Journal ArticleUnknown
An assessment of probabilistic disaster in the oil and gas supply chain leveraging Bayesian belief network
Authors
Author Affiliations
Rajshahi University of Engineering and Technology, Mississippi State University, Decision Sciences (United States), Michigan State University
Published InInternational Journal of Production Economics
Year2021
Citations90
Abstract
The oil and gas supply chain (OGSC) is considered to have one of the most significant stakes in the U.S. economy because of its interconnectedness with supply chains in other sectors, such as health and medicine, food, heavy manufacturing, and services. While oil and gas development is expanding exponentially, various factors ranging from man-made to natural disasters can hinder OGSC processes, which, in turn, can result in inefficient and costly operations in other sectors. This study presents a Bayesian Network (BN) model to predict and assess disasters in the OGSC based on seven main factors: technical, economic, social, political, safety, environmental, and legal. BBN is a probabilistic graphical model that is predominantly used in risk analysis to illustrate and assess…
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Fields & Keywords
Social SciencesDecision SciencesStatistics, Probability and UncertaintyRisk and Safety AnalysisOccupational Health and Safety ResearchSupply Chain Resilience and Risk ManagementRisk analysis (engineering)Environmental economicsIndustrial organizationOperations researchMarketingArtificial intelligenceMeteorology