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

Decision Analytics Journal 2023年 9卷

作者： Pamucar, Dragan Sarkar, Bishal Dey Shardeo, Vipulesh Soni, Tarun Kumar Dwivedi, Ashish Department of Computer Science and Mathematics Lebanese American University Byblos Lebanon University of Belgrade Faculty of Organizational Sciences Department of Operations Research and Statistics Belgrade Serbia Symbiosis Institute of Operations Management Symbiosis International (Deemed University) Pune India FORE School of Management New Delhi India Jindal Global Business School OP Jindal Global University Sonipat India

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. © 2023 The Author(s)

关键词： input–output knowledge modeling Interval programming Pandemic Resiliency modeling Risk assessment

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