-to-end product authentication and allowing for secure, real-time collaboration in project management settings. This integration minimizes vulnerabilities in data handling and improves compliance with privacy regulations by securing data at rest and in transit. By evaluating case studies and recent advancements, this paper highlights the potential of blockchain and homomorphic encryption to redefine security protocols, fostering a trustworthy and resilient supply chain ecosystem. Future research directions are recommended to expand the practical applications and address scalability challenges associated with these emerging technologies.

A Novel Framework to Evaluate the Effect of Strategic Systems Thinking on Sustainable Supply Chain Risks, LARG Capabilities and Performance

Supply chain (SC) disruptions created due to sustainable, social, economic, environmental and technical risks are mitigated by lean, agile, resilient and green (LARG) capabilities across the SC node. This study aims at the assessment and alignment of SC risks and capabilities for a strategic fit of appropriate practices resulting in performance, efficiency and continuity of operations. The novelty of this research work is the investigation of the direct and mediating effects of strategic system thinking (SST) between SC risks, capabilities and performance. A survey comprising of 78 items was administered to 255 managers of Pakistan automotive SC industries. The exploratory factor analysis and confirmatory factor analysis were executed to identify the valid constructs along with their reliability and validity. The structural equation modeling (SEM) was used to test the conceptual model by establishing the second order constructs. SEM results indicated only technical risks having negative significant effect with performance. In terms of capabilities, the general, efficiency, integration as well as the redundant resources were found to have significant association with SC performance. The SST approach was found to be significantly associated with technical risks and capabilities such as general, recovery and redundancy. The hypothesis of SST as a mediating variable across all factors was not observed to be valid in this research. This study can help in the policy and decision-making as well as strategic assessment, planning, development, positioning and alignment of resources across the sustainable SC. The operations can be influenced positively through system integration and conservation of resources for a sustainable performance. The green, environmental and social risks had higher SC impact and need to be focused upon in Pakistan automotive SC for higher performance and sustainability.

Cybersecurity investments in supply chains with two-stage risk propagation

Cyber-attacks present a significant threat to supply chains as their nodes are directly or indirectly vulnerable to risk propagation at various stages. The risk level varies depending on the type of attack. A cybersecurity insurance offers a practical method to mitigate this risk, and it is crucial to determine optimal cybersecurity investments for all supply chain nodes. Previous studies have overlooked the joint impact of the attack type, two-stage risk propagation, and cybersecurity insurance in optimizing cybersecurity investments. This paper addresses this research gap by examining optimal investments under targeted and opportunistic attacks in a two-stage supply chain using game theory. The findings indicate that optimal investments differ based on the type of attack. For instance, retailers should invest more in cybersecurity under opportunistic attacks, while suppliers need to spend more under targeted attacks. Additionally, the results show that under opportunistic attacks, members should reduce their investments. Conversely, under targeted attacks, investments should initially increase and then stabilize. In the case of opportunistic attacks, suppliers and retailers should prioritize reconfiguring their systems over investing heavily in cybersecurity. The model presented in this paper demonstrates that not all cyber risks are worth defending against and that cybersecurity insurance for the entire supply chain can be more cost-effective than addressing cybersecurity risks individually. The paper also explores the impact of joint decisions on cybersecurity insurance when firms are unwilling to invest individually. The insights obtained enable supply chains to identify their optimal cybersecurity investment strategies effectively.

Development of a blockchain-based embodied carbon estimator

PurposeCarbon management in the construction industry plays a vital role as carbon emissions have a significant impact on the environment. Current emphasis on reducing operational carbon through passive designs, zero carbon buildings and so forth has resulted in losing focus on embodied carbon (EC) reduction. Though there are various databases and tools to estimate EC in construction, these estimates are lacking in accuracy and consistency. A Blockchain-based Embodied Carbon (BEC) Estimator was developed as a solution to accurately estimate EC using a supply chain value addition concept as a methodology.Design/methodology/approachThis study focused on developing, testing and validating the blockchain-based prototype system identified as BEC Estimator. The system was developed using Hyperledger Fabric following a waterfall model. Case studies and an expert forum were used to test and validate BEC Estimator.FindingsThe system architecture, development process and the user interface of BEC Estimator are presented in this paper. The comparative evaluation with existing EC databases/tools and the expert forum validated the functioning of BEC Estimator and proved it to be an accurate, secure and trustworthy EC estimating system. SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis identified the strengths and opportunities that will benefit the industry as well as the weaknesses and threats in the system that could be mitigated in future.Originality/valueBEC Estimator accurately accounts for EC additions happening at each supply chain node for any product that gets incorporated in a building, thereby facilitating EC-related decision-making for all relevant stakeholders.

