Pre-construction assessment models in social housing developments: a systematic literature review
The present study performs a Systematic Review of Literature (RSL) to map existing methods and research on the analysis and evaluation of housing projects of social interest that can be applied as Pre-Construction Evaluation. The work is motivated by a widely publicized finding of the lack of archit...
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| 主要な著者: | , |
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| フォーマット: | Online |
| 言語: | por |
| 出版事項: |
Universidade Estadual de Campinas
2017
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| オンライン･アクセス: | https://periodicos.sbu.unicamp.br/ojs/index.php/parc/article/view/8650238 |
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| 要約: | The present study performs a Systematic Review of Literature (RSL) to map existing methods and research on the analysis and evaluation of housing projects of social interest that can be applied as Pre-Construction Evaluation. The work is motivated by a widely publicized finding of the lack of architectural and urban quality in housing developments of social interest, such as those carried out by the Minha Casa Minha Vida Program, especially in its first and second phases. In this sense, we seek to study methods of analysis and evaluation guidelines that can contribute to improving the quality of urban relations in social housing in the country. Thus, the RSL is based on the following reference databases: Scielo (Scientific Electronic Library Online) platform, Scopus, Web of Science, Science Direct and the Brazilian Digital Library of Theses and Dissertations. Results indicate that the publications and studies on this subject are still scarce in the analytical literature in this area. In general, there are no references, protocols, and parameters for the evaluation of projects and their relation with the urban space before the stage of construction, especially when considered this Brazilian case. Therefore, we see a potential for the development of research and methodological knowledge in the field we call the Pre-Construction Assessment (APC), especially when considering the national demand for housing for the lower income population. |
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