ABSTRACT
A global pandemic of coronavirus COVID-19 affects the manufacturing supply chains significantly. This study aims to identify and evaluate the reaction of manufacturing supply chains in using the concept of double-loop learning to mitigate the disruptions induced by COVID-19 at the early stage of pandemic. A two-stage research process has been developed that firstly involves determining the learning pattern of enterprises in industrial supply chains and identifying actions taken. Then, the relationship between taking actions in the field of double-loop learning in the manufacturing supply chains and expecting a change in their market situation, and having knowledge in the field of adaptation to changes caused by the COVID-19 pandemic was examined. The study shows that there is a high level of caution in taking proactive measures in supply chains and a lack of knowledge in the field of adapting industrial supply chains to sudden disruptions caused by the COVID-19 pandemic.
ABSTRACT
A global pandemic of coronavirus COVID-19 affects the manufacturing supply chains significantly. This study aims to identify and evaluate the reaction of manufacturing supply chains in using the concept of double-loop learning to mitigate the disruptions induced by COVID-19 at the early stage of pandemic. A two-stage research process has been developed that firstly involves determining the learning pattern of enterprises in industrial supply chains and identifying actions taken. Then, the relationship between taking actions in the field of double-loop learning in the manufacturing supply chains and expecting a change in their market situation, and having knowledge in the field of adaptation to changes caused by the COVID-19 pandemic was examined. The study shows that there is a high level of caution in taking proactive measures in supply chains and a lack of knowledge in the field of adapting industrial supply chains to sudden disruptions caused by the COVID-19 pandemic. © 2022 The Author(s). Published by Vilnius Gediminas Technical University.
ABSTRACT
A global pandemic of coronavirus COVID-19 affects the manufacturing supply chains significantly. This study aims to identify and evaluate the reaction of manufacturing supply chains in using the concept of double-loop learning to mitigate the disruptions induced by COVID-19 at the early stage of pandemic. A two-stage research process has been developed that firstly involves determining the learning pattern of enterprises in industrial supply chains and identifying actions taken. Then, the relationship between taking actions in the field of double-loop learning in the manufacturing supply chains and expecting a change in their market situation, and having knowl-edge in the field of adaptation to changes caused by the COVID-19 pandemic was examined. The study shows that there is a high level of caution in taking proactive measures in supply chains and a lack of knowledge in the field of adapting industrial supply chains to sudden disruptions caused by the COVID-19 pandemic.
ABSTRACT
Background: Blockchain is a digitally managed, distributed, and decentralized ledger used to record transactions in an immutable format. Its characteristics in providing trust, transparency, and traceability make it attractive for applications where transactions are involved. Originally intended to support financial transactions, the technology has gained attention even in non-financial sectors such as health care, manufacturing, retail, and government services. Methods: For centuries, the various functions of manufacturing industries have worked based on the relationship and trust that they have with their upstream and downstream stakeholders. In addition, as the conventional factories are growing into giant gigafactories, the participation of several intermediaries further complicates the supply chain and logistics operations. Hence, the article aims to provide a comprehensive overview of the role of blockchain technology in addressing supply chain and logistics-related challenges by analyzing, organizing, and reviewing the literature. Results: The study shows that blockchain technology can transform the supply chain and logistics into secure, agile, trusted, and transparent functions. A conceptualized application scenario demonstrates the benefits of blockchain technology in providing provenance and traceability to critical products. Conclusions: In particular, a private or permissioned blockchain is suitable for multi-organizational businesses such as supply chain and logistics. In addition, IoT-blockchain integration, smart contracts, and asset tracking has immense benefits in the future.
ABSTRACT
The goal of this research is to explore solutions to recent shortages in the computer chip supply chain. The COVID-19 pandemic revealed weakness in the supply chain for computer chips. With more industries needing computer chips for their products, particularly the automotive industry, a shortage caused by shutdowns in China after the pandemic led to a rise in prices of consumer goods. In this research, we focus on the technicalities of the computer chip supply chain to find methods of preventing shortages and improving the overall supply chain to avoid future shortages. This is particularly important with the increased dependence on computer chips in products. India has shown success with its government incentives to encourage reshoring of computer chip manufacturing, so there is less dependence on other countries to obtain chips. It is recommended that the US follow India’s lead and encourage reshoring of computer chip manufacturing to reduce the likelihood of shortages in the future. © IEOM Society International.
ABSTRACT
The supply and demand shocks brought on by the Covid-19 crisis are forcing manufacturers everywhere to reassess or even reorganise their supply chains. This paper proposes a general framework that can achieve fast compositional modelling with stochastic performance evaluation process algebra (PEPA) for supply chain systems. The key feature of such a framework is the PEPA-based quantitative analysis approach which includes a new method for calculating response time based on compositional PEPA models. The framework aims to provide an efficient modelling prototype for supply chain systems while supporting accurate response time-based quantitative analysis. To our knowledge, this is the first work using process algebra-based compositional modelling to quantitatively analyse supply chain systems.
ABSTRACT
In practice, an increased interest into end-to-end visibility as a future-oriented driver and capability of resilient supply chains can be observed. However, the research in this area is in its infancy. Even less is understood about resilience and the potentials of a digital supply chain in pandemic settings. Based on an analysis of the relevant literature supplemented with the multiple case studies constructed with the use of primary data, we build a framework that could be instructive for supply chain managers seeking to manage resilience during pandemic disruptions and using digital technology. Our main methodological contributions are unlocking the value and potentials of end-to-end supply chain visibility for resilience management in the face of pandemic disruptions. We propose an associated design and implementation framework containing multiple dimensions-management, organizational, and technological. The outcomes of the article offer a conceptual guideline concerning the potentials and implementation of end-to-end visibility in the management of supply chain resilience.