Knowledge-based framework for automated dynamic supply chain configuration

In the supply chain management, configuration of supply chain is the most important decision in the long term and supplier selection and order allocation are the most important decision in the medium-term that are considered separately. Considering these together can overcome the sub-optimality. This paper deals with an integrated model that has two phases. In the first phase, we present a framework for supplier selection criteria in Closed Loop Supply Chain (CLSC). In addition, we define two performance levels for each supplier based on the quantity and capability of purchasing from it to be closer to real world problem. The output of this phase is the score of each supplier in each criterion in each level. In the second phase, we propose a nonlinear multi-objective mixed integer model that determines the number and location of all facilities (strategic decision), flow in each echelon of CLSC (tactical decision) and supplier selection and order allocation (hybrid decision). The objective functions maximize profit and scores of suppliers and minimize total pollution. To solve the model, we have created a transformation based on the piecewise linearization method. The mathematical programming model illustrated by a real numerical example.

Joint optimization for coordinated configuration of product families and supply chains by a leader-follower Stackelberg game

Multi-criteria decision-making techniques have been used to solve a range of real world problems in management science and specific supply chain management (SCM) problems (e.g. supply chain design and reconfiguration, purchasing, scheduling, supplier selection). The results obtained are encouraging. Nevertheless, robust approaches for solving multi-criteria supply chain problems are still in progress, and more research is needed before an effective and operational framework can be developed. The proposed approach introduces a two-phase hierarchical approach to solve a multi-criteria SCM problem integrating both strategic and tactical decisions where the supply chain is evaluated based on the supply chain operations reference model. The latter considers various metrics such as delivery reliability, flexibility, responsiveness and cost. The first phase evaluates different supply chains configurations using analytic hierarchy process. The second phase solves the network for the optimal safety stock placement using dynamic programming. The output from this two-phase process is a supply chain network configuration that has the right amount of safety stocks at the right place to absorb variability in demand.

The importance of supply chain management to business operations and social growth cannot be overstated. Today's supply chains are very different from those of a few years ago and continually change in a highly competitive climate. Investing in technology that can handle the sheer complexity of dynamic supply chain operations is necessary. Current supply chain solutions cannot completely mitigate the risks of inefficiencies at various supply chain stages. Several functional supply chain applications based on Machine Learning (ML) have appeared in recent years; however, few studies have analyzed data-driven logistics and supply chain management applications. Robotics, machine learning, and natural language processing are potential supply chain transformation enablers. This paper offers a thorough and up-to-date literature review that examines what researchers have done regarding data-driven techniques in the supply chain context and identifies what needs further exploration. We reviewed 135 research articles published between 2008 and 2022 on the Scopus database and created a classification of the research material on data-driven logistics and supply chain management. This comprehensive literature evaluation will enable researchers and business administrators to undertake innovation initiatives better and redirect money and human resource efforts.

The topic of the chapter “Additive manufacturing-based supply chain configurations” is about the implementation of additive technologies in conventional supply chains and the possible supply chain configurations that can be generated. As a guideline in the field of supply chain management, this chapter suggests designing the AM-based supply chain configuration according to the supply chain strategy decided by the focal company of the supply chain. Two questions are not fully resolved in doctrine: the first concerns the measurement of the effects of additive manufacturing implementation in conventional companies and supply chains: the second, the relationship between the total average unit cost and the production volume of additive products. In agreement with some scholars, quantitative approach to the analysis of the impact of additive technologies in companies and supply chains is recommended, and the choice of a simulation method for ex-ante assessment of pros and cons of additive technologies over conventional ones is suggested. The goal of this chapter is twofold: to demonstrate that the superiority of additive manufacturing over conventional one cannot be discussed a priori, because it must be proven quantitatively on a case-by-case basis; to support the thesis according to which additive machines can achieve economies of scale.

Supply chain management is a discipline dealing with organization, coordination, and optimization of relations within supply chains. Complexity and dynamics of supply chains are not always proportional to their reliability, and supply chain risk management becomes a very important tool in minimizing risk and uncertainties caused by, or impacting on, logistics-related activities or resources in the supply chain. Because risk modeling presents a very important segment of risk management, the paper includes a description of the main characteristics of supply chains and a model for risk assessment based on the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) methods. The main intention of the research presented here is to propose approaches based on application of the AHP and FAHP methods which are used as a tool for ranking supply chain risk categories, determining its share in total risk, and as a method for the supply chain risk assessment. The proposed approach is based on the experience and the knowledge of experts from insurance companies which are professionally engaged in the process of risk assessment, and possibility of its application is tested on a numerical example.

