Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies

【Author】 Moosavi, Javid; Fathollahi-Fard, Amir M.; Dulebenets, Maxim A.

【Source】INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION

【影响因子】4.842

【Abstract】The COVID-19 pandemic has made a significant impact on various supply chains (SCs). All around the world, the COVID-19 pandemic affects different dimensions of SCs, including but not limited to finance, lead time, demand changes, and production performance. There is an urgent need to respond to this grand challenge. The catastrophic impact of the COVID-19 pandemic prompted scholars to develop innovative SC disruption management strategies and disseminate them via numerous scientific articles. However, there is still a lack of systematic literature survey studies that aim to identify promising SC disruption management strategies through the bibliometric, network, and thematic analyses. In order to address this drawback, this study presents a set of upto-date bibliometric, network, and thematic analyses to identify the influential contributors, main research streams, and disruption management strategies related to the SC performance under the COVID-19 settings. The conducted analyses reveal that resilience and sustainability are the primary SC topics. Furthermore, the major research themes are found to be food, health-related SCs, and technology-aided tools (e.g., artificial intelligence (AI), internet of things (IoT), and blockchains). Various disruption management strategies focusing on resilience and sustainability themes are extracted from the most influential studies that were identified as a part of this work. In addition, we draw some managerial insights to ensure a resilient and sustainable supply of critical products in the event of a pandemic, such as personal protective equipment (PPE) and vaccines.

【Keywords】Supply chain disruption; Resilience; Sustainability; COVID-19; Literature review; Bibliometric and network analysis

【发表时间】2022 44713

【收录时间】2022-11-24

【文献类型】理论模型

【主题类别】

区块链治理-元分析-主题识别