2021
DOI: 10.1016/j.seps.2020.100909
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An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability

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Cited by 26 publications
(13 citation statements)
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References 72 publications
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“…3) Model Quantification: Carrying out the model quantification using questions in the ANP questionnaire in the form of pairwise comparisons between elements (nodes) in Groups (clusters) or between clusters to find out which of them has the greater influence and how much the difference is through a numerical scale of 1-9 [16]. Pairwise comparison scale is shown in Table 1.…”
Section: Data Analysis Methodsmentioning
confidence: 99%
“…3) Model Quantification: Carrying out the model quantification using questions in the ANP questionnaire in the form of pairwise comparisons between elements (nodes) in Groups (clusters) or between clusters to find out which of them has the greater influence and how much the difference is through a numerical scale of 1-9 [16]. Pairwise comparison scale is shown in Table 1.…”
Section: Data Analysis Methodsmentioning
confidence: 99%
“…The assessment framework for developing green infrastructure for promoting environmental sustainability is still insufficient, despite increased research and urban policy advocating and implementing the development of green infrastructure (GI). S.-H. Lin et al (2021) built the assessment framework to create and improve the GI, which includes four dimensions and ten associated criteria, utilizing Multiple Attribute Decision-making (MADM) techniques. Their findings suggest the application of GI to enhance environmental sustainability, and decision-makers should pay greater attention to improving materials and design in infrastructural dimensions.…”
Section: Energy Efficient Infrastructure and Ecological Sustainabilitymentioning
confidence: 99%
“…Furthermore, the structure ensures data without loss of generality. (ii) Driven by the inference from Kao [61], weights are rationally determined by considering risk attitudes and the nature of factors, which is lacking in the close counterpart approach. (iii) Unlike the framework [53], the ranking algorithm in the proposed work considers the nature of factors and personal choices to provide an interactive, personalized variant of WASPAS with PLD.…”
Section: Comparison Studymentioning
confidence: 99%