Optimization and Benefit Assessment of Production Supply Chain Networks Using Graph Neural Network Models

With the flourishing development of global economy, effective management of production supply chains is crucial for the competitiveness of enterprises. Optimizing supply chain networks can not only improve the efficiency of resource allocation but also enhance market responsiveness and systemic risk resistance. Traditional supply chain network optimization methods, focusing mostly on linear models and static analysis, fall short in addressing the growing complexity and dynamism. The emergence of Graph Neural Network (GNN) models in recent years has offered new opportunities to tackle non-linearity and structural dynamism in supply chain networks. However, existing research still faces methodological limitations in supply chain node relationship mining and benefit assessment. This study introduces an optimization and benefit assessment method for production supply chain networks based on GNNs. Firstly, by developing a node role type-aware graph neural network model, this paper achieves in-depth mining and optimization of node relationships within production supply chain networks. Secondly, a hierarchical factor analysis method is used to comprehensively assess the benefits of the production supply chain. This method can dynamically capture changes in node roles and relationships within the supply chain network, optimize the network structure, and provides a multidimensional, multilevel framework for benefit assessment. This study not only expands the application of GNN in the field of supply chain management but also provides a new analytical tool for the comprehensive assessment of supply chain benefits.

Risk Transmission in Low-Carbon Supply Chains Considering Corporate Risk Aversion

In order to study the impact of risk aversion characteristics of enterprises on supply chain risk transmission, the risk aversion utility function is introduced, and the risk elasticity coefficient is used to construct a supplier-dominated low-carbon supply chain risk transmission model. Simulation analysis is conducted to investigate the transmission of emission reduction and revenue risks caused by internal and external contingent risk factors. The study reveals that under conditions of market demand uncertainty, the risk transmission effect is unaffected by the risk aversion characteristics of members in the low-carbon supply chain. While the risk-aversion characteristics of suppliers can decrease their own profit risk, they have a negative effect on the profit risk of manufacturers and the emission reduction risk of supply chain nodes. There exists a critical threshold for the impact of the risk-aversion degree of suppliers on their own emission reduction risk transmission effect. When this threshold is exceeded, the emission reduction risk decreases with increasing risk aversion intensity of suppliers, and vice versa. The risk aversion characteristics of manufacturers can weaken the negative effect of supplier risk aversion on the fluctuation risk of manufacturer profits, but they exacerbate the emission reduction risk transmission effect of manufacturers under asymmetric information influence. The findings have important theoretical and practical implications for supply chain risk management.

Performance evaluation of low-carbon development at key nodes in the maritime supply chain

ABSTRACT How to effectively monitor and evaluate the low-carbon level of the key nodes in the maritime supply chain is a important challenge for the sustainable development of ocean. This article adopted the ‘bottom-up’ and ‘top-down’ estimation methods comprehensively to measure the carbon emissions of ‘ship-port’ system. A new cross-efficiency network DEA (Data envelopment analysis) model has been established to evaluate the low-carbon efficiency of the ‘ship-port’ system. Finally, this article takes 17 listed ports along the coast of China as examples for case analysis. The main contributions are as follows: First, this paper adds a methodology for monitoring carbon emissions from ships using Automatic Identification System (AIS) data. Second, compared with the European monitoring, reporting, and verification (MRV) system, the estimation and assessment of carbon emissions from ships has been expanded to the ‘ship-port’ system. Third, the newly constructed model can better evaluate the low-carbon performance of the system.

Food fraud threats in UK post-harvest seafood supply chains; an assessment of current vulnerabilities.

