Relevant bibliographies by topics / Supply chain risk monitoring

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Supply chain risk monitoring'

Author: Grafiati
Published: 5 June 2025
Last updated: 24 June 2025

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Journal articles on the topic "Supply chain risk monitoring"

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Richert, Maria, and Marek Dudek. "Risk Mapping: Ranking and Analysis of Selected, Key Risk in Supply Chains." Journal of Risk and Financial Management 16, no. 2 (2023): 71. http://dx.doi.org/10.3390/jrfm16020071.

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This study aimed to analyze the impact of key causes of external and internal risk on supply chains. The basic and most probable causes of the risk are listed, based on literature research and interviews with representatives of the metal industry. The analysis was carried out by semiquantitative assessment using risk maps. The relationship between the probability of an event occurrence and its impact on supply chains was tested. The study postulates that key risk factors can be controlled through risk monitoring. Attention was drawn to the beneficial aspects of using risk maps that enable a comprehensive assessment of the situation. Both external and internal risks can cause turmoil and disruption of the supply chain. The findings suggest that external uncertainty and crises have the most direct impact on supply chain risk and are the most dangerous. The work presents the possibility of practical application of risk maps for risk assessment and monitoring. The presented approach to risk assessment complements the methodology of risk assessment and monitoring. Risk maps were used as a basic tool in assessing the impact of individual risks on supply chains. It has been found that supply chains are subject to high risk, which can be monitored through risk matrix procedures. The conducted analysis showed that critical risk areas in supply chains are external crises, environmental uncertainty, supply chain relationships, and manufacturing and the most dangerous risks in supply chains are related to external conditions beyond the control of the participants in the supply chain. The article fills a gap in research on risk monitoring in supply chains by focusing on selected, generalized measures related to industrial supply.
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Daniel, Cheruyot Barmoiben, and Sammy Odari Dr. "ROLE OF SUPPLY CHAIN RISK MANAGEMENT ON PROCUREMENT PERFORMANCE IN COUNTY GOVERNMENTS IN KENYA." International Journal of Recent Research in Commerce Economics and Management (IJRRCEM) 9, no. 4 (2022): 151–61. https://doi.org/10.5281/zenodo.7477145.

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<strong>Abstract</strong><strong>:</strong> County Governments in Kenya have undertaken projects that have failed to meet the intended objectives largely due to increased risk and uncertainty in supply chain. The general objective of this research project is to establish the role of supply chain risk management on procurement performance; case study of Kericho County Government. The objectives of the study were: to determine how supply chain risk identification, supply chain risk assessment, supply chain risk mitigation and supply chain risk monitoring influences procurement performance. Descriptive research design was adopted where target population of 400 respondents drawn from both technical and support departments. Sample size of 120 respondents was utilized using stratified random sampling design. Questionnaires were used as the research instrument. Quantitative data was presented in tables and multiple regression analysis was used in development of the research model. The outcome of the research points out that the independent variable has good explanatory power and significant. The study recommends that: County Governments should develop mechanisms for identification of risks; develop and implement appropriate mechanisms for analysis and evaluation of risks; undertake risk mitigation planning to mitigate against risks and; ensure appropriate risk control and monitoring management strategies are developed and implemented. <strong>Keywords:</strong> supply chain risk identification, supply chain risk assessment, supply chain risk mitigation and supply chain risk monitoring. <strong>Title:</strong> ROLE OF SUPPLY CHAIN RISK MANAGEMENT ON PROCUREMENT PERFORMANCE IN COUNTY GOVERNMENTS IN KENYA <strong>Author:</strong> Daniel Cheruyot Barmoiben, Dr. Sammy Odari <strong>International Journal of Recent Research in Commerce Economics and Management (IJRRCEM)</strong> <strong>ISSN 2349-7807</strong> <strong>Vol. 9, Issue 4, October 2022 - December 2022</strong> <strong>Page No: 151-161</strong> <strong>Paper Publications&nbsp; </strong> <strong>Website: www.paperpublications.org</strong> <strong>Published Date: 23-December-2022</strong> <strong>DOI: https://doi.org/10.5281/zenodo.7477145</strong> <strong>Paper Download Link (Source)</strong> <strong>https://www.paperpublications.org/upload/book/ROLE%20OF%20SUPPLY%20CHAIN%20RISK%20MANAGEMENT-23122022-4.pdf</strong>
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Usykova, Olena. "Risk Analysis of Supply Chains at an Enterprise." Modern Economics 37, no. 1 (2023): 96–100. http://dx.doi.org/10.31521/modecon.v37(2023)-14.

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Abstract. Introduction. The article investigates the issues of the methodology for assessing the impact of external and internal risks on supply chains. The interrelation between the probability of occurrence of a hazardous event and its impact on supply chains is examined. The principal research method is the use of risk maps on the basis of matrix modeling. Purpose. The purpose of the article is to reveal modern approaches towards the methodology of supply chain risk analysis at an enterprise. Results. It has been stated that key risk factors can be controlled through risk monitoring. External and internal risks that may cause shocks and disruptions to the supply chain have been analyzed. It has been determined that the presented approach to risk assessment complements the methodology for risk assessment and monitoring. It has been established that supply chains are exposed to elevated risk, which can be controlled through the use of the risk matrix procedures. It has been proven that the critical risk areas within supply chains are external crises, environmental uncertainty, supply chains relations and production, while the most hazardous risks within supply chains are associated with external conditions beyond the control of supply chain participants. Conclusions. The growing impact of risk on the activity of the enterprise emphasizes the importance of processes that are intended to reduce the probability of supply chain risk. The presented study attracts attention to the process of risk monitoring, which, if neglected, contributes to the catastrophic consequences of the supply chain collapse. Summing up, it is possible to draw the following conclusions. 1. Supply chains are being exposed to high risk, which can be controlled through risk matrix procedures. 2. The conducted analysis has demonstrated that the critical risk areas in supply chains are external crises, environmental uncertainty, supply chain relations and production. 3. The most hazardous risks in supply chains are associated with external conditions that are beyond the control of supply chain participants. 4. Awareness of a risk and the possibility of classifying it on a risk matrix is a considerable aid to a simpler threat assessment, which may prove useful in practice.
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Choi, Dongyeop, and Yongwon Seo. "Development of Media Text Analysis Based Supply Chain Risk Monitoring System." Korean Production and Operations Management Society 34, no. 4 (2023): 453–71. http://dx.doi.org/10.32956/kopoms.2023.34.4.453.

