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Post-hazard supply chain disruption: Predicting firm-level sales using graph neural network
16 references·0 citing·51 second hop
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References

  • 2012The Network Origins of Aggregate Fluctuations2,549 cited
  • 2020Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case2,407 cited
  • 2020Supply Chain Disruptions: Evidence from the Great East Japan Earthquake*1,175 cited
  • 2008GLOBAL SUPPLY CHAIN RISK MANAGEMENT938 cited
  • 2019The Economic Impacts of Natural Disasters: A Review of Models and Empirical Studies856 cited
  • 2008An Adaptive Regional Input‐Output Model and its Application to the Assessment of the Economic Cost of Katrina700 cited
  • 2019Temporal Relational Ranking for Stock Prediction563 cited
  • 2019Predicting supply chain risks using machine learning: The trade-off between performance and interpretability427 cited
  • 2019Evidence for sharp increase in the economic damages of extreme natural disasters371 cited
  • 2020A machine learning based approach for predicting blockchain adoption in supply Chain315 cited
  • 2021Fusion-Based Supply Chain Collaboration Using Machine Learning Techniques278 cited
  • 2010Supply network topology and robustness against disruptions – an investigation using multi-agent model268 cited
  • 2019Firm-level propagation of shocks through supply-chain networks259 cited
  • 2019Supply chain resilience for performance: role of relational practices and network complexities

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240 cited
  • 2019A systematic review of the research trends of machine learning in supply chain management206 cited
  • 2021A machine learning approach for predicting hidden links in supply chain with graph neural networks198 cited
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