From BIM to the Metaverse: A Human-Centred Framework for Participatory Architectural Design and Governance

Early end-user participation in architectural decision-making remains limited despite Building Information Modelling (BIM) and Digital Twin practice. This paper presents a human-centred, lifecycle-oriented framework that integrates extended reality (XR), generative artificial intelligence (AI), and metaverse environments with a federated BIM and Digital Twin backbone to embed non-specialists at the stages of highest design leverage. A mixed-methods design combined a critical narrative review with a bilingual cross-sectional survey of 69 architectural professionals in the United Kingdom and Turkey, who rated framework components on a four-point Likert scale. Analyses applied Spearman’s ρ, Kendall’s τ-b, and Kruskal–Wallis H tests under Benjamini–Hochberg false discovery rate correction. Eight stakeholder interviews on explainable AI and human-in-the-loop processes refined governance and transparency requirements. Endorsement was moderate to strong across lifecycle stages. Technical design and whole-life circularity recorded the strongest agreement, while metaverse governance returned the lowest mean (M = 2.78). After correction, BIM familiarity was positively associated with one capability item, 5D cost integration, and with one risk-recognition item on neglecting operation and maintenance during coordination, so the BIM familiarity hypothesis (H1) was supported by evidence of two kinds. No positively worded metaverse item survived correction, so the metaverse familiarity hypothesis (H2) was not supported as originally formulated. An exploratory finding indicated that greater metaverse familiarity was associated with heightened awareness of a governance risk—that unclear stakeholder roles would complicate immersive project initiation. The framework as appraised separates core BIM-centred dimensions from emerging metaverse-centred dimensions and aligns with the RIBA Plan of Work and BS EN 15978-1:2021. The framework is conceptual and has not been instantiated as a prototype, so the evidence establishes perceived viability rather than demonstrated effectiveness. It guides phased adoption that prioritises interoperability and identifies functional prototypes as the empirical next step.