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Recently, companies are exposed to various supply chain risks such as intensified trade conflicts, epidemics, economic and geopolitical uncertainties, and natural disasters. Thus there is increasing importance in monitoring information related to supply chain risks. Analyzing real-time media texts, such as news articles, can be utilized for monitoring up-to-date information supply chain risks. However, researches regarding analyzing supply chain risk related text are in early stages, and researches to apply modern AI techniques such as deep learning-based natural language processing to supply chain risk texts are scarce. This study aims to develop a supply chain risk monitoring system that monitors and extracts information related to supply chain risks by analyzing news articles. To collect supply chain risk related articles a filtering model based on KoBERT is developed, of which risk types are identified based on LDA topic modeling to be utilized as the train data. To predict news articles’ risk types, two deep learning- based risk classification models are developed using BOW(Bag of Words) and KoBERT. The results showed high accuracy of KoBERT based model in filtering supply chain risk-related articles, and in the classification of supply chain risk types also KoBERT based model showed better performance than BOW based model.
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Tieman, Marco. "Halal risk management: combining robustness and resilience." Journal of Islamic Marketing 8, no. 3 (2017): 461–75. http://dx.doi.org/10.1108/jima-06-2015-0041.

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Purpose The purpose of this paper is to introduce a supply chain view of a robust and resilient halal brand. In this conceptual paper, a risk prevention-mitigation-recovery cycle is proposed. Design/methodology/approach This paper builds further on previous work published in the Journal of Islamic Marketing on Islamic branding and halal supply chain management. Hypotheses are developed on the intensity of risk management. Findings Integrity of halal products is becoming an increasing concern for governments and industries. Three halal supply chain risk cycles are proposed: (1) risk prevention: risk vulnerability assessment, supply chain (re)design, vertical and horizontal collaboration, monitoring; (2) risk mitigation: investigative audits, cross-functional team, risk mitigation and communication plan, monitoring; and (3) risk recovery: risk recovery and communication plan, resume operations, maintain employee support, review risk mitigation and recovery plans. Research limitations/implications This conceptual paper proposes three halal supply chain risk cycles to better organise risk management in halal supply chains. However, more empirical research on halal risk management is needed to validate these risk management cycles. Practical implications To better protect halal brands and corporate reputation, there are evident benefits of extending halal assurance towards the supply chain, for which prevention-mitigation-recovery cycles are proposed. Originality/value As halal is going through an evolution, towards a halal supply chain and value chain, halal-certified brands need better protection. It is the first study investigating halal risk and reputation management for halal-certified brands.
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Qian, Cheng, and Anna Arkadievna. "Stability And Risk Management of Global Supply Chains in Foreign Trade Economy." American Journal of Economics and Business Innovation 3, no. 1 (2024): 50–55. http://dx.doi.org/10.54536/ajebi.v3i1.2362.

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This article provides an in-depth analysis of the key role of global supply chain stability in the international trade economy and the core role of efficient risk management in this process. Driven by the wave of globalization, supply chains have become a key link connecting the economies of various countries. This article provides a comprehensive analysis of the current status of global supply chains and an in-depth exploration of the many factors affecting supply chain stability, including supplier reliability, logistics system efficiency, demand forecast accuracy, and inventory management effectiveness. It further delves into many aspects of supply chain risk management, including risk identification, assessment, mitigation and monitoring. Analyze and formulate contingency plans for emergencies as well as regular monitoring and evaluation strategies and measures to improve the effectiveness and value of risk management. Finally, this study emphasizes the importance of supply chain stability and efficient risk management in the global foreign trade economic system, and provides suggestions for future research directions and possible improvement strategies. This research has far-reaching significance for enhancing the transparency, resilience and sustainability of global supply chains, and is crucial to the stable development of the global economy.
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Lee, Jong-Jun, and Choong-Bae Lee. "Supply Chain Risk Factors on Resilience Enhancement Strategies and Supply Chain Performance." Korean Academy Of International Commerce 39, no. 1 (2024): 81–103. http://dx.doi.org/10.18104/kalc.2024.39.1.81.

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Purpose: This paper presents the implications of resilience-strengthening strategies by analyzing a resilience strengthening strategy as a supply chain risk factor and its impact on supply chain performance. Research design, data, and methodology: A research model is constructed to empirically analyze the significance of the relationship between risk factors of a supply chain and promoting factors of resilience, as well as the relationship between promoting factors of resilience and corporate performance. Questionnaires were distributed to and collected from companies, and hypotheses were tested through structural equation modeling. Results: Supply chain agility has a positive effect on a company’s financial performance. Robustness has a negative effect on financial performance, but neither agility nor robustness appear to have a significant effect on non-financial performance. Conclusions: Companies should seek sustainable growth and enhanced performance by improving agility and robustness in their supply chains and by strengthening their risk management strategies. Measures include establishing and monitoring risk management, diversifying the supply chain, strengthening flexibility and agility in the supply chain, strengthening cooperation and partnerships, and utilizing technology.
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Tsang, Y. P., K. L. Choy, C. H. Wu, G. T. S. Ho, Cathy H. Y. Lam, and P. S. Koo. "An Internet of Things (IoT)-based risk monitoring system for managing cold supply chain risks." Industrial Management & Data Systems 118, no. 7 (2018): 1432–62. http://dx.doi.org/10.1108/imds-09-2017-0384.

