A Subjective Risk Analysis Approach of Container Supply Chains

After the 9/11 terrorism attacks, the lock-out of the American West Ports in 2002 and the breakout of SARS disease in 2003 have further focused mind of both the public and industrialists to take effective and timely measures for assessing and controlling the risks related to container supply chains (CSCs). However, due to the complexity of the risks in the chains, conventional quantitative risk assessment (QRA) methods may not be capable of providing sufficient safety management information, as achieving such a functionality requires enabling the possibility of conducting risk analysis in view of the challenges and uncertainties posed by the unavailability and incompleteness of historical failure data. Combing the fuzzy set theory (FST) and an evidential reasoning (ER) approach, the paper presents a subjective method to deal with the vulnerability-based risks, which are more ubiquitous and uncertain than the traditional hazard-based ones in the chains.

Risk Management Situation and Strategic Analysis of Supply Chains of Small and Medium Enterprises in Luzhou Liquor Industry Development Zone

After entering the information-based society, profound reform has happened in the business pattern of enterprises, and thecompetitive mode between traditional enterprises has been transformed into the competition between supply chains in nowadays. The liquorindustry in Luzhou is the pillar industry of economy, which involves “Luzhou Old Cellar”, “Ichiro Liquor”and other large-scale enterpriseswith well-known brands. Besides, many small and medium-sized enterprises are developing and flourishing in Luzhou. Compared with thedevelopment of large enterprises, the development of small and medium sized enterprises has more uncertainty and risks. At present, Luzhou Cityis setting about to build Huangyi into a liquor centralized zone, which is also a clusterization strategy for industry development of Luzhou liquor.For Luzhou Liquor Zone, the implementation of supply chain management of small and medium-sized enterprises can greatly reduce the cost ofenterprises and improve effi ciency of operation. The growth and development of small and medium-sized enterprises in Luzhou Liquor Zone andthe promotion of advantages of industrial clusters are closely related to the risks of the supply chain.

Corporate Social Responsibility and Shipping Supply Chain Risks

This study aims to investigate whether Corporate Social Responsibility(CSR)activities reduce supply chain disruptions by examining the impact of the Suez Canal obstruction on the Ever Given container ship in March 2021.This study conclude that the more responsible companies have higher returns and are less affected by this event than the less responsible companies;the less responsible companies have lower returns.The companies with better CSR have a lower impact on their supply chains when faced with disruptions in the supply chain.

Retailers’ Order Strategies in Transshipments in Disruption Risks of Supply Chains

This article investigates the order problem in a two-stage supply chain consisting of retail- ers, primary suppliers and backup suppliers. From retailers＇ perspectives, the optimal offering strategies in unidirectional transshipments are analyzed on the basis of disruption risks in supply chains. With a focus on retailers＇ profits, it develops the decision model of retailers＇ orders in the dual sourcing mode and in the mode of capacity options, to maximize the retailers＇ expected profits. The simulation shows that retailers＇ optimal order decisions are not correlated with the joint disruption probability in the two order modes without service constraints; retailers＇ optimal decisions are influenced by the joint disruption probability in the two order modes with service constraints, and the impact of the joint disruption probability of the primary suppliers＇ optimal order from retailers differs in the two modes. Retailers＇ order decisions in respect of backup suppliers are more sensitive to the changing volumes of transshipments. The contribution of this article is the impact of main parameters on retailers＇ decisions, providing some guidance for enterprises to make order decisions.

Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.

Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.

Evaluation of supply chain default risk based on fuzzy influence diagram

After introducing the supply chain default risk and its causes,based on the literature review of the evaluation methods of supply chain risks,a new evaluation method called the fuzzy influence diagram which combines fuzzy sets with influence diagram theory and considers the interaction among risk factors is proposed.Furthermore,an evaluation model of the supply chain default risk is established based on the research of default risk evaluation and the fuzzy influence diagram.First,the model takes the loss of risk as a valuable node,risk factors as random nodes,drawing a risk analysis influence diagram.Then,three kinds of fuzzy sets are defined,including state fuzzy sets,probabilistic fuzzy sets and a relation fuzzy matrix.Finally,by using the fuzzy algorithm to evaluate nodes,the probability of risk occurrence and the degrees of risk loss are obtained.On the basis of the model,an instance application is used to prove its utility and effectiveness.

