In the last decades, various sustainability assessment tools have been developed to facilitate shift towards sustainability in building industry. However, existing tools mainly focus on environmental and economic issues while give limited consideration on social aspects. This study fills this gap through developing a methodological framework for social sustainability assessment of building projects. Social life cycle assessment method was adopted as the basis for framework development, which aims to assess the potential positive and negative social impact of products or systems throughout their life cycle. Firstly, four stakeholder categories including workers, occupants, local community and society were identified covering groups of people potentially affected by life-cycle activities, based on which social subcategories were selected under each stakeholder category to illustrate different social concerns. Weights among these impact categories were then obtained through AHP process. Secondly, building-specific indicators to assess these impacts and their performance reference values were proposed, including both quantitative and semi-quantitative ones. Values of quantitative indicators can be directly obtained from project records, whereas for semi-quantitative indicators, experts' verbal and qualitative assessments should be conducted and further converted to numbers based on fuzzy set theory method, which addresses the imprecision and uncertainty inherent to human judgments using linguistic terms and fuzzy numbers. Finally, data collection structure combining generic and site-specific information was proposed, and life-cycle social impact index can be calculated based on performance reference values and weights.The proposed social sustainability assessment method was illustrated using a case study of a modular building.
Siyu Liu, Nanyang Technological University, Singapore
Shunzhi Qian, Nanyang Technological University, Singapore
Stream: Social Sustainability & Sustainable Living
Added on Friday, July 27th, 2018
This paper is part of the ACSEE2018 Conference Proceedings (View)
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