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- W4379261181 abstract "Green Buildings Labels (GBL) are indicated as one of the means with the potential to contribute to sustainable development. Worldwide, more than 850,000 green buildings have already had their project and development helped by just three of the GBLs (LEED, BREEAM, and BASIX). Brazil, however, has only 874 LEED-certified projects. Aiming to propose strategies to foster the adoption of GBL in the country, this paper developed an interpretative model involving barriers to them in Brazil. For this, the technique of Validated Interpretative Structural Modeling (VISM) was developed aiming to add statistical validity to interpretative models even in situations of research with small sample sizes. VISM is a modeling technique that incorporates the simplicity of Interpretative Structural Modeling (ISM) with the significance testing procedures of Partial Least Squares - Structural Equation Modeling (PLS-SEM). Adopting the VISM, the barriers model was then developed in five steps: (1) identification of indicators; (2) definition of constructs; (3) identification of relations between constructs; (4) validation of relations between constructs; and (5) creation of the conceptual model. As a result, VISM proved to be an effective innovative modeling technique in the development of models for exploratory research and presents results consistent with the reality studied. Regarding the model developed, the main barriers identified by the study to the adoption of GBL in Brazil are: “environmental protection mechanisms”; “costs and return on investment”; “mistrust of the benefits from GBL”; “corporate and public awareness”; “maturity and market economics”; and the “project, construction, and operation of green buildings." @default.
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- W4379261181 date "2023-08-01" @default.
- W4379261181 modified "2023-10-05" @default.
- W4379261181 title "Analysis of the barriers to the adoption of green buildings labels in Brazil by the validated Interpretative Structural Modeling (VISM) technique" @default.
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- W4379261181 doi "https://doi.org/10.1016/j.jclepro.2023.137642" @default.
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