Decision Support for Dynamic Risks to Improve Supply Chain Resilience

The COVID-19 pandemic resulted in significant supply chain disruptions across many industries, with disruptions caused by both increases in demand and reductions in available supply, leading to detrimental effects that disproportionately affected vulnerable populations. Further complicating matters, the severity of the disruptions varied throughout the pandemic. It was unclear how well data-driven models could capture the variations in time and at what point(s) in time different risk mitigation actions or operational decisions would be most effective. This project examines the effect of variations in risk over time on the management of transportation and supply chain networks with the goal of creating enhanced decision support tools. In the first year, the project addresses two related tasks: (1) to develop a set of models to represent the risk factors and time elements pertinent to common supply chain risk mitigation strategies, and (2) to examine the tradeoffs between prediction accuracy and prediction lead time.

Language

• English

Project

• Status: Active
• Funding: $155110
• Contract Numbers:

  69A3552348307

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Mid-America Transportation Center

  University of Nebraska-Lincoln
  2200 Vine Street, PO Box 830851
  Lincoln, NE  United States  68583-0851
• Performing Organizations:

  University of Missouri, St. Louis

  1 University Boulevard
  St. Louis, MO  United States  63121-4400
• Principal Investigators:

  Hupman, Andrea C

  Enayati, Shakiba

  Encarnacion, Trilce

  Akenroye, Temidayo

  Li, Haitao

• Start Date: 20230601
• Expected Completion Date: 20240731
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Decision support systems; Disaster resilience; Predictive models; Risk assessment; Supply chain management
• Subject Areas: Economics; Freight Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01908399
• Record Type: Research project
• Source Agency: Mid-America Transportation Center
• Contract Numbers: 69A3552348307
• Files: UTC, RIP
• Created Date: Feb 19 2024 6:14PM