Abstract
Risk assessment describes the overall process regarding identifying hazards and risk factors that have the potential to cause harm, analyzing and evaluating the risk associated with that hazard and determining appropriate ways to eliminate the hazard or control the risk. In the literature, lots of approaches are proposed to prioritize hazards and associated risks quantitatively. Fuzzy sets-based multi-criteria decision-making approaches are forefront that they have the ability in expressing the risks verbally based on decision-maker’s opinions and judgments. MCDA-based risk assessment approaches explain different types of uncertainties, which are generally modeled using stochastic analysis or fuzzy sets. The stochastic analysis is more suitable in modelling the probabilistic uncertainty. Therefore, in this study, a risk assessment approach using both stochastic data and subjective judgments is proposed, and a case study is also performed in a construction project. The VIKOR method is extended and a new risk assessment approach is developed where part of the data is stochastic. A three-year data is used to determine a fitted probability distribution of respected frequency. Evaluation of risks with respect to severity and probability parameters are then made by subjective judgments. In conclusion, a risk prioritization and potential action plan suggestion is performed.
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Mete, S., Oz, N.E., Gul, M., Serin, F., Celik, E. (2020). A Risk Assessment Approach Using Both Stochastic Data and Subjective Judgments. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_130
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DOI: https://doi.org/10.1007/978-3-030-23756-1_130
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