The reshoring decision under uncertainty in the post-COVID-19 era

Purpose Using insights from the supply chain resilience perspective and the international business literature, this study aims to investigate the determinants of firms’ decisions to reshore manufacturing under the high levels of uncertainty brought about by the ongoing US–China trade war and COVID-19 pandemic. Design/methodology/approach The proposed conceptual framework is tested using survey data collected from 702 Taiwanese firms with manufacturing in China. The firms were drawn from a database compiled by Taiwan’s Ministry of Economic Affairs. Findings The results show that two supply chain factors (tariffs and supply chain completeness) and two non-location-bound factors (labor cost and material cost) are critical determinants of the decision to reshore under uncertainty. Originality/value This research elucidates and empirically validates several factors that influence the reshoring decision in uncertain environments. The findings provide valuable theoretical, practical and strategic insights into how firms should manage their value chains in the post-COVID-19 era.

Developing Knowledge of Supply Chain Resilience in Less-Developed Countries in the Pandemic Age

The constraints imposed by the pandemic COVID-19 increased the risks of the disruption of supply chains, bringing new challenges to companies. These effects were felt more intensely in less-developed countries, which are highly dependent on imports of products and raw materials. This study aims to assess the impact of supply chain resilience in a less-developed country (Guinea-Bissau) using complex adaptive system theory. We used a qualitative methodology through multiple case studies. Semi-structured interviews were conducted with four companies. The semi-structured script contains questions about supply chain disruptions, vulnerabilities and resilience. The main results show that the companies in Guinea-Bissau, due to their dependence on the outside world and the absence of formal, larger and more diversified supply chains, suffered serious consequences with the disruption imposed by the pandemic. It was also concluded that the more resilient the supply chain, the fewer the impacts of crisis events and that the resilience of companies at this level depends on their obtaining competitive advantages over their competitors. The main practical implications of this study are the need to formalize the supply chain, diversify the supply of services and products of companies dependent on the exterior, adopt metrics that allow for the early detection of situations of supply chain disruption, effectively manage stocks and promote proactive crisis resolution strategies. Studies on the impact of resilience on supply chains in crises are scarce, especially on companies located in underdeveloped countries.

Insights From Supply Chain Disruptions in the COVID-19 Era

The COVID-19 pandemic has created a devastating impact on supply chains. Especially, transportation disruptions, the slowdown in manufacturing, supply-demand imbalances, operational inefficiency in last-mile, and deficiencies in dealing with the crisis can be seen as main headings. This chapter aims to reveal the problems and learn lessons in these areas where significant risks are faced. During the COVID era, the need for resilient supply chains that are not affected by instantaneous changes has come to the fore. Accordingly, the second aim of the chapter is to offer solutions toward the short, medium, and long terms of the first-mile, production, and last-mile processes as enhancing the responsiveness of supply chains by the elements of supply chain resilience. This study is prepared as a review article in an exploratory approach through the supply chain literature and current practical examples. As a result of the study, digital-intensive business models, collaborative network design, and sustainability are highlighted as the main concepts to reach more resilient networks.

Graph Database to Enhance Supply Chain Resilience for Industry 4.0

Supply chain network in the automotive industry has complex, interconnected, multiple-depth relationships. Recently, the volume of supply chain data increases significantly with Industry 4.0. The complex relationships and massive volume of supply chain data can cause visibility and scalability issues in big data analysis and result in less responsive and fragile inventory management. The authors develop a graph data modeling framework to address the computational problem of big supply chain data analysis. In addition, this paper introduces Time-to-Stockout analysis for supply chain resilience and shows how to compute it through a labeled property graph model. The computational result shows that the proposed graph data model is efficient for recursive and variable-length data in supply chain, and relationship-centric graph query language has capable of handling a wide range of business questions with impressive query time.

IS YOUR SUPPLY CHAIN READY FOR THE NEXT DISRUPTION? BUILDING RESILIENT CHAINS

ABSTRACT The ability to recover from disruptions is important for organizations and supply chains. Empirical data were used to investigate factors that affect supply chain recovery from disruptions, including collaboration, visibility, flexibility, analytical orientation, and supply chain risk management. A literature review was conducted to build an online questionnaire that was applied to manufacturing firms in Brazil. This work’s statistical method includes confirmatory factor analysis and structural equation modeling. Our results indicate that a package of resilience capabilities - collaboration, flexibility, visibility, and analytical orientation - positively affect supply chain resilience. Improving such capabilities, therefore, will allow supply chains to recover better from disruptions. It was also discovered, however, that supply chains do not recover from disruptions by way of supply chain risk management alone. Mutual impacts also exist between the group of resilience capabilities and supply chain risk management.