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PurposeSince the handling of environmentally sensitive products requires close monitoring under prescribed conditions throughout the supply chain, it is essential to manage specific supply chain risks, i.e. maintaining good environmental conditions, and ensuring occupational safety in the cold environment. The purpose of this paper is to propose an Internet of Things (IoT)-based risk monitoring system (IoTRMS) for controlling product quality and occupational safety risks in cold chains. Real-time product monitoring and risk assessment in personal occupational safety can be then effectively established throughout the entire cold chain.Design/methodology/approachIn the design of IoTRMS, there are three major components for risk monitoring in cold chains, namely: wireless sensor network; cloud database services; and fuzzy logic approach. The wireless sensor network is deployed to collect ambient environmental conditions automatically, and the collected information is then managed and applied to a product quality degradation model in the cloud database. The fuzzy logic approach is applied in evaluating the cold-associated occupational safety risk of the different cold chain parties considering specific personal health status. To examine the performance of the proposed system, a cold chain service provider is selected for conducting a comparative analysis before and after applying the IoTRMS.FindingsThe real-time environmental monitoring ensures that the products handled within the desired conditions, namely temperature, humidity and lighting intensity so that any violation of the handling requirements is visible among all cold chain parties. In addition, for cold warehouses and rooms in different cold chain facilities, the personal occupational safety risk assessment is established by considering the surrounding environment and the operators’ personal health status. The frequency of occupational safety risks occurring, including cold-related accidents and injuries, can be greatly reduced. In addition, worker satisfaction and operational efficiency are improved. Therefore, it provides a solid foundation for assessing and identifying product quality and occupational safety risks in cold chain activities.Originality/valueThe cold chain is developed for managing environmentally sensitive products in the right conditions. Most studies found that the risks in cold chain are related to the fluctuation of environmental conditions, resulting in poor product quality and negative influences on consumer health. In addition, there is a lack of occupational safety risk consideration for those who work in cold environments. Therefore, this paper proposes IoTRMS to contribute the area of risk monitoring by means of the IoT application and artificial intelligence techniques. The risk assessment and identification can be effectively established, resulting in secure product quality and appropriate occupational safety management.
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LEPEYKO, Tetyana, and Adnane MERZOUGUI. "INTEGRATING SUPPLY CHAIN RISK MANAGEMENT TECHNOLOGY INTO ENTERPRISE MANAGEMENT SYSTEM." MODELING THE DEVELOPMENT OF THE ECONOMIC SYSTEMS, no. 4 (December 28, 2023): 181–88. http://dx.doi.org/10.31891/mdes/2023-10-24.

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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. &#x0D; 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. &#x0D; 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.
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Dvaipayana, Made Arya Teguh, Iphov Kumala Sriwana, and Yudha Prambudia. "Design of supply chain risk mitigation system using house of risk and Fuzzy AHP methods in precast concrete." SINERGI 28, no. 1 (2023): 93. http://dx.doi.org/10.22441/sinergi.2024.1.010.

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Today's global supply chain has many risk factors. These risks include supply disruptions, supply delays, demand fluctuations, price fluctuations, and exchange rate fluctuations. Risks that arise and cannot be mitigated properly in the supply chain can disrupt the company's business processes in various sectors. Companies in the construction sector when working on construction projects face many risks during the project cycle, especially risks in the supply chain process. Partial risk management, namely only on construction projects and not specifically on the supply chain process, causes potential risks in the supply chain process not to be identified in detail, and mitigation strategies cannot be determined effectively for risks in the supply chain. This research was conducted to identify risks and determine appropriate mitigation strategies using the house of risk as a framework and a fuzzy analytical hierarchy process weighting method to select the best mitigation strategy. The research results showed that there were 26 risk events and 21 risk agents identified, and the 5 best mitigation strategies were chosen from the 10 formulated strategies for a mitigation monitoring system. Based on research results, the best risk mitigation strategy can be used as a reference for risk mitigation actions in the company's supply chain as outlined in the form of a dashboard monitoring system.
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Dissertations / Theses on the topic "Supply chain risk monitoring"

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Hampshire, Kenneth E. "External risk monitoring and inventory sizing in supply chain disruption mitigation." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122593.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 67).<br>As AstraZeneca's product portfolio becomes increasingly complex, its supply chains must evolve in parallel. These supply chains operate in an environment of ever-present external risks such as factory fires, geopolitical disruptions and natural disasters. Such risks might manifest as disruptions which could jeopardize the health of those who depend upon AstraZeneca's life-saving medicines. Accordingly, there is a need to improve proactive planning and reactive risk decisions to maintain service levels in such an environment. This thesis presents an approach which enhances both risk planning decisions and reaction to disruptive events. The approach consists of a third party software solution to provide better supply chain visibility, increased risk awareness, and faster disruptive event notification, as well as a stochastic nonlinear optimization model to support inventory reductions. Both approaches improve risk planning decisions, while the software approach also supports reactive decision-making as disruptive events unfold. For a single brand, this thesis model shows that current risk mitigation inventory sizes across its supply chain can be reduced by over 50% while maintaining the target service level. The cost savings estimated for a reduction of this magnitude are at least $20M for one brand alone. Simultaneously, the software uncovers previously unknown sub-tier suppliers and highlights tier one dependencies. Adoption of this thesis' recommendations can improve risk planning and decisionmaking within AstraZeneca's supply chains while greatly reducing mitigation inventory costs.<br>by Kenneth E. Hampshire.<br>M.B.A.<br>S.M.<br>M.B.A. Massachusetts Institute of Technology, Sloan School of Management<br>S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
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Babková, Ivana. "Supply Chain Risk Management." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-3307.

