R.Graph: A new risk-based causal reasoning and its application to COVID-19 risk analysis

Autor: Hamidreza Seiti, Ahmad Makui, Ashkan Hafezalkotob, Mehran Khalaj, Ibrahim A. Hameed
Jazyk: angličtina
Rok vydání: 2022
Předmět:
SARS
Severe acute respiratory syndrome
Environmental Engineering
ANP
Analytic network process
STAMP
Systems-theoretic accident model and processes
SMIC
Cross impact systems and matrices
R.Graph
Risk analysis
General Chemical Engineering
QFD
Quality function deployment
DBN
Dynamic Bayesian network
RBA
Risk-based approach
Causal chain
GDP
Gross domestic product
Article
AR
Acceptable risk
WAA
Weighted arithmetical averaging
CIAM
Cross impact analysis model
COVID-19
Coronavirus disease of 2019
Environmental Chemistry
OECD
The organization for economic co-operation and development
HWA
Hybrid weighted averaging
MICMAC
Cross-impact matrix multiplication applied to classification
Safety
Risk
Reliability and Quality
HAZOP
Hazard and operability study
CAST
Causal analysis based on systems theory
EXIT
Express cross-impact technique
MCM
Multi-criteria based model
COVID-19
BN
Bayesian network
BM
Bayesian model
ISM
Interpretive structural modeling
OWA
Ordered weighted averaging
AXIOM
The advanced cross-impact option method
INTERAX
The acronym for the futures research process
BASICS
Batelle scenario inputs to corporate strategies
DEMATEL
Decision-making trial and evaluation
BWM
Best-worst method
SCC
Spearman’s correlation coefficient
Zdroj: Process Safety and Environmental Protection
ISSN: 1744-3598
0957-5820
Popis: Various unexpected, low-probability events can have short or long-term effects on organizations and the global economy. Hence there is a need for appropriate risk management practices within organizations to increase their readiness and resiliency, especially if an event may lead to a series of irreversible consequences. One of the main aspects of risk management is to analyze the levels of change and risk in critical variables which the organization's survival depends on. In these cases, an awareness of risks provides a practical plan for organizational managers to reduce/avoid them. Various risk analysis methods aim at analyzing the interactions of multiple risk factors within a specific problem. This paper develops a new method of variability and risk analysis, termed R.Graph, to examine the effects of a chain of possible risk factors on multiple variables. Additionally, different configurations of risk analysis are modeled, including acceptable risk, analysis of maximum and minimum risks, factor importance, and sensitivity analysis. This new method's effectiveness is evaluated via a practical analysis of the economic consequences of new Coronavirus in the electricity industry.
Databáze: OpenAIRE
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