Blockchain integrated optimized supply chain security using horse herd algorithm

Recent catastrophic events and risks which have disrupted economies and supply chains around the world create new avenues/agendas for supply chain risks and security. Researcher and practitioner are showing increasing research interest on this area. This research has an effort to identified key factors and relation in supply chain risks and security and development of research framework. Given the increasing awareness of this important topic, the purpose of this research is to study supply chain critical risks important for supply chain security perspective and to investigate the relationship between supply chain vulnerability and supply chain risk. Interpretive structural modelling (ISM) has emerged as a means to analyse the relational aspects of the variables. The objective of this paper is to identify critical enablers of supply chain security management and to establish and analyse relationships among these enables using interpretive structural modelling. This research is continuing in this direction.

Supply Chain Management (SCM) is advancing through the incorporation of machine learning and mathematical modeling methods, improving decision-making effectiveness. The aim of this study is to improve the supply chain functions through four algorithms: Long Short Term Memory (LSTM), Support Vector Machine (SVM) Genetic Algorithm (GA), and Reinforcement Learning (RL). A result of the forecasting experimental data shows that LSTM achieved 94.3% accuracy forecast which exceeds SVM’s 87.8%. GA provides 23% improvement in savings with respect to conventional optimization techniques and RL brings a 15% increase in delivery efficiency through real-time decision making. Comparison of these techniques with existing methods reveals the greater efficiency of hybrid models that combine information from AI with more traditional means. In addition, the research evaluates how blockchain and digital twin technologies improve transparency, and security in supply chains. Despite these issues, the results show that supply chain efficiency can be markedly improved using AI powered decision making. As future studies, combined optimization frameworks and supply chain management ways that focus on sustainability should be investigated to have robust and environmentally friendly supply chains. By arguing that smart supply chain decision needs to be based on empirically validated theoretical assumptions, this research sheds important light on how scholars and industry experts can try to improve supply chain performance through smart decision making.

The Effect of Facility Management in Supply Chain Security Operational Performance and Firm in Malaysia

In response to the changing international landscape and the risks associated with China’s supply chain security, conducting policy simulations on semiconductor supply chain security helps clarify the industry’s policies and governance strategies for semiconductor supply chain security in China. It also enables a better understanding of the current state and focus areas of China’s semiconductor supply chain security, which is of great significance for improving the security levels of semiconductor supply chains across provinces and cities and for constructing a secure, efficient, and autonomous semiconductor supply chain system. Firstly, this paper reviews the current research on semiconductor supply chains, supply chain security, and industrial policies. Secondly, based on the industrial policies for semiconductor supply chain security, an evolutionary game model is constructed, involving government departments, chain owner enterprises, and upstream and downstream small and medium-sized enterprises (SMEs) within the supply chain. Finally, the MATLAB R2016b system simulation method is employed to conduct a policy simulation analysis of China’s semiconductor supply chain security and further analyze the industrial policies related to semiconductor supply chain security. The results show that: (1) Supply chain security depends on multi-agent collaborative governance, with government leadership, and chain owner enterprises driving innovation in SMEs, improving digitalization levels, and ensuring supply chain autonomy and control. (2) Increasing government management revenue, raising the responsibility costs for chain owner enterprises, and reducing the innovation costs for SMEs can accelerate the achievement of the ideal governance state. Lastly, policy recommendations are proposed to build an autonomous and controllable supply chain system.

In most recent time, the global landscape of supply chain management has experienced unprecedented challenges during the COVID-19 pandemic, which has significantly impacted the routine and smooth operations of different firms in the United States. This paper explains about the importance of artificial intelligence (AI) and machine learning (ML) in the mitigation of these disruptions and possible ways of improving supply chain security and its efficiency. This research adopted a questionnaire survey involving 281 managers, with the aim to comprehensively examine the current state of AI integration across the U.S. supply chain sector, with focus on some key components like real-time tracking, cost optimization, and risk management. A mixed method approach was adopted for this research, utilizing both inferential and descriptive analyses to unravel insights and trends into the role of AI in enhancing supply chain security. The results indicate that integrating AI, most especially through cost optimization, real-time tracking, and risk management components, emerges as a significant determinant of supply chain security in the United States. Real-time tracking technologies are identified as crucial for monitoring shipments and assets, enabling quick responses to security incidents, and ensuring end-to-end visibility throughout the supply chain. Despite the potential benefits, the study highlights challenges that hinder the widespread integration of AI technologies in the U.S. supply chain. The high cost of AI adoption and the limited availability of skilled personnel are major obstacles. To address these challenges, the paper proposes practical recommendations. Firstly, real-time tracking technologies are recommended to monitor shipments and assets, facilitating rapid responses to security incidents, and ensuring visibility across the entire supply chain. Furthermore, the paper suggests optimizing costs by investing in cost-effective security solutions. This includes leveraging AI for automated monitoring systems and adopting secure packaging measures. These strategies aim to minimize vulnerabilities without compromising security standards, offering a balanced approach to enhancing supply chain security while mitigating the financial implications associated with AI adoption.

