Supply Chain Risk Management: an Interactive Simulation Model in a Big Data Context

The rapid development of technology has enabled companies to integrate internal and external partners working together in the supply chain network. Supply chain integration allows fast information to facilitate real-time and reliable decision-making. This study investigates the role of supply chain integration on firm performance through adopting lean manufacturing, green supply chain management, and risk management. The study surveyed manufacturing companies implementing ISO 14000 to represent green supply chain management and integrated information technology as a form of integration. The questionnaires were distributed using a Google form, and 93 valid responses were obtained. Data analysis employed a partial least square approach with SmartPLS software 4.1 version. The data processing results found that supply chain integration increased lean manufacturing by 0.684, green supply chain management by 0.451, and supply chain risk management by 0.333. Lean manufacturing companies using a continuous process control system and process improvements significantly improve green supply chain management by a path coefficient of 0.477, supply chain risk management by 0.206, and firm performance by 0.370. Green supply chain management significantly impacts supply chain risk management by a coefficient of 0.416 and firm performance by 0.189. Supply chain risk management with a system for detecting operational process risks and emergency procedures in overcoming changes in customer orders affects the increase in firm performance by 0.354. The practical contribution of research provides insight for practitioners to invest in information technology and adopt ISO 14000 implementation. Theoretical contributions in developing resources-based view theory in adopting green supply chain management and lean manufacturing.

Background: Operational performance faces many challenges in the production of tin especially for Indonesia as the global market leader. Optimization of its operational performance by bolstering its supply chain integration such as customer integration in downstream processes and integration internally is a big challenge with the lack of smelter though it has been catalyzed by Indonesian government regulation. Additionally, supply chain risk management has been considered important globally to the sustainability and environmental awareness of a tin company related to its operational performance and supply chain integration.Purpose: This research aims to investigate how internal integration and customer integration, mediated by supply chain risk management, affect operational performance in a tin mining company. Design/methodology/approach: Employing a quantitative associative design and proportionate stratified random sampling method used in this study. Data from 47 employees from seven divisions of a tin company in Indonesia were collected and analyzed using PLS-SEM analysis on SMART PLS 3.29 software. Findings/Result: Results indicate a significant positive relationship between customer integration and operational performance, mediated by supply chain risk management. Contrary to expectations, internal integration did not significantly influence operational performance, either directly or indirectly.Originality/value (State of the art): These findings contribute to the evolving body of knowledge on supply chain integration by highlighting the critical role of customer-centric approaches in enhancing operational effectiveness within the tin mining sector. For practical implication, Effective collaboration, knowledge sharing, and understanding customer needs are key factors in achieving success in supply chain management. Keywords: customer integration, internal integration, supply chain, risk management, operational performance

Supply chain (SC) risk management (SCRM) is a high-level concern for SC professionals. Supply chain risk management implementation is a difficult task because it requires involvement of various firms across the SC. For effective SCRM implementation, managers need to know the enabling factors and their relative importance. In this research, an empirical study on SC risk mitigation enablers was carried out in Indian automotive industry to examine the relationship between SCRM enablers and SCRM implementation. This relationship was tested using discriminant analysis. The research shows that the most important enabler is information visibility and it is followed by incentives alignment. Contingency planning is the third-most important enabler and last is risk management governance (RMG). Success of the SCRM implementation in terms of its efficiency and effectiveness can be assured by following the sequence of SCRM enablers suggested in this research.

: The purpose of this research was to improve defense supply chain risk management processes through better intelligence integration. To this end, this research sought to capture the present state of academic and Department of Defense (DoD) thought regarding supply chain resiliency and risk management through an extensive review of current academic and DoD literature regarding supply chain risk management and intelligence doctrine. This review established the importance of supply chain risk analysis to ensuring supply chain resiliency and identified a significant gap in DoD acquisitions policy and guidance regarding intelligence support to supply chain risk analysis. This research culminated in the development of a methodology for intelligence professionals to use to support supply chain risk management processes. Specifically, this paper provides analysts a methodology to provide intelligence support to risk analysis for United States Air Force (USAF) weapon system supply chains based on the Intelligence Preparation of the Operational Environment process established in Joint doctrine. While the methodology developed in this paper is targeted at USAF weapon system supply chains, it is readily adaptable to other DoD acquisitions program supply chains. Additionally, this paper provides recommendations for future research to further improve intelligence support to supply chain risk management.