Seafood fraud is commonly reported on food fraud databases and deceptive practices are highlighted by numerous studies, with impacts on the economy, health and marine conservation. Food fraud assessments are a widely accepted fraud mitigation and prevention activity undertaken to identify possible points of deception within a supply chain. This study aims to understand the food fraud vulnerability of post-harvest seafood supply chains in the UK and determine if there are differences according to commodity, supply chain node, business size and certification status. The SSAFE food fraud vulnerability assessment tool was used to assess 48 fraud factors relating to opportunities, motivations and controls. The analysis found seafood supply chains to have a medium vulnerability to food fraud, with the highest perceived vulnerability in technical opportunities. Certification status was a stronger determinant of vulnerability than any other factor, particularly in the level of controls, a factor that also indicated a higher perceived level of vulnerability in smaller companies and the food service industry. This paper also reviews historic food fraud trends in the sector to provide additional insights and the analysis indicates that certain areas of the supply chain, including uncertified prawn supply chains, salmon supply chains and food service companies, may be at higher risk of food fraud. This study conducts an in-depth examination of food fraud vulnerability relating to the UK and for seafood supply chains and contributes to a growing body of literature identifying areas of vulnerability and resilience to food related criminality within the global food system.

Multi-option analytical modeling of levelized costs across various hydrogen supply chain nodes

Hydrogen is envisioned to become a fundamental energy vector for the decarbonization of energy systems. Two key factors that will define the success of hydrogen are its sustainability and competitiveness with alternative solutions. One of the many challenges for the proliferation of hydrogen is the creation of a sustainable supply chain. In this study, a methodology aimed at assessing the economic feasibility of holistic hydrogen supply chains is developed. Based on the designed methodology, a tool which calculates the levelized cost of hydrogen for the different stages of its supply chain: production, transmission & distribution, storage and conversion is proposed. Each stage is evaluated individually, combining relevant technical and economic notions such as learning curves and scaling factors. Subsequently, the findings from each stage are combined to assess the entire supply chain as a whole. The tool is then applied to evaluate case studies of various supply chains, including large-scale remote and small-scale distributed green hydrogen supply chains, as well as conventional steam methane reforming coupled with carbon capture and storage technologies. The results show that both green hydrogen supply chains and conventional methods can achieve a competitive LCOH of around €4/kg in 2030. However, the key contribution of this study is the development of the tool, which provides a foundation for a comprehensive evaluation of hydrogen supply chains that can be continuously improved through the inputs of additional users and further research on one or more of the interconnected stages.

Effect of Warehousing Management on Supply Chain Performance: A Case of Inyange Industries Ltd

In local and globalized markets, warehouses are crucial supply chain nodes. This study aimed to investigate the effect of warehousing on supply chain performance: A case of Inyange Industries Ltd. The goals were to evaluate how inventory management, warehouse capacity building, and material handling affects supply chain performance in Inyange Industries Ltd. This research experimented with three different theories: Just-in-time, Lean, and Triple-A supply chain. The population of this study were 105 staff members of Inyange Industries Ltd. Therefore, census was conducted because the population size is affordable and the researcher can be able to contact all the respondents. Quantitative data were analyzed using inferential research methodology in this study. Questionnaires were used to gather primary data, which was then analyzed. Data analysis was carried out using the Statistical Package for the Social Sciences (SPSS), and descriptive and inferential statistics were used to show the study's results. According to the research, supply chain performance is positively and significantly affected by both automated and manual material handling. Mechanical material handling, on the other hand, improves supply chain performance, but not much. Inyange Industries' supply chain performance is influenced by the material handling systems to the tune of 19.3%, as shown by the modified R2 value of 0.193. According to the research, supply chain performance is positively and significantly affected by inventory counts, warehouse management systems, and inventory organization. A 0.967 adjusted R^2 value suggests that 96.7% of the variation in Inyange Industries' supply chain performance is explained by the inventory management techniques. According to the research, supply chain effectiveness is positively and significantly impacted by warehouse demand planning, design, and management. Warehouse capacity planning techniques at Inyange Industries account for 95.4% of the variation in supply chain performance, as shown by the modified R2 value of 0.954. The research concluded that material handling, inventory management, and warehouse capacity planning are all important warehouse management measures that significantly impact supply chain performance for the better. The methods used by Inyange Industries Ltd. for managing their warehouses have resulted in an improvement in supply chain performance of 87.2%. The regression coefficients, supported by their t-test values and Beta coefficients, highlight both the significance and strength of relationships between independent and dependent variables. Material Handling demonstrated the greatest impact (β1=0.532, t=8.556, p=0.000), followed by Inventory Management (β2=0.379, t=6.147, p=0.000), and Warehouse Capacity Planning (β3=0.172, t=3.268, p=0.002), emphasizing their respective contributions to Supply Chain Performance of Inyange Industries Ltd.'s supply chain. This proved that material handling in warehouse management has a major influence on supply chain performance. Because the p-value was lower than 5%, we may say that the association is statistically significant. The research concluded that both automated and human material handling should get additional funding. To maximize efficiency in stock-taking as well. Previous studies have looked at a variety of organizational factors that affect performance of supply chains. To further understand how warehouse management strategies affect overall performance, more research is needed.

