A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Life Cycle Sustainability Assessment of Buildings: A Scientometric Analysis
The significant environmental impact of the built environment, particularly concerning energy use, carbon emissions, and material consumption, coupled with its economic and social implications, has driven the demand for sustainable buildings. Life Cycle Sustainability Assessment (LCSA) offers a comprehensive approach to evaluating sustainability performance by integrating environmental, economic, and social dimensions across the building life cycle. However, the application of LCSA frameworks in the buildings sector remains limited due to the challenges in harmonizing different sustainability dimensions and addressing methodological inconsistencies. This study employs a scientometric analysis to systematically examine the research landscape on LCSA for buildings. Bibliographic records from the Scopus and Web of Science databases (1999–2024) were systematically analyzed using science mapping techniques and tools, including VOSviewer, CiteSpace, and Gephi. The analysis identifies key research trends, conceptual developments, influential academic sources, and collaboration patterns at the country level. The findings reveal a multi-faceted research landscape characterized by a predominance of environmental assessments, increasing attention to economic and social dimensions, the development of BIM-related methodologies, and emerging trend towards dynamic LCSA. Persistent barriers include insufficient standardization of methodologies, limited data availability, and the fragmented incorporation of the environmental, economic, and social dimensions of sustainability. The findings emphasize the need for advancing LCSA frameworks to achieve more effective integration of the triple bottom line, enabling robust decision-making and advancing sustainability in the built environment.
Life Cycle Sustainability Assessment of Buildings: A Scientometric Analysis
The significant environmental impact of the built environment, particularly concerning energy use, carbon emissions, and material consumption, coupled with its economic and social implications, has driven the demand for sustainable buildings. Life Cycle Sustainability Assessment (LCSA) offers a comprehensive approach to evaluating sustainability performance by integrating environmental, economic, and social dimensions across the building life cycle. However, the application of LCSA frameworks in the buildings sector remains limited due to the challenges in harmonizing different sustainability dimensions and addressing methodological inconsistencies. This study employs a scientometric analysis to systematically examine the research landscape on LCSA for buildings. Bibliographic records from the Scopus and Web of Science databases (1999–2024) were systematically analyzed using science mapping techniques and tools, including VOSviewer, CiteSpace, and Gephi. The analysis identifies key research trends, conceptual developments, influential academic sources, and collaboration patterns at the country level. The findings reveal a multi-faceted research landscape characterized by a predominance of environmental assessments, increasing attention to economic and social dimensions, the development of BIM-related methodologies, and emerging trend towards dynamic LCSA. Persistent barriers include insufficient standardization of methodologies, limited data availability, and the fragmented incorporation of the environmental, economic, and social dimensions of sustainability. The findings emphasize the need for advancing LCSA frameworks to achieve more effective integration of the triple bottom line, enabling robust decision-making and advancing sustainability in the built environment.
Life Cycle Sustainability Assessment of Buildings: A Scientometric Analysis
Ieva Poderytė (author) / Nerija Banaitienė (author) / Audrius Banaitis (author)
2025
Article (Journal)
Electronic Resource
Unknown
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