Maintaining an effective risk management procedure can counterbalance a critical effect on supply chains. The Agri-food supply chain has characteristics that are unique and complex if compared with a conventional supply chain. Sustainability risk management in the supply chain is the key to a competitive organisation in the long term. The aim of this paper is to review current research on sustainable risk management in the Agri-food industry chain. These reviews were arranged in steps systematically, ranging from searching related to review of supply chain sustainability risk management (SCSRM), reviewing the general framework of SCSRM and the framework of Agri-food SCSRM. Selection of literature review papers in the period 2010-2019, and obtained 30 papers. Risk aspects were analysed using a multi-dimensional approach (economic, social, environmental, technical, and institutional) that influences the sustainability of the Agri-food industry. The results show that there are few studies focusing on risk management to achieve a sustainable supply chain system. Some studies only focus on Triple Bottom Line elements (economic, social, and environmental). Sometimes, these studies do not consider risks from other elements such as technical and institutional aspects that can be influence the sustainability of the Agri-food industry. Technical aspects such as the reliability of technological systems and institutional aspects as policymakers support sustainability in a business process. The contribution of this paper is to provide an initial theoretical framework to guide researchers in analysing risk through a multi-dimensional approach to sustainability.

One of the most important problems that multinational organizations are dealing with in risk-oriented supply chains is efficiency assessment and choosing the best low-risk financial institution for financial assistance. We provide an integrated approach for evaluating the unpredictable, dangerous, and fragile arrangement of the financial sector, which directly affects the supply chain network's processing stages. This model is supported by fuzzy-soft tools. The real economy is currently under pressure from both the domestic economic crisis and the decline in international commerce. President Xi Jinping has often suggested stepping up initiatives to assist the real economy's high-quality growth. In this regard, the development of the model for supply chain financing offers a fresh approach to resolving the funding issues faced by businesses. To tackle the financial issues facing the marketplace, we should use the chain of custody finance model, but we also need to thoroughly understand the risks associated with it and how to manage them. False trade orders and insufficient control over core businesses are difficulties that the present logistics finance risk management must deal with. The World Wide Web, big data, and block chain technologies are all blooming, opening new avenues for risk management in block chain finance. As a result, the goal of this essay is to examine the features of supply chain finance based on the technology of block chain, examine the risks associated with financing supply chains, and debate how to use block chain innovation for supply chain banking risk management.[4] Risk Financing: To assist organizations in transferring or reducing supply chain risks, financial institutions offer risk financing solutions including insurance & alternative risk transfer methods. The creation of novel risk financing products, evaluation of their performance, and comprehension of the effects on the resilience of supply chains can all be the subject of research. Financial institutions provide supply chain financing options like factoring, discounted invoices, and supply link finance programmed that help businesses manage their working capital, improve cash flow, and lower the risk of supplier failure to pay or insolvency. The effects of different financing choices on supplier relationships, supply chain stability, and overall risk reduction may be studied. Financial institutions collaborate with businesses to detect and classify different supply chain risks. An extensive investigation of the supply network environment, encompassing suppliers, transportation, logistics, and market dynamics, is required in this phase. Data gathering techniques used may include questionnaires, interviews, & site visits. In the above rank one is axis, and the last one is Punjab national bank. Financial Institution in Supply Chain Risk Management In the above rank one is axis, and the last one is Punjab national bank.

The increasing complexity and uncertainty in global supply chains have intensified the need for effective risk management strategies. In recent years, Artificial Intelligence (AI) has emerged as a transformative technology capable of enhancing the identification, prediction, and mitigation of supply chain risks. This study conducts a systematic review of existing literature to examine the role of AI in supply chain risk management. Using a structured review approach, relevant research articles published between 2015 and 2025 were collected from major academic databases and screened based on predefined inclusion and exclusion criteria. The review aims to synthesize the existing body of knowledge on how AI technologies such as machine learning, predictive analytics, and big data analytics are applied to manage disruptions and uncertainties in supply chains. Furthermore, the study identifies the dominant research themes, technological applications, and methodological approaches adopted in previous studies. The findings highlight the growing integration of AI-driven tools in areas such as demand forecasting, disruption prediction, supplier risk evaluation, and decision support systems. Despite the increasing attention to AI-based solutions, the review also reveals several research gaps related to implementation challenges, data quality issues, and integration with traditional risk management practices. The study provides a comprehensive understanding of the current research landscape and offers directions for future studies in AI-enabled supply chain risk management.