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Práce se zabývá problematikou řízení rizika v logistických řetězcích se zaměřením na jeden konkrétní článek řetězce. Definuje základní oblasti risk managementu, jeho hlavní aspekty a systém spojitého plánování. Zabývá se bezpečností práce v pojetí EU, České republiky a Velké Británie. V aplikační části uvádí řízení rizika v jednom článku logistického řetězce, skladu poskytovatele logistických služeb ve Velké Británii.
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Yang, Nan. "Supply risks in supply chain management." online access from Digital Dissertation Consortium, 2007. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?3266705.

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Feng, Zekang, Rui He, Wen Zhu, and Fazal Amin. "Supply Side Risks Assessment of the Supply Chain : A case study of the Supply Side Risks Assessment in HUAWEI’s Supply Chain." Thesis, Linnéuniversitetet, Institutionen för ekonomistyrning och logistik (ELO), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-64872.

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Research questions 1. What kind of risks in the supply side of HUAWEI supply chain can be identified? 2. How can supply side risks of HUAWEI supply chain be assessed? 3. How can supply side risks of HUAWEI supply chain be mitigated? Purpose This paper describes supply side risks in HUAWEI in China, the types of risks identified, provides guidelines for assessment of these risks and suggestions for mitigation. Methodology In order to answer above research questions empirical data have been collected through observations, interviews at with logistics managers of HUAWEI in China, and from the official documents, annual reports and authentic web pages of the HUAWEI. Theoretical framework has been built through scientific articles, peer reviewed journals, authentic web based documents, and textbooks. The information is then assessed and analyzed, which result in conclusion and recommendations for the company. Conclusion There can be four major risks identified on the supply side. Manufacturing risk, logistics risk, information risk and inventory risk. The manufacturing risk include risks related to production, skill, and quality. The logistics risk further include delivery risk, lead time risk, and transportation risk. Production risk and skill risk are critical and they can be avoided by enhancing risk awareness, evaluating production feasibility, strengthen staff training, investing in high skills, strengthening R&amp;D, and analysis of the external environment. The quality and inbound delivery risks can be reduced through supplier inspection and establishing good supplier relations. Lead time risk and inventory risk can be reduced by vendor based managed inventory system and mass customization. Meanwhile, transportation risk can adopt risk transfer strategy. The information risk can be reduced by increasing information sharing levels and adopting modern communication technologies.
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Mokhtar, Samira. "Supply risk management in a supply chain under uncertain supply conditions." Thesis, Mokhtar, Samira (2020) Supply risk management in a supply chain under uncertain supply conditions. PhD thesis, Murdoch University, 2020. https://researchrepository.murdoch.edu.au/id/eprint/59211/.

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A disruption to the supply of input materials is one of the main threats to manufacturing supply chains. Trade wars, natural disasters, pandemics, cyber-attacks, sudden changes in cost and quality, machine breakdowns and transport accidents are among the causes of disruptions to supply chains. The supply chain is made up of several interconnected parties, where a product or service moves from raw material suppliers through to manufacturing, before its final delivery to customers. The extent and complexity of such interconnections can significantly increase the vulnerability of the supply chain system to disruptions. A disturbance to one party may propagate to other nodes and cause major disruption and financial losses for the whole supply chain. Many causes of supply disruptions are beyond the control of supply chain managers, therefore the best way to manage them is to be proactive. Supply chain managers undertake a risk management process to prepare the supply chain for mitigating the possible impacts of disruptions. Managers have several options to control their exposure to disruption risks. Two main options available are stocking material in inventory and maintaining a portfolio of suppliers. This thesis focuses on managing supply disruption risks in supply chains. It aims to assist the supply chain managers to mitigate the risk of supply disruptions and the corresponding effects these will have on profits. This thesis makes its contribution in three broad steps: (1) Development of a decision-making model to efficiently mitigate the likelihood of a supply disruption. The model determines an optimal supplier portfolio through continuous monitoring of supply risk indicators that detects early warnings of a supply disruption. Risk indicators are based on a supplier’s product price, financial and production stability, and quality. Using an integrated system dynamics and portfolio optimisation solution approach, the model assists decision-makers to rebalance their supplier portfolio in response to early changes in supply risk indicators over a planning horizon. (2) Development of an optimal inventory strategy model from the perspective of a manufacturer in a supply chain. This model aims to determine the optimal inventory strategy based on the expected supply price and product market demand over a planning horizon. The model seeks to maximise the manufacturer’s profit at the beginning of a planning horizon, rendering the inventory option as managerial flexibility to mitigate the undesirable effects of supply disruptions. (3) Development of a decision-making model to determine an optimal contracting strategy, sourcing policy and inventory management at each period to maximise the manufacturer’s profit at the beginning of the planning horizon. This third step allows for the concurrent application of managerial flexibilities to manage supply chain risks. This model adopts the view of a manufacturer in a supply chain with two suppliers. It provides the manufacturer with the optimal allocation of supplies, including an optimal long-term contract position with one supplier at the beginning of the planning horizon. The model also enables the decision-makers to find the optimal inventory strategy at each period to mitigate the effects of supply disruptions and maximise profit for the manufacturer. To develop the decision-making models in steps (2) and (3), this thesis applies a real options analysis method. An American-style option valuation method is used to solve the optimal inventory, sourcing and contracting strategy under uncertain supply price and product demand. This thesis uses a least-square Monte Carlo simulation to solve the underlying dynamic programming model. The results of the modelling in step (1) demonstrate how a supply portfolio can be developed to provide higher expected profit at a certain level of risk. They also show how the optimal decision depends on the risk propensity of the decision-maker. The results of modelling in step (2) demonstrate the conditions under which inventory flexibility is valuable to a supply chain. Results show how a higher expected supply price during a disruption period and a higher expectation of disruption, increases the value of an inventory flexibility option. Expectations of early disruptions increased the value of the inventory option. Results of modelling in step (3) show how a manufacturer can balance their inventory of supplies and a long-term contract with one supplier at the beginning of the planning horizon to maximise profit.
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Tiwari, Tarun (Tarun K. )., and Anthony Toteda. "The value of monitoring in supply chains." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112858.