Supply chain coordination with participators' risk bias under buy-back contract

Considering participators' risk bias,which is measured by the method of value at risk,the risk constraints in a two-echelon supply chain coordination under buy-back contract is equal to giving the order of an upper bound.With a risk-averse dominant enterprise(M)and a risk-neutral non-dominant one(R),the coordination which optimizes the supply chain under the risk constraints is achieved by a penalty mechanism L to reduce R's order.With risk-neutral M and risk-averse R,M can motivate R to increase his order by providing a risk subsidy K,and two cases are discussed.If the risk constraints of R cannot satisfy M's participation constraint to offer K,M will prefer to accept R's order to obtain a sub-optimization solution of the supply chain.Or else,with M's K,R's optimal order just coordinates the supply chain,which is equal to the case without risk bias,and in this situation R's risk bias only affects the profit distribution between the participators.

Dynamic Voting Classifier for Risk Identification in Supply Chain 4.0

Supply chain 4.0 refers to the fourth industrial revolution’s supply chain management systems,which integrate the supply chain’s manufacturing operations,information technology,and telecommunication processes.Although supply chain 4.0 aims to improve supply chains’production systems and profitability,it is subject to different operational and disruptive risks.Operational risks are a big challenge in the cycle of supply chain 4.0 for controlling the demand and supply operations to produce and deliver products across IT systems.This paper proposes a voting classifier to identify the operational risks in the supply chain 4.0 based on a Sine Cosine Dynamic Group(SCDG)algorithm.Exploration and exploitation mechanisms of the basic Sine Cosine Algorithm(CSA)are adjusted and controlled by two groups of agents that can be changed dynamically during the iterations.External and internal features were collected and analyzed from different data sources of service level agreements and transaction data from various KSA firms to validate the proposed algorithm’s efficiency.A balanced accuracy of 0.989 and a Mean Square Error(MSE)of 0.0476 were achieved compared with other optimization-based classifier techniques.A one-way analysis of variance(ANOVA)and Wilcoxon rank-sum tests were performed to show the superiority of the proposed SCDG algorithm.Thus,the experimental results indicate the effectiveness of the proposed SCDG algorithm-based voting classifier.

Supply Chain Finance Credit Risk Evaluation Method Based on Self-Adaption Weight

Credit risk is the core issue of supply chain finance. In the supply chain, problems happened in different enterprises can influent the whole to different degrees through transferring, thus statuses of all enterprises and their different influences should be considered when evaluating the supply chain’s credit risk. We examine the characters of supply chain network and complex network, use the local growing complex network to simulate the real supply chain, use cluster analysis to classify the company into several levels;Introducing each level’s self-adaption weight formula according to the company’s quantity and degrees of this level and use the weight to improve the credit evaluation method. The research results indicate that complex network can be used to simulate the supply chain. The credit risk evaluation (CRE) of an enterprise level with bigger note degrees has a greater weight in the supply chain system’s CRE, thus has greater effect on the whole chain. Considering different influences of different enterprise levels can improve credit risk evaluation method’s sensitivity.

Study on risk analysis of supply chain enterprises

The sources of supply chain enterprise risk from different aspects including material flow, information flow, cash flow and partner relationship is analyzed. Measures for risk reduction have also been summarized from the aspects of risk sharing, information sharing, change of inventory control mode, and supply chain flexibility. Finally, problems in current research on supply chain risk management are pointed out and a discussion on future research trend is presented.

Agricultural Supply Chain Risks Evaluation with Spherical Fuzzy Analytic Hierarchy Process

The outbreak of the COVID-19 pandemic has impacted the development of the global economy.As most developing and third world countries are heavily dependent on agriculture and agricultural imports,the agricultural supply chains(ASC)in all these countries are exposed to unprecedented risks following COVID-19.Therefore,it is vital to investigate the impact of risks and create resilient ASC organizations.In this study,critical risks associated with ASC were assessed using a novel Analytical Hierarchy Process based on spherical fuzzy sets(SF-AHP).The findings indicated that depending on the scope and scale of the organization,supply risks,demand risks,financial risks,logistics and infrastructure risks,management and operational risks,policy and regulatory risks,and biological and environmental risks all have a significant impact on ASC.This research highlighted that the most significant criterion is specified as Transportation(TP),followed by Market(MA)and Policy(PO),respectively.Meanwhile,Technology(TL)is the least significant criterion.The study’s findings can help managers with a holistic view of the agriculture supply chain risk mitigation.Furthermore,this study may assist managers in sharing information about the processing of agricultural products from top to bottom to manage risk in the supply chain.