Strategic supply chain planning and supply chain risk management are two fields of supply chain management that are inseparable nowadays. The ability to consider risks is essential to maintain business performance. In addition, integrating the different business departments’ visions in a common business vision is necessary to properly plan the future of a company. However, it is still a challenge for companies to design and maintain a decision-making process supporting strategic supply chain decisions that integrates risk management and unify business vision across departments. This paper relates an industrial experiment as an attempt to meet this challenge. This experiment was asked by a pharmaceutical company with the aim of supporting strategic decisions regarding its network of suppliers. It led to a decision-making process including the use of a computerized information system composed of a software for computations and a business intelligence software to easily make decisions. This process was put in practice on a pilot use case with two years old data. It resulted in the identification of several decisions that could have been made if the process was in operation two years ago, which is considered as a first validation of the approach. Finally, limitations have been identified regarding the data collection, opening avenues for future research on an innovative approach combining supply chain hyperconnectivity and event-driven principles.

Towards Decision Support Automation for Supply Chain Risk Management among Logistics Network Stakeholders

The aim of this study is to investigate the effect of supply chain risk management on supply chain resilience in the presence of Internet-of-Things as an intermediate variable. In other words, the study seeks to identify whether supply chain risk management completely affects supply chain resilience. Collecting data by a questionnaire from a sample composed of managers of Jordanian industrial firms, the results show that supply chain risk management has a direct and indirect effect on supply chain resilience through Internet-of-Things. These results do not support the hypothesis that supply chain risk management completely affects supply chain resilience and accepted the hypothesis that Internet-of-Things intervenes the effect of supply chain risk management on supply chain resilience. The study contributes to the literature through filling a research gap regarding the mediating role of Internet-of-Things in the relationship between supply chain risk management and supply chain resilience and contributes to the industry through instructing managers to adopt technologies such as Internet-of-Things to help their firms cope with supply chain risks.

Based on analyzing the characteristics of supply chain risk management under the influences of knowledge, in this paper integrates basic theories and methods of knowledge management into the process of risk management, builds a knowledge-oriented supply chain risk management system model, and proposes relevant strategies, presenting references for practical application of knowledge-oriented supply chain risk management. By means of acquiring, storing, sharing, and transferring supply chain risk knowledge and knowledge innovation, it can ensure the knowledge supply for the whole process of supply chain operation management and risk management, effectively blocking the evolution and transmission of risks in supply chain, realizing the added value of activities in supply chain, and improving the performance of supply chain.

In today's globalized business landscape, enterprises face increasing reliance on intricate supply chains to deliver goods and services efficiently. However, this interconnectedness exposes organizations to diverse risks, exacerbated by factors like natural disasters, geopolitical tensions, and technological vulnerabilities. The COVID-19 pandemic further emphasized the vulnerability of supply chains, prompting the urgent need for robust risk management strategies. Interstate conflicts also significantly influence supply chain risks, posing challenges such as trade disruptions and security vulnerabilities. To mitigate these risks, enterprises must adopt proactive risk management strategies, enhance supply chain resilience, and leverage technology-enabled solutions for real-time monitoring and response. The study examines supply chain risk management (SCRM) practices in healthcare establishments in Algeria and Ukraine, comparing countries with differing healthcare systems. The research aims to identify disparities in SCRM approaches and their consequences. Results reveal that while both countries prioritize technology for predictive analysis, Algerian managers emphasize collaboration with other institutions. The study suggests integrating SCRM technology into enterprise management system, prioritizing advanced technological solutions, scenario planning, collaborative partnerships, comprehensive risk management plans, continuous monitoring, and strengthening supplier relationships to enhance supply chain resilience and continuity in healthcare service delivery. These findings underscore the importance of efficient SCRM strategies in mitigating supply chain disruptions and ensuring uninterrupted healthcare services. By implementing these strategic measures, healthcare establishments can enhance their SCRM capabilities, thus promoting resilience, efficiency, and continuity in healthcare service delivery across diverse healthcare systems.

On the use of simulation as a Big Data semantic validator for supply chain management

The ISO 31000 standard in supply chain risk management

Contemporary supply chains are facing myriad types of risks caused by unprecedented risk factors. This condition motivates us to develop a contemporary supply chain risk typology to help identify and monitor newly surfaced risks and reveal emerging topics and research collaborators to help foster impactful research in supply chain risk management (SCRM). In this paper, we applied the scholarly network analysis approach to critically analyse an extensive list of 345 SCRM journal articles published from 2011 to 2020. We address two research questions: What is the contemporary supply chain risk typology? How can SCRM research be mapped comprehensively in terms of its emerging topics and research collaborators? First, we propose a novel and holistic classification of supply chain risks based on three interconnected perspectives, namely the characteristics, the location, and the impact of risks. Second, we identify five emerging SCRM topics. In each of these emerging topics, we identify the prominent collaborators and the core author, the main research themes, commonly used approaches and theories, and potential research agendas for bridging the identified research gaps. This paper contributes to the field of SCRM by aiding scholars and practitioners in managing contemporary supply chains resiliently and sustainably.