Bayesian Algorithm for The Construction of Logistics Node Delay Model and Its Impact on Subsequent Nodes in Supply Chain

The logistics nodes delay of supply chain has become a focus of customer complaints at the State Post Bureau of China in recent years. Nodes delay usually also brings uncertain business loss. The purpose of this paper is to explore propagation of nodes delay and make it precisely controllable. To address this, Netica software is used and a hybrid strategy of genetic algorithm (GA) and tabu search algorithm (TS) validated by datasets is utilized to optimize the Bayesian algorithm model. Bayesian algorithm model of logistics nodes delay of supply chain is constructed through parameter learning. The empirical analysis is conducted on the basis of three types of nodes delay with 2041 sets of data for cargo departures and arrivals, upstream nodes delay, and nodes delay of supply chain. The results show that the nodes delay of supply chain gradually decreases from upstream to downstream; there are strong correlations between propagation probability and transfer time of nodes delay; the effects of initial node delay are the maximum, after 3 transitions, still having 30% probability to affect the succeeding nodes. Therefore, some suggestions, such as controlling the transfer points and transfer time and strengthening the management of initial node delay, are given.

Food supply chain resilience in major disruptions

PurposeCorona Virus Disease (Covid-19) is a global pandemic that emerged at the end of 2019 and caused disruptions in global supply chains, particularly in the food supply chains that exposed the vulnerability of today’s food supply chain in a major disruption which provided a unique research opportunity. This review explores the current research direction for food supply chain resilience and identifies gaps for future research in preparing for future major global pandemics.Design/methodology/approachThis article presents a review of food supply chain resilience followed a systematic literature review of the business and management-based studies related to the food supply chain in Covid-19 published between December 2019 and December 2021 to identify the immediate issues and responses that need to be addressed in the event of future disruptions in food supply chains due to new global health threats.FindingsThe study revealed the need for more literature on food supply chain resilience, particularly resilience to a major global pandemic. The study also uncovered the sequence of events in a major pandemic and identified some strategies for building resilience to potential future risks of such an event.Research limitations/implicationsThe limitations of this study are apparent. Firstly, the selection of databases is not comprehensive. Due to time limitations, authoritative publishers such as Springer, Emerald, Wiley and Taylor & Francis were not selected. Secondly, a single author completed the literature quality testing and text analysis, possibly reducing the credibility of the results due to subjective bias. Thirdly, the selected literature are the studies published during the immediate event of Covid-19, and before January 2022, other research studies may have been completed but were still in the state of auditing at this time.Originality/valueThis paper is the first study that provides a detailed classification of the immediate challenges to the food supply chain faced in both upstream and downstream nodes during a major global disruption. For researchers, this clearly shows the immediate difficulties faced at each node of the food supply chain, which provides research topics for future studies.

Enhancing Supply Chain Resilience in Coal Mining: A Review of Managing Disruptions

Objective – Coal mining operations encounter substantial risks and uncertainties that originate from a wide array of sources, encompassing but not limited to natural calamities, supplier disruptions, market volatilities, regulatory modifications, and geopolitical instability. This study aims to conduct a comprehensive literature review on supply chain resilience in the coal mining industry and pinpoint potential avenues for further investigation. Methodology – A systematic literature review (SLR) was utilized to examine a total of 115 studies in the field of management and the coal mining supply chain. The studies were published from 2010 to 2023. The vulnerabilities and resilience strategies within the coal mining supply chain are the focal points of our research. We have integrated viewpoints from the domains of management and the coal mining supply chain to support our analysis. Findings – Challenges such as resource distribution, government policies, and maintenance are prevalent, pointing to the need for strategies that enhance performance through dynamic optimization and incentivizing integration. Practitioners must identify vulnerabilities in the coal mining supply chain to proactively anticipate and effectively manage potential disruptions, thus bolstering operational resilience. Novelty –This study fills the gap in extant literature by investigating the sequential application of supply chain resilience in the context of coal mining operations using the integrative view of supply chain nodes. Type of Paper: Review JEL Classification: M00, L72, M11, O13. Keywords: Coal mining, Disruption, Risk mitigation, Supply chain resilience, Systematic literature review Reference to this paper should be made as follows: Sinaga, P.T; Simatupang, T.M; Basri, M.H. (2024). Enhancing Supply Chain Resilience in Coal Mining: A Review of Managing Disruptions, J. Bus. Econ. Review, 8(4), 01–10. https://doi.org/10.35609/jber.2024.8.4(1)