Implementation and adoption of new technologies are gaining the result of smooth supply chain and logistics operations. Internet of things (IoT) artificial intelligence, including data mining, intensified in all fields of life, particularly in supply chain management and operations. Blockchain technology has the capability to reform the supply chain and logistics operations management. Blockchain provides digital database solutions for all transactions across supply chain and operations management. Radio frequency identification device (RFID) is also helping technology transmit electromagnetic waves to radio-compatible integrated circuits to look after and manage the entire supply chain and logistics operations management. The Fourth Industry Revolution 4.0 refers to the automation, interconnectivity, machine learning, and real-time data that help supply chain and logistics operations management in the 21st century.

The paper presents possible solutions to small farmers in the agricultural sector in a small island setting grappling with challenges of enhancing their local industry and import substitution through a supply-demand chain framework. In 2005, Hawaiian farms produced approximately 363,200 kg of avocados. However, Hawaiian demand for these fruits required an additional 908,000 kg of avocados that were supplied through imports. At the same time, it is worth noting; almost 49% of locally produced avocados did not reach the market. These facts clearly suggest inefficiencies in the local avocado supply chain. Review of the literature on supply chain management suggests a sustainable avocado industry requires an integrated supply and demand chain management system. Hence, a modified conceptual model of supply-chain management called the Supply Demand Integrated Management (SDIM) model is proposed in this paper. Traditional supply chains contain three functional components: supply coordination, physical production and logistic management. In the new model, we propose adding R4D (Research for Development), a public good provided by the government to agricultural industries as an integral part of the supply-demand chain system. It articulates the significance of research and supply chain partnerships between small growers, industry groups, and public agencies. A well-integrated demand/supply chain in the avocado industry allows sharing of vital market information which can contribute to long-term strategic decisions that help local avocado growers increase their competitiveness against foreign imports. It also provides metrics in terms of consumer satisfaction, profitability, competitiveness, self-sufficiency, import substitution and sustainability. The SDIM model as applied to the avocado industry suggests two hypotheses relevant to the current situation. The hypotheses are: (1) There is a lack of coordination between what the farmers are growing and the chefs' (a high-end customer/buyer) preferences; (2) Forming an avocado farmer cooperative will enhance the profitability of local farmers. Survey data was collected from Hawaiian chefs and avocado farmers. Data was analysed using a Duncan multi-range test and a mathematical model, respectively, to test the hypotheses. The test revealed a lack of coordination between what the farmers are growing and buyer preferences. The results from the mathematical model suggested that formation of an avocado marketing cooperative would enhance the profitability of local farmers. Thus, the SDIM framework expands existing body of knowledge about supply chain management and provides useful information to local avocado growers that can help strengthen their supply and demand chain management.

Effective Supply Chain Management (SCM) is a pivotal issue in the dynamically changing business environment. Dynamic SCM requires integrated decision-making amongst autonomous chain partners with effective decision information synchronization amongst them. By exploiting flexibility in supply chain structures, better performance can be achieved. Similarly, by judiciously employing decision flexibility and the associated dynamic control amongst autonomous supply chain nodes, many improvements are possible. The paper presents a study on the role of different flexibility options (i.e. no flexibility, partial flexibility and full flexibility) in a dynamic supply chain model based on some key parameters and performance measures. Supply chain flexibility has significant potential and needs a greater research attention. The paper attempts to advance the knowledge of dynamic control on effective flexibility exploitation in the context of dynamic supply chains. A simulation model of a dynamic supply chain is used for this purpose. The key results are highlighted along with industry implications. Here each supply chain node involves decision-making. Based on the order and sample information available from the immediate buyers or customers, the supplier selection decisions are dynamically made. A seemingly good decision at a stage based on local information often ends up as detrimental not only to the total chain cost, but also to the total costs of the node itself. These observations are important for the designers and managers of the flexible supply chain systems to arrive at appropriate types and a judicious level of flexibility to attain significant improvements in total cost reduction. The modelling of dynamic supply chains with a focus on flexibility can offer enormous potential to the industry. This paper addresses this interesting and challenging domain.

