Analysis of Supply Chain Super-Network Coordination Considering Risk Function in Emergencies

The supply chain (SC) network is prone to disturbance due to various uncertainties associated with their subsystems. The COVID-19 outbreak has exposed the global vulnerability of the supply chain network. The current pandemic has severely affected almost every SC network because its members are situated at the international level. One of the reasons for SC network failure is the deterministic assumptions of different parameters. A realistic SC network model requires the use of the uncertain value of the parameters, which can be further captured by fuzzy numbers. This paper discusses the possibilistic moment of several nonlinear types of fuzzy numbers that are important for SC network modeling. We give closed-form possibilistic moments’ expression for various types of fuzzy numbers that are very similar to the moment’s properties in probability theory and stochastic process. We then illustrate the application of proposed fuzzy numbers by solving an inventory model. This paper also provides results related to the EPQ inventory model in a fuzzy possibilistic setup.

Firms source goods and services in complex, global supply chains. The network structures of these far‐reaching supply chains are believed to influence both firm‐level and supply chain‐level behavior. However, researchers and managers are challenged to manage extended supply chain networks because firms typically do not actively oversee their entire supply chain network. The extant research on the underlying network topologies is limited and relies on untested structural assumptions. This study addresses the latter issue by examining structural topologies in supply chain networks. We draw from the network and supply chain literature and empirically investigate the presence of topologies found in complex networks. In particular, we look for: small‐world, scale‐free, community, and hierarchical network structures. We study 21 extended (five‐tier) supply chain networks of firms representing various industries. Our analysis provides evidence for community, scale‐free, and hierarchical structures within the observed supply chain networks. The identification of network topologies is relevant to understand how to study supply chain networks and provide insights into network behavior and performance.

Since the onset of Supply chain management has gained maximum recognition, with many countries elevating supply chain levels at the strategic level. This article selects AH Company’s supply chain network as the research object, analyzes the main challenges faced by the company in the supply chain aspect, and evaluates its original supply chain network. It incorporates sustainable development factors into the current global supply chain management theme, taking into account four aspects: total supply chain cost, service level, corporate sustainable development vision (carbon emissions), and supply chain risks. The “Supply Chain Guru X (2022)” software is applied to propose optimization solutions for existing problems on the basis of the original supply chain network. Based on the existing data, a comprehensive comparison of the advantages and disadvantages of various optimization schemes is implemented to select the current optimal supply chain network optimization scheme. In the process of optimizing the plan, the multi-objective optimization theory and big data processing technology were emphasized, and the corresponding technical theories were integrated into the “Supply Chain Guru X (2022)” software. By optimizing the supply chain network of AH Company, the overall operating costs of the company’s supply chain network have been significantly reduced while meeting customer needs. Concurrently, it can provide a good example for optimizing the supply chain network of similar enterprises.

Cloud computing services are growing and developing at a rapid pace. The growth of cloud services is taking place in various forms that are suitable for various applications. Cloud computing as a computing service caters to the needs of various applications by providing a distributed environment for computing services. The services are useful in managing various engineering and management processes in the supply chain network (SCN). A supply chain network is encapsulated with challenges related to capital costs, operational costs, timely availability of information, management information system and overhead costs. Cloud computing services offer services that helps in minimizing the problems related to the challenges faced and thereby increases the productivity of the supply chain network. The supply chain firms can benefit from cloud services by way of reduced capital expenditure and reduced operational costs. Supply chain firms can be decentralized units which can utilize fog computing in which data and applications are distributed logically between data points and cloud. Also, emerging concepts of mist computing can be helpful wherein the system architecture pushes the processes nearer to the data source in a supply chain network. The expenditure mainly is because of the operational cost which can be minimized by suitable deployment of cloud computing service. The cloud services are available today as metered services thereby the operational cost can be reduced by regulating the usage. Cloud computing services from Microsoft, Google, and Amazon are already available at reasonable rates and many services providers are entering the market to pose more competition which is healthy for users from reduced pricing. It can be expected that with the developments in cloud services, the service charges will decrease which will be a great advantage to the supply chain network firms and other related firms. A supply chain network enabled with cloud computing services is referred to as the Cloud Supply Chain Network (CSCN). In this paper, the benefits and opportunities of cloud supply chain network along with the challenges faced by the firms are discussed. Firms while planning to adopt cloud services to enhance their supply chain network processes look for budgeting plans which can be determined using functions as discussed in this paper. The perspectives, principles and practices in cloud supply chain network are detailed. It also describes how one can consider the parameters of the characteristics of cloud computing in supply chain network for the purpose of modeling and analyzing the information flow. A framework of the design factors of cloud supply chain is explained which will enable the decision maker to derive the necessary results by suitably incorporating the factors in the analysis of cloud supply chain network.

