An integrated interval programming and input–output knowledge model for risk and resiliency management

• Published in: Decision analytics journal Vol. 9; p. 100317
• Main Authors: Pamucar, Dragan, Sarkar, Bishal Dey, Shardeo, Vipulesh, Soni, Tarun Kumar, Dwivedi, Ashish
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.12.2023
• Subjects: Input–output knowledge modeling; Interval programming; Pandemic; Resiliency modeling; Risk assessment; Interval programming; Pandemic; Input–output knowledge modeling; Risk assessment; Resiliency modeling
• ISSN: 2772-6622; 2772-6622
• DOI: 10.1016/j.dajour.2023.100317

The COVID-19 pandemic has devastated nearly every sector of the global economy. The research seeks to examine the COVID-19 pandemic’s effects on economy and its interdependencies, specifically on mining and minerals, energy, and agriculture sectors. We propose a mathematical model by combining interval programming with input–output knowledge modeling. The input–output model illustrates how pandemic-induced perturbations in one sector spread to others. According to how susceptible they are to disturbances coming from the primary sector (e.g., mining and minerals, agriculture, or energy), a ranking of the impacted sectors can serve as an essential input for risk and resiliency management. The study also determines which sectors are anticipated to suffer significant financial losses due to the pandemic, allowing decision-makers to prioritize their investment plans in light of system-level uncertainty. We further develop four distinct scenarios and analyze the influence of the three most influential sectors on others. •Propose a mathematical model by combining interval programming and input–output knowledge modeling.•Analyze the impact of the COVID-19 pandemic on various economic sectors.•Enable decision-makers to prioritize investment planning.•Develop four distinct scenarios and analyze the influence of the three most influential sectors on others.