This study aims to analyze the changes in the agrifood supply chain (AFSC) configurations in Latin America (LATAM) imposed by the markets as an effect of the COVID-19 pandemic. This paper analyzes the results of mobility trends, production rates, logistics performance, and the strategies developed by managers and decision makers of the organizations of the agro-industrial sector for supply chain configurations during the early stages of the pandemic in a food-exporting region that contributes 14% of the world’s production of agricultural and fishery products. Through a literature review of reports and scientific articles on the behavior of the pandemic published by international organizations, research centers, and researchers around the AFSC in LATAM, the impacts on logistical disruptions, configuration strategies, and disruptive technologies applied in Latin American agrifood supply chains during the lockdown are identified. As a result of this reconfiguration of the AFSC, the development of short supply chains and the digitalization of supply based on electronic commerce were the most used strategies during COVID-19 in LATAM. The results of this study show that Mexico, Chile, and Brazil maintained a prominent position as leaders in the different logistics indicators for the AFSC by developing strategies that include short supply chains and the digitalization of supplies based on electronic commerce. Finally, this study also highlights the imminent need to address new research and theories on the reconfiguration of the AFSC, which allows expanding analytical capabilities in organizations to face future risks and challenges that will enable the reconfiguration of the supply chain in the face of catastrophic scenarios such as COVID-19.

The supply chain is an extremely important and complex system, which is widely related to the social system and the management system. The hierarchical scheduling and production planning of a dynamic supply chain can enable enterprises in the supply chain to obtain, and maintain, stable and lasting competitive advantages; thus, improving the overall competitiveness of the supply chain. Simultaneously, research on supply chains is also a hotspot in system engineering. At present, research on complex supply chain systems with dual channels is insufficient, and analysis of dynamic supply chains with supply failure of goods is rare. In the epidemic era, dynamic supply chain management was affected by the epidemic and became a very challenging topic. The control of the supply chain system under the impact of an epidemic situation is particularly important. This paper focused on H∞ the fault-tolerant control of a complex supply chain system with dual channels. First, from the perspective of engineering practice and green production, we established a new green supply chain model. This supply chain model includes the dual-channel supply of goods and also considers the supply failure of goods. At the same time, production delay and supply delay are also considered in this model. Second, a supply scheduling scheme was designed through cybernetics to ensure the stability of a supply chain with dual channels under supply failure of goods, and we completed supply chain management. Finally, the effectiveness of our results was verified by specific Chinese enterprise data.

Causal Inference in Supply Chain Management: How Does Ever Given Accident at the Suez Canal Affect the Prices of Shipping Containers?

Supply chain management is struggling with a bunch of issues that appear during supply chain members coordination. Raising of supply chain complexity leads to the necessity of developing new software applications, which can be used for analysis of supply chain dynamics, storing data about it’s past and present states, predicting future behavior. This paper discusses current challenges in supply chain management and presents a model for the multi-agent framework in order to investigate supply chain dynamics.

ABSTRACTUnder globalization and economic uncertainty, enterprises optimize supply chain configurations via supply chain finance (SCF). From the perspective of supply chain governance, we use A‐share listed company data (2007–2021) and find that SCF reduces concentration and promotes diversification, especially in high‐trust, uncertain environments. When the mechanism test is adopted, the supply and demand coordination cost and the financing cost and enterprise risk of core enterprises in the upstream and downstream transaction process can be significantly reduced, and the transparency of the supply chain can be improved. These features promote the diversified supply chain configuration of enterprises and ensure supply chain security.

Currently, the concept of Internet of Things, as well as Industry 4.0 and Smart Manufacturing, are attracting considerable attention. Digital technologies and the industry’s rapid progress have stimulated enormous advances in the development of manufacturing technology. In the era of digitalization, the role of new technologies in enhancing the competitiveness of industries has become more crucial. So these novel technologies have created a new potential of supply chain risks. It mainly includes information and cybersecurity risks. The present paper aims to present a literature review through a bibliometric analysis of related works about risk management in supply chain 4.0. This study discusses the supply chain 4.0 risks. It also provides a framework about Risk management in supply chain 4.0. The suggested work is helpful for academics as well as professionals as it emphasizes the importance of implementing new methodologies of risk management in the age of intense competition. Furthermore, it presents a roadmap to confront new risks facing new interconnected and dynamic supply chains.