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Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 45-46).<br>Logistics providers process millions of packages daily and collect an incredible amount of data from these shipments. As new sensors are added to more and more packages, companies will now have increasingly fast access to even more data. However, how will logistics companies leverage this idea of big data to generate the most business value for their customers? Using a qualitative approach by interviewing current users of real-time monitoring devices, we were able to understand how customers perceive the value added by this technology. Moreover, we scoured a significant amount of literature on sensors, the logistics industry, and upcoming technological breakthroughs. We quickly discovered that customers do not perform extensive quantitative analysis to determine the trade-offs and financial benefit of using real-time sensors in their shipping processes. Additionally, we found that customers are unwilling to analyze this big data themselves, but instead want their logistics provider to interpret the data to provide value-added services. Therefore, logistics providers should leverage all of the data they collect, instead of simply creating value when shipments become exceptions, e.g. out of temperature range. We propose using smart contracts on a permissioned blockchain to automate business processes and reduce frictions within the shipping parties and other intermediaries.<br>by Tarun Tiwari and Anthony Toteda.<br>M. Eng. in Supply Chain Management
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Zhang, Yu. "Contributions in supply chain risk assessment and mitigation." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47520.

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This dissertation develops contributions in the area of supply chain risk assessment and mitigation. In each of the three main chapters, we present and analyze a risk assessment or mitigation problem for supply chains. The first problem is to assess the impact of infrastructure disruptions on supply chain performance; the second problem is to develop an operational control approach to mitigate risks posed by uncertain events that disrupt network synchronization; and the third problem is to analyze the risk posed by an adversary seeking to use a supply chain as a weapon. Chapter II presents a methodology for assessing the excess supply chain costs that arise from a failure of or an attack on a critical supply chain infrastructure component. Different from many subjective risk assessment practices, our methodology provides a systematic approach to search for the most vulnerable supply chain components and measure the economic consequences of disruption. Modeling a supply chain using network flow models, we analyze the impact of disruption by linear programming theory, and propose an efficient assessment algorithm based on the dual network simplex method. Finally, a case study on the U.S. corn export supply chain is presented. Chapter III discusses the mitigation of risks created by transit time uncertainties in less-than-truckload (LTL) line-haul operations. Transit time uncertainty may undermine the performance of the load plan, which specifies the route for each shipment and is synchronized to reduce line-haul costs. In our study, risk assessment of a load plan is performed via a dispatch simulation under randomly generated travel time scenarios. The risk consequence is measured by the average excess operational cost, including transportation cost and handling cost. Compared to existing line-haul network models embedded within integer programming approaches for load plan optimization, the dispatch simulation can evaluate the performance of a load plan more realistically. In addition, a heuristic search algorithm based on "multi-tree pivots" is provided to obtain a cost-efficient load plan that is robust to transit time uncertainties. Chapter IV presents methodology to assess the consequence of risks which arise from the intentional contamination of a food supply chain. Different from many risk management practices, the source of risk in this problem is an intelligent adversary, e.g., a terrorist group, who intends to deliver chemical or biological toxins to consumers using the supply chain. First, a general modeling scheme based on state-space models is provided to describe the dissemination of toxin across consumed products in a food supply chain. Then, a case study based on a representative liquid egg supply chain is presented. Based on the system model, a risk assessment for different supply chain designs is performed by simulation. Moreover, an in-depth analysis is conducted to determine the worst-case consequence given an intelligent attack considering the operational characteristics of the system. The worst-case consequence tool developed is designed to be embedded within any risk assessment approach.
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Hollmann, Dominik. "Supply chain network design under uncertainty and risk." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6407.

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We consider the research problem of quantitative support for decision making in supply chain network design (SCND). We first identify the requirements for a comprehensive SCND as (i) a methodology to select uncertainties, (ii) a stochastic optimisation model, and (iii) an appropriate solution algorithm. We propose a process to select a manageable number of uncertainties to be included in a stochastic program for SCND. We develop a comprehensive two-stage stochastic program for SCND that includes uncertainty in demand, currency exchange rates, labour costs, productivity, supplier costs, and transport costs. Also, we consider conditional value at risk (CV@R) to explore the trade-off between risk and return. We use a scenario generator based on moment matching to represent the multivariate uncertainty. The resulting stochastic integer program is computationally challenging and we propose a novel iterative solution algorithm called adaptive scenario refinement (ASR) to process the problem. We describe the rationale underlying ASR, validate it for a set of benchmark problems, and discuss the benefits of the algorithm applied to our SCND problem. Finally, we demonstrate the benefits of the proposed model in a case study and show that multiple sources of uncertainty and risk are important to consider in the SCND. Whereas in the literature most research is on demand uncertainty, our study suggests that exchange rate uncertainty is more important for the choice of optimal supply chain strategies in international production networks. The SCND model and the use of the coherent downside risk measure in the stochastic program are innovative and novel; these and the ASR solution algorithm taken together make contributions to knowledge.
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MICCUCI, VALERIA CAMPOS GOMES DE SOUZA. "A PROACTIVE MODEL OF SUPPLY CHAIN RISK MANAGEMENT." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13213@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>Uma nova cadeia de suprimentos vem sendo observada nos últimos anos: focada, enxuta, flexível, participativa, contudo frágil, vulnerável. Interrupções já têm sido sentidas pelas empresas, e a sensação de insegurança tem se propagado, com questionamentos a cerca da vulnerabilidade das cadeias. Tornar as empresas resilientes aos fatores aleatórios é o que tem sido buscado nos estudos e pesquisas no mundo, principalmente pelo fato de que se tornar uma empresa resiliente é possuir uma fonte de vantagens competitivas em relação às demais. Aliando-se às pesquisas mais recentes na área de gerenciamento da cadeia de suprimentos, esta tese vem propor um modelo pró- ativo de monitoramento de riscos nos processos essenciais da cadeia de suprimentos, adaptando o modelo Reason de acidente organizacional ao modelo de integração e gerenciamento de processos de negócios de uma cadeia de suprimentos de Lambert e Cooper. Os vetores orientadores para a adaptação foram: o tripé estrutural do modelo de gerenciamento da cadeia de suprimentos proposto por Lambert e Cooper; e o modelo de segurança de aviação da Marinha do Brasil.<br>In the last years a modern supply chain is emerging: focused, lean, flexible, collaborative, nevertheless fragile and vulnerable. Since the disruptions are been perceived by companies in theirs supply chains, the perception of uncertainties and unsafeties have been diffused, and questions about the vulnerability of the supply chains have arisen. Therefore, the studies and researches in supply chain management around the world are trying to make the supply chains resilient to the random factors, mainly because to become a resilient supply chain is to be ahead of the others, getting a competitive gain. Aligning with the recent researches and studies, this thesis is proposing a proactive model of supply chain risk management. The proposed model would monitor the essential process risks along the supply chain by applying the Reason's organizational accident model to the Lambert and Cooper's model of SCM. The guide vectors used are (1) the Lambert e Cooper's conceptual framework of supply chain management model, and (2) the Brazilian navy's model of aviation safety.
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ROCHA, ANDRE LUIZ COSTA LEVASSEUR. "SUPPLY CHAIN RISK MANAGEMENT IN HIGH RELIABILITY ORGANIZATIONS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=20302@1.

