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. Practical application The study validates a framework comprising seven criteria and 21 indicators aligned with the tripartite well-being model, keeping architectural design quality at the forefront of residential assessment. Weighted criteria enable architects to prioritise passive design strategies, particularly natural ventilation and daylighting, that enhance resident satisfaction while reducing reliance on mechanical systems. During concept design and massing iterations, the framework can assess spatial configurations, test alternatives, and develop client briefs against evidence-based well-being criteria. The scoring supports benchmarking among alternatives within a project and across residential developments. Apartment-level well-being scores can guide prospective residents towards options that best support their well-being.

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Publication Details

Journal
Building Services Engineering Research and Technology
Published
2026-07-18
DOI
https://doi.org/10.1177/01436244261463511
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
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article

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

Chandra Sabnani, Priyanka Rewatkar, Vijay Kapse
Building Services Engineering Research and Technology
Building Energy and Comfort Optimization
article

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

Chandra Sabnani, Priyanka Rewatkar, Vijay Kapse
article en

Abstract

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. Practical application The study validates a framework comprising seven criteria and 21 indicators aligned with the tripartite well-being model, keeping architectural design quality at the forefront of residential assessment. Weighted criteria enable architects to prioritise passive design strategies, particularly natural ventilation and daylighting, that enhance resident satisfaction while reducing reliance on mechanical systems. During concept design and massing iterations, the framework can assess spatial configurations, test alternatives, and develop client briefs against evidence-based well-being criteria. The scoring supports benchmarking among alternatives within a project and across residential developments. Apartment-level well-being scores can guide prospective residents towards options that best support their well-being.

Building Services Engineering Research and Technology
Visvesvaraya National Institute of Technology (IN)
Sustainable cities and communities
Openalex Percentile: Top 11%
Building Energy and Comfort Optimization
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