During the past decade, great studies have been made in the development of standardized tools for supply chain modeling and network optimization Network optimization is the most basic type of modeling that can be performed with tools which helps to identity optimum paths or flow of goods in supply chain network. In this case, the network is defined by the flow of finished goods from origin to destination. Network modeling becomes more complex as the dimensions and scope of the supply chain expand Uncertainties in the supply chain usually increase the variance of profit or cost to the company, increasing the likely hood of decreased profit i.e. increase in total supply chain cost. Demand uncertainty and constraints posed by the every echelon are important factors to be considered in the supply chain design operations. This chapter specifically deals with the modeling and optimization of a three echelon supply chain network architecture using new Particle Swarm Optimization algorithm.

COVID-19 pandemic is the worst humanitarian crisis that economies across the globe have witnessed. Forced lockdowns, social distancing, and restricted mobility have contributed to large scale disruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting global supply chain and evaluate strategies for risk reduction in the supply chain network by making it resilient.Our study incorporates multi-criteria decision approach using Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) to analyze factors that affected the supply chain networks with the onset of COVID-19. The AHP method enabled to hierarchically rank the factors based on the relative weightage while DEMATEL ascertained the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the cost–optimization as the most significant factor and the human resource management as the least important factor in reducing vulnerabilities of the supply chain network. Our analysis from DEMATEL approach indicate that government support is a significant causal factor which can effectively eliminate the issues plaguing supply chains during this pandemic. The results from our study aim to help policymakers in developing a risk resilient framework that can enhance performance and operational capability of the supply chain, thereby ensuring sustainability and socio-economic well-being of all the stakeholders involved in the entire network.

Using modeling approach of the complex network to construct a supply chain network model, this paper has mainly studied the problem of disruption risk control of supply chain under the background of globalization. The simulation result of the supply chain network model showed that the supply chain network is scale-free. The key nodes in the supply chain network can be identified by calculating the centrality of the nodes. Detailed results demonstrated that the ability of resist disruption risks and the network resilience of a supply chain can be improved by adding redundancy of the supply chain network and keeping a high level of collaborative working of the key suppliers.

Designing a responsive-sustainable-resilient blood supply chain network considering congestion by linear regression method

PurposeThis study explores how factors arising from supply chain (SC) network and complexity work together in supply chain learning (SCL) behavior.Design/methodology/approachFuzzy set qualitative comparative analysis, which is an emerging configurational analysis method, was adopted to examine the complex combination of five influencing factors. The data were collected using a two-stage survey. First, the authors selected seven typical firms with an awareness of SCL. Second, questionnaires were sent to the partners of the seven selected firms, and 156 valid questionnaires were obtained from 76 firms.FindingsDrawing on emergent insights from the initiative, the authors find that multiple configurations of SC network and complexity lead to high SCL. Specifically, weak ties are necessary conditions of such learning, while strong ties are also conducive to this. Moreover, a moderate SC complexity is conducive to SCL.Practical implicationsThis study enriches the understanding of SCL and provides new insights for SC management practitioners to take measures to improve it.Originality/valueThis study addresses the lack of in-depth understanding of the antecedent conditions of SCL in the literature. It establishes an integrated and comprehensive theoretical framework of such learning based on contingency theory. Additionally, this study incorporates ambidextrous SCL (i.e. creation capability and dispersion capacity). An overall prototype of SCL capability is proposed on SC network and complexity theory.

