scholarly journals Management plan: risk-analysis methodology

1978 ◽  
Author(s):  
Keyword(s):  
Risk Analysis ◽  
Management Plan ◽  
Analysis Methodology

A Common Approach to Risk Analysis Methodology

2003 ◽  
Author(s):  
J. Robert Sims
Keyword(s):  
Resource Allocation ◽  
Risk Analysis ◽  
Broad Spectrum ◽  
Analysis Methodology ◽  
Risk Ranking ◽  
Homeland Defense ◽  
Narrow Area ◽  
Allocation Decisions ◽  
Resource Allocation Decisions

Risk analysis has been used extensively to inform decisions throughout government and industry for many years. Many methodologies have been developed to perform these analyses, resulting in differences in terminology and approach that make it difficult to compare the results of an analysis in one field to that in another. In particular, many approaches result only in a risk ranking within a narrow area or field of interest, so the results cannot be compared to rankings in other areas or fields. However, dealing with terrorist threats requires prioritizing the allocation of homeland defense resources across a broad spectrum of possible targets. Therefore, a common approach is needed to allow comparison of risks. This presentation summarizes an approach that will allow the results of risk analyses based on using current methodologies to be expressed in a common format with common terminology to facilitate resource allocation decisions.

scholarly journals Risk Analysis and Community Based Disaster Management Plan of Sateek Village, Aizawl District, Mizoram, India

2019 ◽  
Vol 4 (1) ◽  
pp. 11-20
Author(s):  
C. Zoramthara ◽  
Lalthakima
Keyword(s):  
Risk Analysis ◽  
Disaster Management ◽  
Emergency Services ◽  
Secondary Data ◽  
Management Plan ◽  
Primary Data ◽  
Landslide Risk ◽  
Community Based ◽  
The People ◽  
Disaster Assessment

Sateek village is vulnerable to plenty of disasters such as earthquake, landslide, forest fire and disease outbreak. Some other features like poverty, remote area from the city, lack of hospital and other emergency services make the people of this village more vulnerable. The present study deals with the idea of community based disaster management (CBDM) and their risk assessment in Sateek village, which is located in Aibawk block of Aizawl District, Mizoram, India. The data used in this research include collection of primary data through interview, questionnaire and Secondary data. Landslide risk analysis was carried out in quantitative approach. The study seized disaster assessment, resource analysis, risk and vulnerable profile and response plan and interpretation in various disaster of Sateek village and how community based disaster management (CBDM) plan can help the people to cope with hazards.

Decision Support Model for Fire Insurance Risk Analysis in a Petrochemical Case Study

2015 ◽  
pp. 990-1004
Author(s):  
Hadis Z. Nejad ◽  
Reza Samizadeh
Keyword(s):  
Decision Support ◽  
Risk Analysis ◽  
Oil And Gas ◽  
Oil Refinery ◽  
Decision Support Model ◽  
Analysis Methodology ◽  
Damage Costs ◽  
Fire Insurance ◽  
Margin Of Error

A decision support system was researched and applied to a case study in the petrochemical industry. The participants were an insurance company underwriting the policies of oil and gas refineries located in a major oil producing nation. The Chemical Process Quantitative Risk Analysis methodology was applied as a framework to implement uncertainty quantification and risk analysis using a specialized commercial DSS software product. A gas vapor explosion was simulated at an oil refinery, to predict the fire and radiation damage. Costs and risks were entered into the model based on historical data. Loss estimates were generated for equipment and buildings located various distances (pressures) from the explosion origin. Overall, the DSS model predicted an expected loss of over $14,000,000 USD for equipment located in the 50 meter explosion radius, which represented a loss ratio of almost 52%. The losses predicted from the DSS model were comparable to the literature and to experiences of the case study company. The margin of error from the DSS model was less than ±5% which made it very reliable according to benchmarks.

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