A data driven decision-making framework for architectural design quality: Enhancing well-being in multi-family housing

Rapid global urbanisation necessitates multi-family housing designs that enhance residents’ physical, social, and psychological well-being. However, prevailing assessment tools often prioritise environmental and economic aspects while underrepresenting architect-controlled design attributes. This oversight has significant yet under-studied effect: poor architectural design can increase operational energy loads through reliance on mechanical systems. This study develops and validates a framework for assessing architectural design quality in relation to residents’ well-being in multi-family residential buildings, addressing gaps in existing assessment tools. Using a PRISMA - guided systematic scoping review, 2536 indicators were identified. Unsupervised machine learning identified thematic clusters, which were refined through expert review based on the study’s theoretical foundation and scope. The criteria and indicators were weighted using the Analytic Hierarchy Process (n = 51 architects) and refined through resident survey analysis (n = 411), resulting in a framework comprising seven criteria and 21 indicators. From the architects’ perspective, natural ventilation (25.3%) emerged as the highest-weighted criterion, followed by daylighting (21.7%) and functionality (21.6%). The findings highlight the role of passive architectural design in supporting well-being. The study presents a novel, design-focused, decision-support framework that complements existing assessment tools by introducing design quality as a foundational layer for early-stage housing design decision-making.