The construction industry is an industrial sector that is complex and dynamic. As a developing country, Malaysia recognizes building as one of the main contributors to the economy of the country. Hence, being one of the economic drivers, the construction industry needs to ensure it remains important and competent by venturing successful strategies applied by other sectors. The implementation of supply chain management, especially in the manufacturing sector, has been positive and has produced the expected benefits such as cost reduction, competitive advantages, improved productivity, value creation and better relations between parties. This study aims to review reported outcome on Bumiputera contractors’ supply chain network. Additionally, this study also intent to analyse the main categories of risk that affect the Bumiputera contractors’ project performance which related to their approach on supply chain management. Current research papers on relevance to the issue were critically reviewed. The results from the structured literature review managed to identifies that supply chain is not used extensively among the Bumiputera contractors. Additionally, risks associated with the supply chain network in construction industry can be further categorised into external and internal factors such as cooperative risk, financial risk, technology risk and economic risk. The result have aspired a better understanding between the supply chain management with sustaining project performance among Bumiputera contractors. This study is a part of an on-going contract research with the overall aim to model supply chain network using risk parameters which will be identified at later stage of this research.

An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks

As necessities in people's lives, the stability and quality safety of the production and circulation of agricultural products are widely of concern to the whole society. With the development of economic globalization, networking and informatization, the structure and dynamic behaviour of the agricultural product supply chain are becoming increasingly complex. A concept increasingly central to supply chain theory is sustainability. As the frontier of network science, complex network theory provides a new method to study complex real networks. This paper adopts the complex network theory to explore the formation and evolution mechanism of the agricultural product supply chain network and the risk propagation mechanism on the supply chain network through modelling and simulation. On this basis, it proposes the control strategy of risk propagation. The research in this paper can enrich the results of complex network theory in the field of supply chain based on ecological theory. The network model construction can reveal the formation and evolution mechanism of the agricultural product supply chain network. The analysis of risk dynamics can provide a theoretical basis and practical guidance for controlling risk propagation of agricultural product supply chain networks.

One of the main topics discussed in a supply chain is the production-distribution problem. Producing and distributing the products plays a key role in reducing the costs of the chain. To design a supply chain, a network of efficient management and production-distribution decisions is essential. Accordingly, providing an appropriate mathematical model for such problems can be helpful in designing and managing supply chain networks. Mathematical formulations must be drawn close to the real world due to the importance of supply chain networks. This makes those formulations more complicated. In this study, a novel multi-objective formulation is devised for the production-distribution problem of a supply chain that consists of several suppliers, manufacturers, distributors, and different customers. Also, a Mixed Integer Linear Programming (MILP) mathematical model is proposed for designing a multi-objective and multi-period supply chain network. In addition, grey flexible linear programming (GFLP) is done for a multi-objective production-distribution problem in a supply chain network. The network is designed for the first time to cope with the uncertain nature of costs, demands, and capacity parameters. In this regard, due to the NP-hardness and complexity of problems and the necessity of using meta-heuristic algorithms, NSGA-II and Fast PGA algorithm are applied and compared in terms of several criteria that emphasize the quality and diversity of the solutions.

The purpose of this study is to propose a methodology that reflects the impact of interest rate risk on firms in supply chain network under bank financing and trade credit and further describe how trade credit improves the impact of interest rate risk on supply chain network through a financial flow equilibrium. A mean-variance framework and a network equilibrium analysis are integrated to provide a modeling framework. The model allows for the investigation of how bank credit financing (BCF) and trade credit financing (TCF) affect the payment strategy and financial flow of interconnected firms in supply chain networks and how they are affected by interest rate risks. The optimal behavior of manufacturers and retailers is described through variational inequality. We construct a supply chain network equilibrium model and derive qualitative properties of the solution and the function that becomes assimilated to the variational inequality problem. Additionally, variational inequality is solved using the modified projection method. This study extends the research on the impact of interest rate risk on the decision in supply chain network of firms. While other studies focus on the game between banks and firms, only a few authors have made attempts to examine the game between one manufacturer and one retailer in supply chain. An effective trade credit strategy is obtained by balancing cash and credit transactions. Through the case study, we learn how to balance the capital flow effectively to improve the negative impact of interest rate risk on supply chain.

Supply Chain Performance Assessment and Supplier and Component Importance Identification in a General Competitive Multitiered Supply Chain Network Model