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Desde os primórdios da humanidade, a logística tem sido aplicada como meio de subsistência para a sobrevivência dos indivíduos, bem como no fornecimento de recursos às tropas militares envolvidas em conflitos beligerantes, tendo ganhado relevância no meio empresarial, após a Segunda Guerra. O desenvolvimento da informática, da tecnologia da informação e a crescente competitividade suscitaram a percepção da necessidade de que os processos logísticos não mais poderiam ser desenvolvidos de modo isolado. Surge, então, o conceito de Gerenciamento da Cadeia de Suprimentos, no qual funções logísticas são integradas além das fronteiras das empresas. No entanto, nesse ambiente altamente competitivo, as empresas estão sujeitas a fatores internos e externos que propiciam riscos. Diante desse cenário de vulnerabilidades, as organizações buscam atingir a resiliência. Embora ainda seja pouco explorado, tem sido dada maior atenção ao gerenciamento dos riscos, de modo a proporcionar a proteção das cadeias às quais as empresas pertencem, o que se torna crítico no caso das Organizações Altamente Confiáveis. Assim, o presente estudo vislumbra apresentar uma metodologia de gerenciamento de risco na cadeia de suprimentos, tomando por base alguns modelos disponíveis na literatura, entre os quais o proposto por Miccuci (2008), que é baseado no modelo de gerenciamento da cadeia de suprimentos, de Lambert E Cooper (2000) e no de acidente organizacional, de Reason (1997); o modelo do Project Management Institute (PMI); o modelo proposto por Cavalcante (2010); e a norma brasileira ABN NBR ISO 31000:2009.<br>Since the beginning of humanity, logistics has been applied as a mean of subsistence for the survival of individuals, as well as providing resources to the troops warring, having gained relevance in the civil business after World War II. The developments of the computer science, the information technology, and the increased competition have raised the awareness that logistics processes could no longer be developed in isolation. Then, the concept of Supply Chain Management comes, in which logistics functions are integrated beyond the boundaries of firms. However, in this highly competitive environment, the companies are submitted to internal and external factors that lead to hazards. In this context of vulnerability, organizations are seeking to achieve resilience. Although it is still little explored, it has been given greater attention to risk management, to provide protection to the chains to which the companies belong, which becomes critical in the case of High Reliability Organizations. Thus, this study envisions to present a methodology for risk management in the supply chain, based on some models available in the literature, including the one proposed by Miccuci (2008), which is based on the model of supply chain management by Lambert and Cooper (2000) and the organizational accident by Reason (1997); the model of the Project Management Institute (PMI); the model proposed by Cavalcante (2010); and the Brazilian standard ABN NBR ISO 31000:2009.
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Books on the topic "Supply chain risk monitoring"

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Zsidisin, George A., and Bob Ritchie, eds. Supply Chain Risk. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-79934-6.

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Sigler, Ken, Dan Shoemaker, and Anne Kohnke. Supply Chain Risk Management. Auerbach Publications, 2017. http://dx.doi.org/10.4324/9781315279572.

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Helmold, Marc, Ayşe Küçük Yılmaz, Tracy Dathe, and Triant G. Flouris. Supply Chain Risk Management. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90800-3.

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Khojasteh, Yacob, Henry Xu, and Saeed Zolfaghari, eds. Supply Chain Risk Mitigation. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09183-4.

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Sodhi, ManMohan S., and Christopher S. Tang. Managing Supply Chain Risk. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3238-8.

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Zsidisin, George A., and Michael Henke, eds. Revisiting Supply Chain Risk. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03813-7.

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Khojasteh, Yacob, ed. Supply Chain Risk Management. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-4106-8.

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Sodhi, ManMohan S. Managing Supply Chain Risk. Springer US, 2012.

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Waters, Donald. Supply Chain Risk Management. Kogan Page Publishers, 2007.

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Heckmann, Iris. Towards Supply Chain Risk Analytics. Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-14870-6.