Researches on Risk Evaluation of Green Agro-product Closed Supply Chain

Closed supply chain is a superior form of management model of chain supply and an effective means of improving the modernization of agro-product circulation. Based on the research results of the current literatures on supply chain risk and agro-product supply chain, related subjects of the agro-product closed supply chain involving production, management and consumption are studied and analyzed and the primary risking factors in the supply chain system are classified as environmental risk, system risk, information risk, management risk and quality risk. Risk of agro-product closed supply chain is evaluated by using the method of fuzzy comprehensive evaluation and the values are acquired. The result shows that risk of agro-product closed supply chain is moderate with relatively high risk, which basically accords with the present actual situations. It can be seen from the index weights of various levels that the key first-level indices influencing the risks are system risk, information risk, quality and safety risk and the key second-level are the coordinating and controlling ability of core enterprises, the implementation of information traceability and the construction of quality safety system. Therefore, risk of agro-product closed supply chain should be reduced by taking prevention and controlling measures mainly from these aspects.

Risk Assessment of Agricultural Products Supply-Chain Finance Based on D-S Theory

Agricultural products supply-chain finance, as one of the solutions to the issue of “capital problems” of agriculture, countryside and farmers, has proposed a kind of characteristics model to assess the risk of agricultural production, processing and marketing, which can improve the issue of farmers and enterprises lacking of funds. This model is proposed on the basis of uncertain information processing method of D-S theory and its data combination rules, combined with the “discount rate” correction model, and it includes a risk assessment index system of agricultural products supply-chain finance, fully considering the five aspects of production, processing, marketing, cooperation of supply chain and collateral. At last, a taro supply chain is taken for example. And the risk assessment of its supply-chain finance based on this model has been discussed in detail. And the result has proved that the model and its algorithm are practical and feasible.

Interaction between supply chain risk and organizational performance

To offer a theoretic guidance to practice, on the basis of the work in an emerging strand of supply chain management and by matching the constructs of performance and risk together, a framework between supply chain risk management and organizational performance is developed. The framework includes a series of mutually associated processes as follows: risk sources and profiles, risk and performance drives, risk and performance consequences, risk management responses, and risk and performance outcomes. Furthermore, every process is elaborated on in detail. Thereinto, organizational performance consists of efficiency and effectiveness which is linked to risk drivers and risk management responses. Finally, some necessary discussions and supplements are put forward from a practical point of view. This study is to some extent expected to be conducive to the theories and the practice of supply chain management for contemporary enterprises.

A Petri Net Pareto ISO 31000 Workflow Process Decision Making Approach for Supply Chain Risk Trigger Inventory Decisions in Government Organizations

The Petri Net Pareto method proposed in this study has the advantages of acting directly on computing results by assessment of workflow process information. Our study contributes to the literature because it has investigated an ISO 31000 workflow process approach to group decision making for reducing backorders in the supply chain, from an integrated perspective utilizing Pareto charts and Petri nets. The contribution to the literature is also enhanced by the L-Project illustrative example that presents an evaluation hierarchy of supply chain risk. The proposed method is appropriate for use in situations in which assessment information may be qualitative or precise quantitative information is either unavailable or too costly to compute.

A Review of Research on Risk Assessment of Fresh Agricultural Product Supply Chain

With the establishment of a well-off society in an all-round way,Chinese residents have put forward higher requirements for the quality and safety of fresh agricultural products.In recent years,domestic and foreign academic circles have also paid more and more attention to the risk of fresh agricultural product supply chain.This article collects and sorts out the research findings of domestic and foreign scholars on the risk assessment of fresh agricultural product supply chain in recent years,and summarizes and discusses from three aspects:supply chain risk factors,risk assessment indicator selection,and risk assessment methods.It is intended to provide a reference for future new research ideas and research perspectives.

Linear-contract Mechanisms Based on the Risk Preference of an Agent in a Supply Chain

With respect to different risk preference of an agent in a supply chain, linear-contract models are designed according to the principal-agent theory. The study shows that the risk preference of an agent directly correlates with the incentive compensation coefficient of principal, order quantity of principal and production capability level of the agent. The principal should offer an appropriate incentive contract according to the risk preference of the agent, or choose an agent holding a different risk preference to establish the supply chain.

Research on Risk Identification of Supply Chain Management in Pharmaceutical Wholesale Enterprises——Taking Enterprise A as an Example

Objective To study the current situation of supply chain management in pharmaceutical wholesale enterprises so that supply chain risks can be identified effectively.Methods Through the analysis of the actual situation of enterprise A,combining with the supply chain problem of the enterprise,the enterprise supply chain risks were found out.Results and Conclusion With the development of pharmaceutical circulation industry,the competition among drug wholesalers has become increasingly fierce.For enterprises,the supply chain risks are increasing,and the traditional upstream and downstream supply risks are transformed into multiple-dimensional risks.The goal of carrying out supply chain risk identification in pharmaceutical wholesale enterprises is to enable key enterprises to discover and understand different types of risks in time so as to improve the management of supply chain.