Research on Knowledge-Oriented Supply Chain Risk Management System Model

: 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.

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 beef and red meat sector in Australia is undergoing rapid change because of globalization, a highly competitive beef and red meat market (local and export). Risk management in the Australian beef and red meat supply chain has become increasingly important as companies both large and small seek to extend their global reach. It is important to manage these supply chain risks. The purpose of the conceptual paper is to present a framework for managing supply chain risk in the Australian beef and red meat industry. The supply chain risk management strategy is critical and significant to strategically support the supply chain and business success in the long run. However, little research has been conducted in the industry so far. Based on the resource-based view (RBV) approach, the firms’ capability is considered as effective tools for mitigating the supply chain risk in the real operational environment. The paper identified major types of supply chain risks in the red meat industry. The conceptual framework focuses on the relationships among the firms’ capabilities and supply chain risks. This provides insights into the supply chain risk management. Although, the study focuses on the Australian red meat industry, the proposed framework can be validated with an empirical work in different sectors. Moreover, this paper contributes to the supply chain risk management literature.

In this paper, IoT (Internet of Things) information technology has been widely applied to the supply chain risk management (SCRM). Firstly, the source of risks has been sorted out, the external and internal risks have been described in detail with the risk management of supply chain system. Secondly, the supply chain risk and case reasoning were mentioned. Finally, the work actively explored the supply chain risk management by the IoT information, such as 3G network, RFID and GPS. The research on SCRM based on IoT information contributes to the construction and improvement of supply chain informatisation.

Since the 1990s, more and more risk events of supply chain have emerged, which have caused serious consequences, and aroused extensive research attentions from domestic and foreign scholars. This article describes the definition of supply chain risk and analyzes the reasons that lead to supply chain risk. Then we summarize the general process for supply chain risk management. In the second part of this paper, we introduce one of risk management approaches, that is simple theoretical model of multi-attribute score (SMART Model), and by case study we apply the SMART model for supply chain risk management.

Operational risk management in supply chain activities is important for the successful achievement of the desired outcomes. Although it is an active area of research with an aim of improving a firm's success in its operations, a drawback of existing approaches is that they analyze it from only the perspective of events local to the supply chain. In this paper, we argue that it is also important for firms in a supply chain to consider external events as they will directly influence the internal ones and use various real-world examples of the risks in different processes of a supply chain as justification to prove our point. We then consider supply chain risk management not only as an operational research process, as do all the relevant survey papers, but a data science problem to gain deeper real-time insights for information risk management. Then, we suggest directions for future research that will assist supply chain risk managers to undertake better supply chain risk management processes.

This exploratory study provides initial directions about how risk management programmes could be assessed in a supply chain setting and discusses how such a measurement system could be designed. Measures are needed both for the management to evaluate the success of actions taken in supply chain risk management, as well as for the (supply chain) risk manager to communicate the value of his work. A number of indicators could show whether it is successful, for example, in reducing risk consequences, addressing the right risk sources and developing the right risk management processes. A central question within assessing risk management programmes is how to link risk management activities to outcomes. A tentative framework, based on a quality model, is proposed to assess the performance of supply chain risk management work. It highlights the importance of trying to capture both the capabilities of supply chain risk management and the results of the work.