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Book chapters on the topic "Supply chain risk monitoring"

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Kliem, Ralph L. "Perform Political Risk Monitoring and Controlling." In Political Risk Management for the Global Supply Chain. Auerbach Publications, 2021. http://dx.doi.org/10.1201/9781003036241-11.

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Stampe, Lucas, and Bernd Hellingrath. "Risk Indicators and Data Analytics in Supply Chain Risk Monitoring." In Logistics Management. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85843-8_16.

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Sathyasri, B., G. Aloy Anuja Mary, C. Ambika Bhuvaneswari, K. Aanandha Saravanan, and S. Vishnu Kumar. "IOT Enabled Cloud Based Risk Monitoring System in Food Supply Chain." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-73318-5_37.

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Göllner, Johannes, Andreas Peer, Stefan Rass, Gerald Quirchmayr, and Viliam Zathurecky. "Global Supply Chain Network Risk Analysis and Monitoring for Global Cyber Defense." In Handbook of Cyber-Development, Cyber-Democracy, and Cyber-Defense. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-06091-0_33-1.

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Göllner, Johannes, Andreas Peer, Stefan Rass, Gerald Quirchmayr, and Viliam Zathurecky. "Global Supply Chain Network Risk Analysis and Monitoring for Global Cyber-Defense." In Handbook of Cyber-Development, Cyber-Democracy, and Cyber-Defense. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-09069-6_33.

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Cantoni, Beatrice. "A Risk-Based Approach for Contaminants of Emerging Concern in Drinking Water Production and Distribution Chain." In Civil and Environmental Engineering for the Sustainable Development Goals. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99593-5_1.

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AbstractProvision of safe drinking water (DW) is one of the major requisites for human health, related to four Sustainable Development Goals (SDGs) of the United Nation 2030 Agenda: SDGs 3 (Good health), 6 (Clean water and sanitation), 11 (Sustainable cities) and 12 (Responsible production and consumption). However, this is hindered by the presence, especially in highly-anthropized contexts, of contaminants of emerging concern (CECs) in DW, that may pose a risk for human health. The present study aims at developing a holistic framework to support both (i) decision-makers for CECs prioritization in DW regulation and (ii) water utilities for the selection of appropriate monitoring and treatment interventions for the optimization of DW supply system. In detail, a quantitative chemical risk assessment (QCRA), including uncertainties related to both exposure and hazard assessments, was developed. Then, it was combined with testing and modeling of CECs fate in treatment processes and in distribution network, obtaining a robust tool to achieve the above-mentioned SDGs. Graphical Abstract
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Kanagachidambaresan, G. R., and Bharathi N. "Supply Chain Monitoring." In Sensors and Protocols for Industry 4.0. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9007-1_7.

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Waters, Donald. "Supply Chain Risk." In Supply Chain Management. Macmillan Education UK, 2009. http://dx.doi.org/10.1007/978-1-137-26234-9_15.

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Wieteska, Grażyna. "Supply Chain Risk." In Managing Towards Supply Chain Maturity. Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137359667_4.

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Cai, Gangshu. "Risk-Adjusted Evaluation." In Supply Chain Finance. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56125-2_11.

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Conference papers on the topic "Supply chain risk monitoring"

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Oqbi, Manar Y., and Dhabia M. Al-Mohannadi. "Deciphering the Policy-Technology Nexus: Enabling Effective and Transparent Carbon Capture Utilization and Storage Supply Chains." In Foundations of Computer-Aided Process Design. PSE Press, 2024. http://dx.doi.org/10.69997/sct.185903.

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In response to the global imperative to address climate change, this research focuses on enhancing the transparency and efficiency of the Carbon Capture Utilization and Storage (CCUS) supply chain under carbon tax. We propose a decision-making framework that integrates the CCUS supply chain's optimization model, emphasizing carbon tax policies, with a blockchain network. Smart contracts play a pivotal role in automating the exchange and utilization of carbon emissions, enhancing the digitalization of the CCUS supply chain from source to sink. This automation facilitates seamless matching of carbon sources with sinks, efficient transfer of emissions and funds besides record-keeping of transactions. Consequently, it improves the monitoring, reporting, and verification processes within the CCUS framework, thereby simplifying compliance with regulatory mandates for net emission reductions and carbon taxation policies. By eliminating reliance on third-party verifiers, our blockchain-based CCUS system reduces verification costs and ensures reliable tracking of emissions, mitigating the risk of carbon leakage. Policymakers and stakeholders gain valuable insights to optimize the CCUS network design, specifically considering the impact of carbon tax. This study represents an advancement in sustainable practices, providing a robust tool for decision-makers engaged in climate change mitigation efforts.
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Qiu, Jianfeng. "Risk Management in A Global Supply Chain." In International Conference on Data Science and Engineering. SCITEPRESS - Science and Technology Publications, 2024. http://dx.doi.org/10.5220/0012838700004547.

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Kassim, Mohd Sallehin Mohd, Muhammad Haziq bin Rozman, and Faridah Yahya. "Frozen Food Supply Chain Monitoring with IoT." In 2025 19th International Conference on Ubiquitous Information Management and Communication (IMCOM). IEEE, 2025. https://doi.org/10.1109/imcom64595.2025.10857555.

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Lemay, Antoine, and Neeraj Katiyar. "Supply Chain Risk Analysis Via SBOM Data Enrichment." In 2025 IEEE International systems Conference (SysCon). IEEE, 2025. https://doi.org/10.1109/syscon64521.2025.11014830.

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Wei, Xing. "Research on Monitoring and Control for Supply Chain Finance Risk." In Proceedings of the 2017 5th International Education, Economics, Social Science, Arts, Sports and Management Engineering Conference (IEESASM 2017). Atlantis Press, 2018. http://dx.doi.org/10.2991/ieesasm-17.2018.118.

