An enabling framework towards digital twins implementation model for sustainable smart facility management

Purpose Digital twins (DT) technology shows great promise in transforming smart facility management (FM) towards sustainability in the built environment. However, having a clear understanding of the underlying enablers towards the implementation is imperative, and prior studies have paid little attention. To address the gap, this study investigates the critical enablers of effective DT implementation and their systemic relationship to achieve sustainable smart FM applications in the built environment. Design/methodology/approach An embedded mixed-method design, involving a literature review, an expert quantitative and qualitative survey, was pragmatically adopted. The design is further integrated with partial least squares structural equation modelling and inductive-thematic analysis. Findings A relatively high awareness level of DT, with a fair agreement level of its implementation for sustainable smart FM, was revealed. However, six categories of critical enablers were revealed to form an enabling framework (R2 = 92.70%, p > 0.05), considering their systemic interrelationships. This included “data sensing and processing-related technologies”, “network-related technologies”, “communication-related technologies”, “knowledge building”, “design process” and “development technologies”. The enabling framework explained 86.90% (p = 0.019) of the variance to develop an effective DT implementation model to achieve sustainability in smart FM. Practical implications The study develops a DT implementation model, recommending the critical enablers and their categories to FM professionals and firms, and if considered in decision-making and policymaking, could help effectively implement DT to achieve sustainability. Originality/value The study makes a unique contribution by developing a theoretically grounded enabling framework, explicitly underpinned by systems theory, to operationalise DT for sustainable smart FM. This framework advances existing knowledge by providing an implementation model through which FM organisations can systematically leverage DT for enhanced decision-making on improving sustainability outcomes and operational effectiveness in the built environment.

Authors

Institutions

Publication Details

Journal
Smart and Sustainable Built Environment
Published
2026-05-22
DOI
https://doi.org/10.1108/sasbe-12-2025-0848
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An enabling framework towards digital twins implementation model for sustainable smart facility management

Samuel Twum-Ampofo, Kofi A. B. Asare, Liupengfei Wu, Caleb Debrah et al.
Smart and Sustainable Built Environment
BIM and Construction Integration
article

An enabling framework towards digital twins implementation model for sustainable smart facility management

Samuel Twum-Ampofo, Kofi A. B. Asare, Liupengfei Wu, Caleb Debrah, Frank Ato Ghansah
article en

Abstract

Purpose Digital twins (DT) technology shows great promise in transforming smart facility management (FM) towards sustainability in the built environment. However, having a clear understanding of the underlying enablers towards the implementation is imperative, and prior studies have paid little attention. To address the gap, this study investigates the critical enablers of effective DT implementation and their systemic relationship to achieve sustainable smart FM applications in the built environment. Design/methodology/approach An embedded mixed-method design, involving a literature review, an expert quantitative and qualitative survey, was pragmatically adopted. The design is further integrated with partial least squares structural equation modelling and inductive-thematic analysis. Findings A relatively high awareness level of DT, with a fair agreement level of its implementation for sustainable smart FM, was revealed. However, six categories of critical enablers were revealed to form an enabling framework (R2 = 92.70%, p > 0.05), considering their systemic interrelationships. This included “data sensing and processing-related technologies”, “network-related technologies”, “communication-related technologies”, “knowledge building”, “design process” and “development technologies”. The enabling framework explained 86.90% (p = 0.019) of the variance to develop an effective DT implementation model to achieve sustainability in smart FM. Practical implications The study develops a DT implementation model, recommending the critical enablers and their categories to FM professionals and firms, and if considered in decision-making and policymaking, could help effectively implement DT to achieve sustainability. Originality/value The study makes a unique contribution by developing a theoretically grounded enabling framework, explicitly underpinned by systems theory, to operationalise DT for sustainable smart FM. This framework advances existing knowledge by providing an implementation model through which FM organisations can systematically leverage DT for enhanced decision-making on improving sustainability outcomes and operational effectiveness in the built environment.

Smart and Sustainable Built Environment
Hong Kong Polytechnic University (HK), Lingnan University (HK), University of Derby (GB), London South Bank University (GB), Japan Real Estate Institute (JP), University of Oklahoma (US), University of Hong Kong (HK)
London South Bank University
Openalex Percentile: Top 7%
BIM and Construction Integration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.