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امروز دوشنبه 1403.7.23 Iranian Construction Engineering and Management
صفحه اصلی
مقالات و آثار علمی

مقاله اثر مشوقها بر ساخت و ساز سبز


Authors
Abbas Tajaddini, Leyla Pirooznezhad, Mehdi Ravanshadnia, David Coley
Publication date
2023/11/7
Journal
International Journal of Construction Management
Pages
1-18
Publisher
Taylor & Francis
Description
The switch to sustainable, or green buildings (GBs) is likely to involve a range of governmental policies, with the mix of incentives dependent on the country. The question then becomes one of creating the mix such that it represents the minimum cost/effort whilst maximizing the delivery rate. This research aimed at quantifying the influence of differing GB incentives using a fuzzy inference system. Twenty-six incentives were identified through literature review and expert interviews (n = 36) using a 5-point pairwise questionnaire. These incentives can be naturally bundled into Technical, Financial and Legal groups. Ranking these suggests the Financial, Technical and Legal groups rank first to third, with weights of 0.42, 0.32 and 0.26, respectively. Then, to quantify the potential influence of individual incentives, a fuzzy inference model was created. The model was then employed to predict the influence of each …
Authors
Abbas Tajaddini, Leyla Pirooznezhad, Mehdi Ravanshadnia, David Coley
Publication date
2023/11/7
Journal
International Journal of Construction Management
Pages
1-18
Publisher
Taylor & Francis
Description
The switch to sustainable, or green buildings (GBs) is likely to involve a range of governmental policies, with the mix of incentives dependent on the country. The question then becomes one of creating the mix such that it represents the minimum cost/effort whilst maximizing the delivery rate. This research aimed at quantifying the influence of differing GB incentives using a fuzzy inference system. Twenty-six incentives were identified through literature review and expert interviews (n = 36) using a 5-point pairwise questionnaire. These incentives can be naturally bundled into Technical, Financial and Legal groups. Ranking these suggests the Financial, Technical and Legal groups rank first to third, with weights of 0.42, 0.32 and 0.26, respectively. Then, to quantify the potential influence of individual incentives, a fuzzy inference model was created. The model was then employed to predict the influence of each …


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