Background This systematic assessment of 408 research publications from 2004 to 2024 examines how talent management (TM) improves supply chain optimization (SCO). Objective The main goal is to find and study TM CSFs that affect SCO. The research distinguishes internal elements (consumer expectations, flexibility, and cost reduction) from external aspects (human capital and sustainability) and provides insights into successful TM techniques that enhance supply chain performance. Methods This research examines talent management (TM) and supply chain optimization (SCO) using a systematic literature review and bibliometric analysis. The study maps co-occurrence networks and significant themes using VOSviewer and RStudio on 408 Web of Science articles. TM’s influence on SCO is assessed by categorizing key success factors (CSFs) and showing trends, topic clusters, and literature gaps. Results show that strategic TM practices including personnel planning and performance management improve operational efficiency, innovation, and market response. The paper also emphasizes TM integration into supply chain strategy by highlighting TM and SCO developments. Implications This study highlights the relevance of TM in SCO and lays the groundwork for future research on TM and SCO.

Purpose– The purpose of this empirical research is to attempt to explore the effect of information security initiatives (ISI) on supply chain performance, considering various intra- and inter-organization information security aspects that are deemed to have an influence on supply chain operations and performance.Design/methodology/approach– Based on extant information security management and supply chain security management literature, a conceptual model was developed and validated. A questionnaire survey instrument was developed and administered among supply chain managers to collect data. Data were collected from 197 organizations belonging to various sectors. The study used exploratory and confirmatory factor analysis for data analysis. Further, to test the hypotheses and to fit the theoretical model, structural equation modeling techniques were used.Findings– Results of this study indicate that ISI, comprising technical, formal and informal security aspects in an intra- and inter-organizational environment, are positively associated with supply chain operations, which, in turn, positively affects supply chain performance.Research limitations/implications– This study provides the foundation for future research in the management of information security in supply chains. Findings are expected to provide the communities of practice with better information security decision-making in a supply chain context, by clearly formulating technical, formal and informal information security policies for improving supply chain performance.Originality/value– In today’s global supply chain environment where competition prevails among supply chains, this research is relevant in terms of capability that an organization has to acquire for managing internal and external information security. In that sense, this study contributes to the body of knowledge with an empirical analysis of organizations’ information security management initiatives as a blend of technical, formal and informal security aspects.

The article discusses supply chain optimization based on blockchain supply chain technology and genetic algorithm in the context of IoT to improve the availability of goods and the security of logistics information, improve supply chain efficiency and reduce transportation costs. First, the basic theories of supply chain technology, supply chain optimization and genetic algorithm are introduced, and supply chain optimization with collaborative logistics information management is analyzed. Then, a supply chain network optimization model based on genetic algorithm is established and the optimization results are analyzed. The optimization results show that applying blockchain technology to collaborative logistics information management system improves the overall efficiency of supply chain logistics; using genetic algorithm, the logistics distribution cost is reduced. The study is innovative in optimizing the collaborative logistics information management system in the logistics supply chain and the logistics distribution channel by using blockchain technology and genetic algorithm to improve the security and availability of logistics information. The case study shows that the optimization of supply chain logistics using blockchain technology and genetic algorithm improves efficiency, reduces costs, improves corporate governance and economic efficiency, and increases the competitiveness of the company.

The Cyber Supply Chain (CSC) system is a multifaceted system with multiple subsystems carrying out distinct functions. The inherent vulnerabilities and threats from any portion of the system that can be exploited at any point in the supply chain make supply chain security difficult. This can cause a severe disruption on the overall business continuity. Thus, it is critical for organizations to comprehend and assess the risks in order to implement the appropriate supply chain security management measures. In order to analyse and forecast the risks based on the features of Cyber Threat Intelligence (CTI), we have combined CTI with Machine Learning (ML) approaches. To demonstrate the applicability of our approach, CTI data is gathered and a number of ML algorithms, i.e., Logistic Regression (LG), Support Vector Machine (SVM), Random Forest (RF) and Decision Tree (DT), are used to develop predictive analytics using the Microsoft Malware Prediction dataset. KEYWORDS: Cyber Supply Chain, Malware, Cyber Threat Intelligence, Machine Learning.

