Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2023Scopus SJRQ1/r/munzur/3060
  COVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model

  Baskak, Dilber; Ozbey, Sumeyye; Yucesan, Melih; Gul, Muhammet

  The fight against the COVID-19 pandemic, which has affected the whole world in recent years and has had devastating effects on all segments of society, has been one of the most important priorities. The Turkish Standards Institution has determined a checklist to contribute to developing safe and clean environments in higher education institutions in Turkey and to follow-up on infection control measures. However, this study is only a checklist that makes it necessary for decision-makers to make a subjective evaluation during the evaluation process, while the need to develop a more effective, systematic framework that takes into account the importance levels of multiple criteria has emerged. Therefore, this study applies the best-worst method under interval type-2 fuzzy set concept (IT2F-BWM) to determine the importance levels of criteria affecting the “COVID-19 safe campus” evaluation of universities in the context of global pandemic. A three-level hierarchy consisting of three main criteria, 11 sub-criteria, and 58 sub-criteria has been created for this aim. Considering the hierarchy, the most important sub-criterion was determined as periodic disinfection. The high contribution of the interval-valued type-2 fuzzy sets in expressing the uncertainty in the decision-makers’ evaluations and the fact that BWM provides criterion weights with a mathematical optimization model that produces less pairwise comparisons and higher consistency are the main factors in choosing this approach. Simple additive weighting (SAW) has also been injected into the IT2F-BWM to determine the safety level of any university campus regarding COVID-19. Thus, decision-makers will be better prepared for the devastating effects of the pandemic by first improving the factors that are relatively important in the fight against the pandemic. In addition, a threshold value will be determined by considering all criteria, and it will prepare the ground for a road map for campuses. A case study is employed to apply the proposed model, and a comparison study is also presented with the Bayesian BWM to validate the results of the criteria weights.

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  AtıfScopus4·WoS3·OpenAlex2

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• MakaleYalnız künye2021Scopus SJRQ1/r/munzur/2418
  Extension of FEMA and SMUG models with Bayesian best-worst method for disaster risk reduction

  Yanilmaz, Sumeyye; Baskak, Dilber; Yucesan, Melih; Gul, Muhammet

  Turkey is one of the countries that face many natural and man-made disasters. The entire geography of Turkey is affected by these disasters and the secondary disasters resulting from them. Tunceli is located in the Eastern Anatolia Region of Turkey and is a disaster-prone region. Therefore, it is important to carry out an adaptable hazard analysis for the region and support the national disaster risk reduction struggle. In this study, a comprehensive disaster hazard analysis was conducted for Tunceli province, and potential mitigation measures were discussed. As methodological background, FEMA (Federal Emergency Management Agency) and SMUG (Seriousness Manageability Urgency Growth) models, which are well-known methods, were extended under the Bayesian Best-Worst Method (BWM). Bayesian BWM is a pairwise comparison-based multi-criteria decision-making method that takes a probabilistic view of the experts' group decision without losing information, providing less pairwise comparison and higher consistency. Nine different disaster hazards for the Tunceli region are prioritized by the proposed approach. Initially, weights of the risk parameters in FEMA and SMUG and the priority values of disaster hazards based on each parameter were calculated. Then, ranking orders were determined. In addition, more precise evaluations were made for the results obtained with the credal ranking graphs. Some comparative studies were also included in the study to test the solidity of the approach. According to the results, both models showed that the top priority hazard for Tunceli is “earthquake”. Also, flood, mass movement, terrorism, and epidemics are hazards with higher priority to be taken into account. Considering the final preference values of disaster hazards for Tunceli province, the first three hazards for the FEMA model are earthquake with 0.192, mass movement with 0.141 and flood with 0.114, respectively. In the SMUG model, earthquake with 0.194, flood with 0.129 and epidemic disease with 0.120 are in the first three places.

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  AtıfScopus35·WoS25·OpenAlex32

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