ArticleIFAC-PapersOnLine2022
COVID-19 pandemic: Supply chain risk management by integrating Interpretive Structural Modeling and Bayesian belief network.
Article in IFAC-PapersOnLine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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0 citing papers in PubMed.
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Authors and funding
3 authors.
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Abstract
The paper proposes a theoretical framework, based on a literature review, that analyzes the links between COVID-19 impacts and supply chain risk mitigation strategies, investigating the role of digitalization as a potential key resource to improve the effectiveness of supply chain resilience. Then, the paper empirically tests the framework through a hybrid causal mapping technique using the frameworks of Interpretive Structural Modelling and Bayesian Belief Networks methods to support supply chain decision making approaches. The findings of this paper can support managers in developing simple and traciable models for assessing interdependences among supply chain disruption sources and to invest effectively in resilience strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.