An avalanche of new supply chain security (SCS) standards, programs and regulations have emerged since 2001. These have been developed and promoted by various governmental, supply chain and standardization parties. Due to political, economic, technical and legal reasons, no dominating global standard has been developed that covers all possible aspects of SCS. Instead, we have seen national and regional, transport mode-specific, crime issue-specific, and other types of more focused SCS standards gaining some popularity within supply chain operating communities. This paper intends to capture and explain the most relevant SCS standard characteristics, in order to form a pragmatic framework for the analysis and design of SCS standards for the benefit of governmental policy makers and business community supply chain and security experts. A theoretical framework derived from the literature is tested and further developed in a real-life SCS standardization feasibility study project. Recommendations are made as to how the framework might be exploited, and topics for future research are suggested.

Optimal supply chain design depends on the business context the chain caters for. In this dissertation, we are concerned with attaining and maintaining this alignment between a firm's supply chain portfolio and its business context. Following an introduction in Chapter 1, in Chapter 2 of this dissertation, we analyze the influence of a firm's product types on optimal supply chain design: Academics and practitioners agree that functional products are best delivered via physically efficient supply chains, while innovative products are best delivered via market responsive chains. However, to date, only a few firms have systematically adjusted their supply chain strategies according to this argument. Instead of carrying only one product type, firms deliver a number of both functional and innovative products in parallel complicating the alignment of supply chain portfolios with product portfolios. We address this issue and analyze in detail a firm's optimal supply chain portfolio as a function of its product portfolio. We target the tactical level of decision-making and develop a generic mathematical model to analyze how product portfolios affect the optimal setup of supply chain portfolios. We identify generic problem properties and perform extensive sensitivity analysis to illustrate our findings with numerical examples. Our results indicate that effective supply chain and product portfolio alignment holds the potential for significant cost savings. Because of the large number of factors influencing the optimal set-up, however, profound quantitative analysis is required to exploit the full potential of aligning the supply chain with the product portfolio and to guide implementation. In Chapter 3, we extend our modeling framework and take into account the fact that a firm's products and global business parameters, such as labor rates and transportation costs, evolve over time. Hence, firms need to adapt their supply chain portfolios frequently to stay aligned in the long term. Adapting a well-established supply chain portfolio, however, may involve high costs and expose a firm to unforeseeable risks. We address this issue, differentiating business dynamics into product portfolio dynamics and global business dynamics, and classifying supply chain adaptation into high, medium and low. Building on these classifications, we extend our mathematical model to analyze how much supply chain adaptation a firm actually requires to respond to the business dynamics it faces. Our results indicate that supply chain adaptation may indeed be crucial for a firm to retain its competitiveness. The need for adaptation, however, varies widely across firms: For example, a firm faced with product portfolio commoditization may be required to adapt its entire manufacturing footprint, while a firm with a high product turnover rate may not need to adapt its supply chain portfolio at all. Furthermore, the need for supply chain adaptation is not only determined by the business context in which a firm operates, but can also be manipulated by the firm's product portfolio decisions. Finally, a firm should carefully align its supply chain portfolio with the employed supply chain adaptation strategy to exhaust attainable benefits. In Chapter 4, we widen our scope and develop a step-by-step process to guide sustained alignment between a firm's business context and its supply chain portfolio in practice. Drawing on academic literature, insights from our quantitative models, and extensive interviews with executives from leading firms, we propose and detail four process steps. In the first step we suggest challenging the performance of a firm's current supply chain setup and identifying pressure points to evaluate how acute supply chain realignment is. As a second step we propose and detail a business context analysis to identify what a supply chain lacks and potential areas for realignment. To complement the previous analysis, in a third step, we frame and discuss generic options for long-term supply chain strategy. As a fourth step, we lay out opportunities and pitfalls during the project implementation. We conclude with recommendations on how to stay aligned in the long term. We end the dissertation with a conclusion in Chapter 5.

