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The transformation of global value chains in the age of Covid-19 and Digitization.
Rösch, Anna-Lena; Härting, Ralf-Christian; Gakharia, Sopiko.
  • Rösch AL; Aalen University of Applied Sciences, Beethovenstr. 1, 73430 Aalen, Germany.
  • Härting RC; Aalen University of Applied Sciences, Beethovenstr. 1, 73430 Aalen, Germany.
  • Gakharia S; Aalen University of Applied Sciences, Beethovenstr. 1, 73430 Aalen, Germany.
Procedia Comput Sci ; 207: 2474-2482, 2022.
Article in English | MEDLINE | ID: covidwho-2159716
ABSTRACT
Almost everyone on the globe had to adjust to new conditions as a result of Covid-19 in conjunction with digitization. Contact and entry limitations damaged global business, trade and social connections. In addition, there is an increasing impact of digitization in supply chain. Regarding these disruptions current publications emphasize that global value chains are transforming to become more resilient. This study analyzes potential factors that might increase resilience in such a dynamic environment. The research is based on a quantitative empirical study to test the formulated hypotheses. The research questions were investigated trough a survey with logistics professionals. Two hypotheses were established as significant throughout the study. These are the robustness and responsiveness of global value chains, which have a substantial impact on their resilience. Both are determined direct or indirect by digital technologies. The complexity of global value chains had no discernible effect on the resilience of the system. A structural equation model is used to analyze the data's processing. This is achieved via a hypothesis model. As a result, major implications on global value chains' resilience can be found.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Procedia Comput Sci Year: 2022 Document Type: Article Affiliation country: J.procs.2022.09.305

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Procedia Comput Sci Year: 2022 Document Type: Article Affiliation country: J.procs.2022.09.305