Nowadays business world requires more collaboration along supply chains in order to sustain production, optimize cost structure and speed up delivery. The growing inter twist among supply chainpartners causesnumerous risks whose impacting magnitude and scope are larger than ever before. The risks are not just limited in operations any more but further extend to relationships related aspects. It demonstrates new features that we think should deserve careful investigation. Although supply chain risks and partnerships are great concerns in both academics and industry, the existing literature seldom links them together, and it echoesinadequately upon the new situations happened in the past decade. As such, this research project is made with ambition to improve the understanding of risks in the context of today’s collaborative supply chains where interorganizational linkages are strengthened through partnerships.
\nThe research project contains three studies. They constitute an integrated series subjected to the overall research objective. The first study starts with concept building and fundamental notion rethinking of risks in supply chains. We conceptualize supply chain risks into a general form in which risks are integrated into a system capable to reflect the correlation and chain effect among them. Through analytical inference and simulation it is found that the level of collaboration of partners contributes to the resilience of supply chains. It implies that partnerships can positively affect the integration of supply chain risk system, thus enhancing supply chain operations by improved ability in fault recovery.In the following two studies we are concerned with the impacts of different types of risks in supply chains upon companies’ operational performance given the effect of partnerships. The pre risk event effect and post risk event effect of partnerships are investigated in study two and study three respectively. The second study uses survey to research practitioners’ view on the role of supply chain risks and partnerships in supply chain performance. The validated sample of 162 responses reveals that the depth of partnerships imposes the most significant impact on supply chain risks and the collaboration risks are considered the top risk type that can influence supply chain performance to the most extent. The third study focuses on the negative consequence brought to the companies by supply chain risks when they have been realized. Event study is employed as the research methodology to identify and analyzethe effects of different risks under different partnerships. With respect to impact analysis, relationship risks are shown to cause the most significant loss to firm value. Moreover, deeper partnerships are found to have more negative impact on firm value resulted from relationship risks.
\nThis research project could contribute to the supply chain risk management literature by furthering the understanding of the important role of supply chain risks in enhancing the company’svalue and operational performance. The findings uncover the crucialrelationship between partnerships and supply chain risks, offering a novel view from a risk perspective to explain why an increasing number of supply chain companies are consciously engaged in partnerships nowadays. They may confer academicians and industrial practitioners with some new insights for risk management in supply chains and encouragefuture research in this area.

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.

Today’s supply chains (SC) are immersed in extremely dynamic environments, and supply chain management (SCM) has to deal with a multitude of risks. The domain of supply chain risk management (SCRM) has emerged, providing approaches on how to cope with risks in SC. However, due to increased complexity, volatility, and uncertainty, the number of risks in global SC has increased significantly. Harnessing the power of predictive analytics (PA), implemented in intelligent decision support systems (IDSS), offers huge potential in SCRM. However, research at the intersection of the domains of SCRM, PA, and IDSS is still in its infancy, and several research gaps have yet to be addressed. The paper elaborates on these research gaps by means of a systematic literature review. The results include a set of seven research questions and proposed research directions for future studies. Future research is presented with a plethora of starting points, which originate from the business perspective (i.e., the SCRM domain), the data-driven (i.e., the PA domain) as well as an IT-system perspective (i.e., the IDSS domain).KeywordsSupply chain managementPredictive analyticsSupply chain risk managementDecision support

Purpose– As global supply networks proliferate, the strategic significance of supply chain risk management (SCRM) – defined as the identification, evaluation, and management of supply chain-related risks to reduce overall supply chain vulnerability – also increases. Yet, despite consistent evidence that firm performance is enhanced by appropriate fit between strategy and context, extant SCRM research focusses more on identifying sources of supply chain risk, types of SCRM strategy, and performance implications associated with SCRM than on the relative efficacy of alternative primary supply chain risk mitigation strategies in different risk contexts. Drawing on contingency theory, a conceptual framework is proposed that aligns well-established aspects of SCRM to present a rubric for matching primary alternative supply chain risk mitigation strategies (redundancy and flexibility) with particular risk contexts (severity and probability of risk occurrence). The paper aims to discuss these issues.Design/methodology/approach– Conceptual paper.Findings– The proposed framework addresses supply chain managers’ need for a basic rubric to help them choose and implement risk mitigation approaches. The framework may also prove helpful for introducing business students to the fundamentals of SCRM.Originality/value– The framework and associated research propositions provide a theoretically grounded basis for managing the firm’s portfolio of potential supply chain risks by applying appropriate primary risk mitigation strategies based on the specific context of each risk rather than taking a “one size fits all” approach to risk mitigation. An agenda for progressing research on contingency-based approaches to SCRM is also presented.

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.

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.