Palladium, essential in manufacturing industries and sustainable development, faces supply stability threats due to its concentrated geographical distribution and global supply–demand mismatch. This study employs complex network analysis and the cascading failure model to assess the supply chain security of the global palladium trade network during 1990–2023. The results show that the network structure is shaped by multiple factors including geopolitics, economic climates, and industrial technology. A notable decrease in the concentration of palladium supply has been observed, with higher network densities, average clustering coefficients, and shorter path lengths indicating the network's enhanced aggregation, transmission efficiency and overall resistance ability to risks. However, the recent intensification of global geopolitical situations has led to a trend of reconfiguration and isolation, progressively partitioning the network into communities of North America, Western Europe, and Russia‐East Asia, while elevating the geographical proximity as a crucial factor in trade. Despite the fact that Russia and South Africa, as major producers and suppliers of palladium, play significant roles in the spreading of supply chain crises, the central status of the network remains dominated by palladium consumers and transit countries. The risk matrix assessment demonstrates that supply risks have declined more substantially than vulnerabilities, revealing that the improvements in palladium's supply chain security are more dependent on mitigating the severity of a potential supply disruption rather than its likelihood. This study serves to integrate the dynamic perspective of crisis propagation into the evaluation of supply chain security, approaching a scenario closer to reality.

Supply chain security is one of the most integral aspect in global trade. The flow of goods or logistic through land, sea, and air transportation should be granted for its security. But with many Terrorism issue and accident pose a threat to supply chain because terrorism can destroy the flow chain of goods. United States then come as a pioneer in enforcing supply chain security through a program called CTPAT which focused on controlling and exmanining incoming cargo to US by US Custom and Border Protection (incoming import products). But what makes it interesting is, this program can enforce and strengthen global supply chain security. This research was meaning to explain how far is actor’s role in enhancing global supply chain security through CTPAT using complex interdependence where CTPAT is a public private partnership which makes private sector is considered into having role in enhancing global supply chain security. This research argue that actors role in enhancing global supply chains security is determined by benefits that actor’s gain in CTPAT Partnership and also because the emerging of terrorist threat to supply chain security which also included in CTPAT.

Locally as well as internationally, supply chains are subject to security risks and incidents, which can have negative influences on both trade and the economy as a whole. It is also attested that the industrial revolution 4.0 imposes mandatory conditions on companies to expand and connect all internal processes with customers and suppliers, in order to adopt effective strategies for the supply chain. The model that offers practitioners a modern tool to streamline international supply chains and ensure security is the ISO 28001 international standard, which recognizes the complexity of supply issues, because they are dynamic and involve many business actors (organizations, partners). Ensuring an adequate level of security of the international supply chain is possible with the partial or total implementation of the ISO 28001 standard. This standard can be considered as a tool of strategic supply chain management, with the help of which any company could increase the competitiveness of the chain. This paper comes with a theoretical approach to what supply chain and international supply chain means, and how it can be improved by applying/implementing the requirements of the ISO 28001 standard. The research objectives were achieved by using traditional research methods, such as theoretical, empirical qualitative and quantitative. The literature was researched, both in traditional format, but also in the form of electronic publications in the field of procurement, international supply chains and international ISO standards.

Supply chain disruptions may derive from various sources but the antagonistic threats are centered in supply chain disruption. Antagonistic threats are dynamic due to the spiral input, processes and feedbacks which create a very complex situation to analyze, assess and making decision. Beside risks, vulnerability derived from supply chain characteristics is the other issue which should be measured. Antagonistic threats are magnified in such vulnerable supply chains. After 9/11, 2001, the Security and Efficiency of the global supply chain has become an important issue in global transportation. This leads firms to consider Supply chain security as part and parcel of a company’s comprehensive risk-management program. In a security business, it is essential to understand different type risks and evaluate transportation assets, do risk based prioritization, and protect customers through cost effective actions. This could be occurred corresponding to risk management methods. Providing security may occur internally by firms or they outsource it to security providers which could be performed in higher quality or more cost effectively. In this article, we focus on managing the risks and securing the supply chain business with the security theory and strategies in the supply chain and transportation network. In order to discover risks throughout the supply chain, security provider needs to find risk hot spots where the likelihood of risk is higher. We propose two approaches (geographical and elements/process) to seek probable risks. The next step is to take strategies for risk prevention and risk mitigation. Consequently, we connect the security strategies from the literature review and collected information from security business to suggest a suitable model of how to handle the risks and achieve security in a systemic and scientific way.