Blockchain technology for operational excellence and supply chain resilience: a framework based on use cases and an architecture demonstration

ABSTRACT Increased risks and uncertainties can disrupt the whole supply chain (SC), resulting in ineffective value transition. Facilitated by digital technologies, SC resilience can be achieved which enables organisations to strengthen capabilities. Therefore, blockchain is emerging as a promising technology that promises transparency and decentralisation across multiple SC nodes and can effectively respond to any disruption and recover fast through visibility. However, prior research does not offer a clear framework for blockchain adoption to achieve operational excellence and SC resilience. This paper develops an explanatory framework for SC resilience and operational excellence by conducting a rigorous analysis of recent literature, existing industrial cases (i.e. food SC, diamond SC, electric vehicle (EV) battery SC, blood SC), and a reference architecture implementation in forest SC. We explore how blockchain has addressed the traceability challenges and developed operational excellence in selected use cases. The theoretical and use case analysis reveal the promising effect of blockchain in developing capabilities and effective response systems where transparency, traceability, real-time information sharing, process, and security are the most common value propositions. The reference model (available on GitHub) demonstrates an increase in process efficiency by offering data safety, and transparent and traceable information which cannot be altered throughout SC.

Research on vehicle routing problem of automobile part Milk-Run with time windows constrained

Based on the parts inbound logistics as the research object, this thesis introduces Milk-run of third party logistics enterprise mode. Establish mathematical model under the premise of time window, through genetic algorithm optimize the distribution route, and using MATLAB to simulation, the results show that distribution vehicles reduced from 18 to 6. Transportation costs were reduced by 30.05%. Though the research on the circular pick-up mode of incoming logistics of parts and components, this thesis explores the strategy of optimizing its transportation path. On the one hand, it can solve the contradiction of reducing inventory cost but increasing transportation cost to a certain extent, and effectively reduce the cost of the nodes of the whole supply chain, which has certain theoretical value and significance for the research of vehicle path optimization; On the other hand, a reasonable distribution route can reduce driving distance and alleviate urban traffic pressure, while reducing distribution vehicles can reduce urban noise and automobile exhaust emissions, and contribute to the realization of low-carbon environmental protection.

Processes and Strategies for Digital Transformation in Manufacturing Industry

The manufacturing supply chain has undergone an on-going transformation using revolutionary digital technologies that have profoundly changed manufacturing processes and operation ways. It is necessary to conduct digital technologies to enhance production performance. The present study analysis related digital technologies in manufacturing sector and proposes a framework under the fourth industrial revolution background, explores the benefits and challenges of digitalization. In addition, this paper establishes a manufacturing system with the applications of big data, 5G, AI in manufacturing processes. The product data can be collected and stored in the nodes of supply chain. The traceability results show the digitalization has great impacts to the manufacturing systems.

Pricing Decisions for Power Battery Closed-Loop Supply Chains with Low-Carbon Input by Echelon Utilization Enterprises

Today, with the number of waste power batteries and consumers’ awareness of low-carbon both increasing, a new closed-loop supply chain model in which the node enterprises of reverse supply chains are being constructed. These are responsible for the recycling, echelon utilization and low-carbon innovation of waste power batteries. This provides a new way for the development of reverse supply chain node enterprises and lays a theoretical foundation. In this paper, we use the backward solution method to solve the Nash equilibrium solution of the Stackelberg game. Through numerical calculation and simulation, the decision variables, profit and income of the supply chain are analyzed and the equilibrium results are compared. The experimental results indicate that the implementation of low-carbon innovative production by cascaded utilization enterprises is conducive to the growth of their profits with lower cost inputs. The impact of the initial waste power battery recycling rate on the decision variables is negative, while, for the supply chain as a whole, the profit growth of the node companies can be positive and the location of the inflection point appears to be particularly important. The sensitivity coefficient of low-carbonization levels has a positive regulatory effect on decision variables and location of all parties. The closed-loop supply chain model proposed in this study promotes the overall development of a power battery closed-loop supply chain, and also provides theoretical guidance for reasonable pricing decisions of node enterprises under the new model. Based on the results of this paper, the government can implement incentives such as subsidies, or formulate reasonable policies for the development of a power battery closed-loop supply chain.

