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Evaluation of Sustainable Green Building Indicators by Fuzzy Multi-Criteria Decision Making

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Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 420))

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Abstract

The relevance of the notion of sustainability today is revealed by global warming, pollution, and the depletion of water resources in a world that has become a village as a result of fast globalization. The number of buildings in which many natural resources are consumed during the construction phase and severe damage to the environment caused by the wastes generated is constantly increasing. The construction of green buildings can reduce these negativities caused by the construction. Environmental sustainability in Turkey is still in its infancy. The goal of this research is to define and rank sustainability indicators to evaluate green building production in Turkey as a tool for assessing sustainability. To evaluate green buildings, 12 criteria in four dimensions have been presented. The weights of the dimensions and criteria addressed in the assessment framework were determined using the novel fuzzy level-based weight assessment (LBWA), which can represent human reasoning. The results show that ecology and energy-saving are the most critical dimensions in evaluating green building production in Turkey while reducing waste and health are the least essential dimensions. Research output can be a valuable reference for green building builders in the country. It can serve as a guide to selecting and promoting optimal applications in green building products. In addition, the proposed framework can be adapted for countries that are similar to Turkey’s climate and environmental conditions.

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Correspondence to Gülay Demir .

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Demir, G. (2023). Evaluation of Sustainable Green Building Indicators by Fuzzy Multi-Criteria Decision Making. In: Sahoo, L., Senapati, T., Yager, R.R. (eds) Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain. Studies in Fuzziness and Soft Computing, vol 420. Springer, Singapore. https://doi.org/10.1007/978-981-19-4929-6_16

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