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The Application of Data-Driven Technologies to Enhance Supply Chain Resilience in the Context of COVID-19

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Advances in Artificial Systems for Logistics Engineering (ICAILE 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 82))

Abstract

The sudden outbreak of COVID-19 has wreaked havoc on global supply chains. Fortunately, digital drive technology can improve supply chain resilience. This paper is based on literature review to research the impact of COVID-19 to supply chain, to research the interplay of supply chain resilience and data-driven technology, focuses on the operation mechanism of data-driven technology (digital twin, blockchain, big data) and integration them together to enhance the resilience of supply chain. This paper try to presents an effective perspective of supply chain resilience by data-driven technology, and it can provide some reference and guidance for improving the resilience of supply chain during and after the COVID-19.

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Acknowledgment

This project is supported by Guangxi philosophy and social science planning research project(17FJY014) and Guangxi young and middle-aged teacher’s basic ability enhancement project (2018KY0744).

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Authors and Affiliations

  1. Nanning College, Nanning, 530200, China

    Zhong Zheng, Liwei Li, Liuqing Lu & Yanfang Pan

  2. King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand

    Zhong Zheng

  3. Chongqing University, Chong Qing, 400030, China

    Yun Lin

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  1. Zhong Zheng
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  2. Yun Lin
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  3. Liwei Li
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  4. Liuqing Lu
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  5. Yanfang Pan
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Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Zhengbing Hu

  2. Department of Logistics Management, Wuhan Institute of Technology, Wuhan, China

    Qingying Zhang

  3. Mechanical Engineering Research Institute of the Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  4. Halmos College of Natural Sciences, Nova Southeastern University, Plantation, FL, USA

    Matthew He

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Zheng, Z., Lin, Y., Li, L., Lu, L., Pan, Y. (2021). The Application of Data-Driven Technologies to Enhance Supply Chain Resilience in the Context of COVID-19. In: Hu, Z., Zhang, Q., Petoukhov, S., He, M. (eds) Advances in Artificial Systems for Logistics Engineering. ICAILE 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 82. Springer, Cham. https://doi.org/10.1007/978-3-030-80475-6_24

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