Strategy generation for risk minimization of renewable energy technology ınvestments in hospitals with sf top-dematel methodology
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info:eu-repo/semantics/openAccessAttribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/Tarih
2024Üst veri
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Dinçer, H., Eti, S., Yüksel, S., Gökalp, Y. ve Çelebi, B. (2024). Strategy generation for risk minimization of renewable energy technology ınvestments in hospitals with sf top-dematel methodology. Journal of Computational and Cognitive Engineering, (3)1, 58-66. http://dx.doi.org/10.47852/bonviewJCCE32021141Özet
Effective risk management plays an important role to improve renewable energy technology investments. Because of this issue,necessary actions must be implemented to effectively manage these risks. However, having high costs is the biggest disadvantage of theimplementation of these actions. Therefore, it is not financially possible to implement different strategies together. In other words, it isnecessary to identify the most important of these strategies. Accordingly, the purpose of this study is to make a priority evaluation for therisk strategies related to renewable energy technologies in hospitals. For this purpose, a new model is generated with spherical fuzzy (SF)TOP-DEMATEL technique. In this process, significant indicators are defined based on literature evaluations. In the next process, theweights of these indicators are calculated. The main contribution of this study is that a new technique is proposed by the name of TOP-DEMATEL. In this scope, the final steps of TOPSIS are integrated to the analysis process of DEMATEL to overcome criticisms forclassical DEMATEL technique. Moreover, a priority evaluation is carried out to understand the most critical risk management strategies inrenewable energy technology investments. With the help of this analysis, it can be much easier to take risk management actions withouthaving financial difficulties. It is determined that the weighting results of the criteria are quite similar for different t values. This situationidentifies that the proposed model provides coherent and reliable results. It is concluded that government support is the most importantstrategy in this context. Additionally, technological improvements also play a crucial role for this situation. It is strongly recommended thatgovernments should establish appropriate legal and regulatory frameworks to promote renewable energy projects. These frameworks canfacilitate the financing and licensing of projects and offer economic incentives such as tax incentives and subsidies.
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Journal of Computational and Cognitive EngineeringCilt
3Sayı
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