A Learnheuristic Algorithm for the Capacitated Dispersion Problem under Dynamic Conditions

The capacitated dispersion problem, which is a variant of the maximum diversity problem, aims to determine a set of elements within a network. These elements could symbolize, for instance, facilities in a supply chain or transmission nodes in a telecommunication network. While each element typically has a bounded service capacity, in this research, we introduce a twist. The capacity of each node might be influenced by a random Bernoulli component, thereby rendering the possibility of a node having zero capacity, which is contingent upon a black box mechanism that accounts for environmental variables. Recognizing the inherent complexity and the NP-hard nature of the capacitated dispersion problem, heuristic algorithms have become indispensable for handling larger instances. In this paper, we introduce a novel approach by hybridizing a heuristic algorithm with reinforcement learning to address this intricate problem variant.

Greening warehouses through energy efficiency and environmental impact reduction: a conceptual framework based on a systematic literature review

PurposeThe purpose of this paper is to propose a framework of green strategies as a combination of energy-efficiency measures and solutions towards environmental impact reduction for improving environmental sustainability at logistics sites. Such measures are examined by discussing the related impacts, motivations and barriers that could influence the measures' adoption. Starting from the framework, directions for future research in this field are outlined.Design/methodology/approachThe proposed framework was developed starting from a systematic literature review (SLR) approach on 60 papers published from 2008 to 2022 in international peer-reviewed journals or conference proceedings.FindingsThe framework identifies six main areas of intervention (“green strategies”) towards green warehousing, namely Building, Utilities, Lighting, Material Handling and Automation, Materials and Operational Practices. For each strategy, specific energy-efficiency measures and solutions towards environmental impact reduction are further pinpointed. In most cases, “green-gold” measures emerge as the most appealing, entailing environmental and economic benefits at the same time. Finally, for each measure the relationship with the measures' primary impacts is discussed.Originality/valueFrom an academic viewpoint, the framework fills a major gap in the scientific literature since, for the first time, this study elaborates the concept of green warehousing as a result of energy-efficiency measures and solutions towards environmental impact reduction. A classification of the main areas of intervention (“green strategies”) is proposed by adopting a holistic approach. From a managerial perspective, the paper addresses a compelling need of practitioners – e.g. logistics service providers (LSPs), manufacturers and retailers – for practices and solutions towards greener warehousing processes to increase energy efficiency and decrease the environmental impact of the practitioners' logistics facilities. In this sense, the proposed framework can provide valuable support for logistics managers that are about to approach the challenge of turning the managers' warehouses into greener nodes of the managers' supply chains.

Blockchain Technology Applied to Supply Chain Management: A Systems’ Analysis

Blockchain technology can be used to record real data at various nodes in the entire supply chain and can achieve timely data sharing and full traceability of the whole lifecycle of products in the supply chain. This study conducts a systematic literature review based on the WOS database, focusing on the research topic of the application of blockchain technology in supply chain management. We propose clear search and screening criteria based on 4 research questions and finally obtain 591 target studies. We conduct a detailed study on the distribution of the target literature in this research area, country/region, institution, and journal. Different countries/regions cooperate with each other and, thus, are clustered into five significant countries regions’ cooperation networks. There is a strong coupling relationship between research institutions, forming four major institutional cooperation networks. According to the analysis of those papers with a high number of citations, most of such papers were published in 2019, while the cross-citation phenomenon between papers occurred more frequently in 2021 and 2022. We use VOSviewer for visual coupling analysis of all keywords, which are automatically clustered into three research hotspots. Using CiteSpace to perform timeline-based keyword cooccurrence analysis, we find that scholars have gone through a “discovery-acceptance-question-improvement” process for the application of blockchain technology in supply chain management. According to the intensity and duration of burst detection words in different years, we draw three key points for future research. (i) Blockchain technology should be used to restructure and optimize the high-end food and medical cold chain supply chains. (ii) Blockchain technology should be used to enhance the cooperative relationship between supply chain members and the overall competitiveness of the supply chain. (iii) Innovate blockchain encryption technology that should be used to reduce the risk of information and privacy leakage in the supply chain.