A New Approach to the Fine Kinney Method with AHP Based ELECTRE I and Math Model on Risk Assessment for Natural Disasters

Derse, Onur

doi:10.26650/jgeog2021-875427

Cited by 8 publications

(6 citation statements)

References 20 publications

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“…It is an easy to use and numerical analysis method. It consists of the combination of three parameters: probability, exposure, and consequence, and a result is obtained by multiplying the scale values (seven for probability and six for both exposure and consequence parameters) of the three parameters numerically (Kuleshov et al 2021 ; Çınar et al 2021 ; Derse 2021 ). According to the result, actions (i.e., control measures) are put on the agenda (Gul et al 2021b ).…”

Section: Methodsmentioning

confidence: 99%

Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Gül

Yücesan

2022

Environ Sci Pollut Res

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The Fine − Kinney is a risk assessment method widely used in many industries due to its ease of use and quantitative risk evaluation. As in other methods, it is a method that recommends taking a series of control measures for operational safety. However, it is not always possible to implement control measures based on the determined priorities of the risks. It is considered that determining the priorities of these measures depends on many criteria such as applicability, functionality, performance, and integrity. Therefore, this study has studied the prioritization of control measures in Fine − Kinney-based risk assessment. The criteria affecting the prioritization of control measures are hierarchically structured, and the importance weights of the criteria are determined by the Bayesian Best–Worst Method (BBWM). The priorities of control measures were determined with the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) method. The proposed model has been applied to the risk assessment process in a petrol station’s liquid fuel tank area. According to the results obtained with BBWM, the most important criterion affecting the prioritization of control measures is the applicability criterion. It has an importance weight of about 42%. It is followed by performance with 31%, functionality with 18%, and integrity with 10%, respectively. FVIKOR results show that the “Periodic control of the ventilation device” measure is the top priority for Fine − Kinney risk assessment. “The absence of any ducts or sewer pits that may cause gas accumulation in the tank area and near the dispenser; Yellow line marking of entry and exit and vehicle roads; Placing of speed limit warning signs” has been determined as a secondary priority. On conclusion, this proposed model is expected to bring a new perspective to the work of occupational health and safety analysts, since the priority suggested by Fine − Kinney risk analysis methods is not always in the same order as the one in the stage of taking action, and the source, budget, and cost/benefit ratio of the measure affect this situation in practice. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-022-19454-x.

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Section: Methodsmentioning

confidence: 99%

Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Gül

Yücesan

2022

Environ Sci Pollut Res

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“…Derse et al developed a model for measuring natural catastrophe risk using the Fine-Kinney approach. After calculating the risk score and identifying high-risk locations during a crisis, this study employed the Analytical Hierarchy Process (AHP)-based electrification method [ 15 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment

Soltani,

Mirzaei Aliabadi

2023

Heliyon

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“…Kuleshov et al ( 2021 ) used the Fine–Kinney method to evaluate the severity of the results of an accident as one of the occupational risk components. Derse ( 2021 ) aimed to propose a risk assessment for natural disasters by using the Fine–Kinney method.…”

Section: Literature Reviewmentioning

confidence: 99%

Action selection in risk assessment with fuzzy Fine–Kinney-based AHP-TOPSIS approach: a case study in gas plant

Dogan

Oturakci

Dağsuyu

2022

Environ Sci Pollut Res

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In this study, the hazards occurring in a medium-sized gas filling facility were defined, and the risk scores of these hazards were determined by the expert team according to the Fine–Kinney risk analysis method. However, since the same risk significance score is obtained in different combinations of scale values in the classical Fine–Kinney risk analysis method and the characteristics/constraints of the company applied in the risk analysis are not taken into account, the hazards were evaluated using fuzzy Fine–Kinney risk analysis, and the most critical hazards were determined. Action plans are defined for critical hazards determined as a result of fuzzy Fine–Kinney risk analysis. Among the actions that require company resources, the action selection was performed with the TOPSIS method, taking into account their relationship with the hazards by integrating the weights, which was calculated with the AHP method, of affected groups. The effect of operating constraints is included in the last step of the study to calculate the final weights. Calculating the results by including the risk-affected groups and company constraints and ranking the actions reveals that the study is an original, objective, and applicable study.

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A New Approach to the Fine Kinney Method with AHP Based ELECTRE I and Math Model on Risk Assessment for Natural Disasters

Cited by 8 publications

References 20 publications

Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment

Action selection in risk assessment with fuzzy Fine–Kinney-based AHP-TOPSIS approach: a case study in gas plant

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