ABSTRACT
The functioning of existing logistics supply chains was disrupted by the COVID-19 pandemic, the consequences of which have not been overcome yet. The crisis was caused by the termination of logistics operations as a result of lack of resources, as well as long delays in the supply of products from suppliers and logistics partners. The cardinal transformations which are taking place in the supply chains are also associated with the transition of all logistics operations to the digital environment. The purpose of the study is to develop a strategy for the formation of a sustainable supply chain that more comprehensive responds and effectively overcomes external influences. Redesigning of the global network, setting of the new parameters for supply chain buffers, and proactive supplier's management are aimed to overcome external influences. Rapid response to emerging logistics chain failures is achieved through end-to-end supply management, the use of an artificial intelligence-based risk management system, and planning based on forecasting, modeling and scenario development. The application of the proposed strategy for the creating of a sustainable supply chain will improve the level and quality of customer service, increase the revenue and reduce risks through the cost savings. The developed strategy for the formation of a sustainable supply chain will allow not only to monitor ongoing processes at any time, but also to correct possible changes in order to maintain the sustainability of the supply chain. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The functioning of existing logistics supply chains was disrupted by the COVID-19 pandemic, the consequences of which have not been overcome yet. The crisis was caused by the termination of logistics operations as a result of lack of resources, as well as long delays in the supply of products from suppliers and logistics partners. The cardinal transformations which are taking place in the supply chains are also associated with the transition of all logistics operations to the digital environment. The purpose of the study is to develop a strategy for the formation of a sustainable supply chain that more comprehensive responds and effectively overcomes external influences. Redesigning of the global network, setting of the new parameters for supply chain buffers, and proactive supplier’s management are aimed to overcome external influences. Rapid response to emerging logistics chain failures is achieved through end-to-end supply management, the use of an artificial intelligence-based risk management system, and planning based on forecasting, modeling and scenario development. The application of the proposed strategy for the creating of a sustainable supply chain will improve the level and quality of customer service, increase the revenue and reduce risks through the cost savings. The developed strategy for the formation of a sustainable supply chain will allow not only to monitor ongoing processes at any time, but also to correct possible changes in order to maintain the sustainability of the supply chain. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The article considers the impact of migration processes on the GDP per capita. Numerous studies examine the reasons for changes in the vector of migration policy and indicate various factors of migration influx rate. However, the most recent observations indicate an almost stagnant migration flow being affected by the COVID-19. As a result of the ongoing impacts, the requirements for the quality of human capital will be changed completely, and the volume of GDP will be decreased. As examples of two countries, Germany and Great Britain, having different migration policy approaches, authors analyze the importance of migration flows. Based on this fact, the authors suggest that migration processes can be one of the statistically significant factors affecting GDP per capita. It also can be used in the building of mathematical forecasting models. Analyses of variance (ANOVA) method is used to test the hypothesis. The linear regression is used to build models and show how factor influences the linear approximation. As a result, the hypothesis of the impact of the migration flows on GDP per capita was confirmed with the econometric models' support and their indicated explanatory abilities. Inflation and unemployment rates were considered as complement factors. The results of the models allow predicting migration policy based on migration quotas. (C) 2021 Published by European Publisher.