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Lajimi, Chokri, Amine Boufaied, and Ouajdi Korbaa. "Monitoring dynamic risk evolutions in operational flows of a supply chain." In 2015 4th International Conference on Advanced Logistics and Transport (ICALT). IEEE, 2015. http://dx.doi.org/10.1109/icadlt.2015.7136599.

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Goh, Rick Siow Mong, Zhaoxia Wang, Xiaofeng Yin, et al. "RiskVis: Supply chain visualization with risk management and real-time monitoring." In 2013 IEEE International Conference on Automation Science and Engineering (CASE 2013). IEEE, 2013. http://dx.doi.org/10.1109/coase.2013.6653910.

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Ugrinov, Stefan, Dragan Ćoćkalo, Mihalj Bakator, Mila Kavalić, and Verica Gluvakov. "Integrating environmental management into supply chain strategies." In XXI International May Conference on Strategic Management – IMCSM25 Proceedings, Bor, 30.05.2025. University of Belgrade - Technical Faculty in Bor, Bor, 2024. https://doi.org/10.5937/imcsm25227u.

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The paper examines how environmental management can be integrated into supply chain strategies while highlighting the necessity for sustainable practices in contemporary operation systems. The paper analysis focuses on essential aspects including environmental risk identification along with eco-efficiency measures and resource optimization strategies as well as regulatory compliance requirements together with stakeholder engagement methods and technological innovation processes. The paper introduces a theoretical framework organizing supply chain dimensions into four core elements with additional sub-element support to systematically improve performance and manage risks. The analysis shows the relationship between proactive risk assessment and advanced technology adoption which proves real-time monitoring and data analytics support adaptive management practices. This research examines how regulatory frameworks and stakeholder collaboration work together to increase transparency and accountability. Findings establish a base for scholarly research and real-world implementation by presenting organizational strategies that integrate economic goals with environmental preservation.
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He, Zhangwei. "Blockchain Security Risk Monitoring of Power Supply Chain Based on Fuzzy Neural Network." In 2023 IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA). IEEE, 2023. http://dx.doi.org/10.1109/eebda56825.2023.10090552.

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Li, Junyi, Yating Jin, Huiying Weng, and Wei Guo. "Research on Power Supply Chain Security Risk Monitoring based on Particle Swarm Optimization." In 2023 9th Annual International Conference on Network and Information Systems for Computers (ICNISC). IEEE, 2023. http://dx.doi.org/10.1109/icnisc60562.2023.00060.

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Reports on the topic "Supply chain risk monitoring"

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Butler, Anthony, José Fernando Moreno Gutiérrez, Carlos León, and Kimmo Soramäki. Liquidity-Saving Mechanisms in Trade Credit Networks: Optimising Corporate Liquidity. FNA, 2023. http://dx.doi.org/10.69701/rthh6385.

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We suggest a similar approach to mitigate liquidity and counterparty risks in trade credit networks. By introducing a new Financial Market Infrastructure (FMI) that runs LSMs in trade credit networks, we can reduce the outstanding exposures among firms, reduce the payment terms, and mitigate potential risks arising from undesirable network and feedback loop effects. This way, by implementing LSMs, risks and potential amplification effects from trade credit exposures are mitigated while their potential contribution to firms’ growth, supply chain resilience, and economic activity is preserved. Besides, as this implementation of LSMs requires observing the trade credit network, new data for monitoring and policy-making is available for central banks and financial authorities.
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Wagner, Jesse, Laura Koepfler, and Jonathan R. Treadwell. Supply Chain Disruption Monitoring Programs. Agency for Healthcare Research and Quality (AHRQ), 2025. https://doi.org/10.23970/ahrqepc_mhs4supply.

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McWhite, Rebecca. NIST Cybersecurity Supply Chain Risk Management:. National Institute of Standards and Technology, 2024. http://dx.doi.org/10.6028/nist.sp.1326.ipd.

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Carter, Charles L. Intelligence Support to Supply Chain Risk Management. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada562495.

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Tabarias, Jason. When does industrial policy reduce supply chain risk? East Asia Forum, 2024. http://dx.doi.org/10.59425/eabc.1723716000.

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Urban, Kelli, Jane Pusch, and Jonathan White. Managing Cyber Supply Chain Risk for Renewable Energy Technologies. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1821626.

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Boyens, Jon M. Cybersecurity Supply Chain Risk Management for Systems and Organizations. National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.sp.800-161r1.

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Organizations are concerned about the risks associated with products and services that may contain potentially malicious functionality, are counterfeit, or are vulnerable due to poor manufacturing and development practices within the supply chain. These risks are associated with an enterprise’s decreased visibility into, and understanding of, how the technology they acquire is developed, integrated, and deployed, or the processes, procedures, standards, and practices used to ensure the security, resilience, reliability, safety, integrity, and quality of the products and services. This publication provides guidance to organizations on identifying, assessing, and mitigating cybersecurity risks throughout the supply chain at all levels of their organizations. The publication integrates cybersecurity supply chain risk management (C-SCRM) into risk management activities by applying a multilevel, C-SCRM-specific approach, including guidance on development of C-SCRM strategy implementation plans, C-SCRM policies, C-SCRM plans, and risk assessments for products and services
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Eggers, Shannon. Towards a New Supply Chain Cybersecurity Risk Analysis Technique. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1877401.

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Boyens, Jon, Celia Paulsen, Nadya Bartol, Stephany A. Shankles, and Rama Moorthy. Notional Supply Chain Risk Management Practices for Federal Information Systems. National Institute of Standards and Technology, 2012. http://dx.doi.org/10.6028/nist.ir.7622.

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Boyens, Jon M., Celia Paulsen, Nadya Bartol, Kris Winkler, and James Gimbi. Case Studies in Cyber Supply Chain Risk Management: Mayo Clinic. National Institute of Standards and Technology, 2020. http://dx.doi.org/10.6028/nist.cswp.02042020-5.

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