Information-driven Supply Chain During a Catastrophic Event: COVID-19 Pandemic

Author:

Safa Mahdi1,Sharma Nomita2,Zelbst Pamela1

Affiliation:

1. Sam Houston State University, Huntsville, TX, USA.

2. Department of Management Studies, University of Delhi, New Delhi, Delhi, India.

Abstract

We learn painful lessons these days about the hidden weaknesses in the supply chains, while the surge reflects a new inflection point of the COVID-19 outbreak. Healthcare experts, politicians, academics, and supply chain practitioners need to collaborate to build a reform agenda and roadmap for our humanitarian supply chain. This study aims at investigating and assessing risks on the supply chain, especially for health care supplies. The theme of the article is based on the development of an information-driven model to help in the assessment of supply chain risk. An integrative review technique has been used to analyze literature to develop prepositions for the model. The main actors of the model are supply chain preparedness, supply chain risk, supply chain response, and supply chain recovery. The findings identify that timely preparation and assessment of supply chain risk can result in accurate adoption of the practices that can not only reduce supply chain risk but also enhance supply chain recovery during any catastrophic event.

Publisher

SAGE Publications

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A comprehensive systematic review of the literature on the impact of the COVID-19 pandemic on supply chains;Supply Chain Analytics;2023-09

2. Covid-19's effect on green supply chains and environmental sustainability; innovative technologies moderation;Journal of Cleaner Production;2023-06

3. Next normal for business post pandemics: COVID-19;International Journal of Technology Management & Sustainable Development;2023-05-01

4. Barriers to supply chain performance measurement during disruptions such as the COVID-19 pandemic;International Journal of Quality & Reliability Management;2023-04-11

5. Optimization of Healthcare Problem using Swarm Intelligence: A Review;2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM);2022-12-07

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