China, September 19, 2025
News Summary
Two new academic syntheses reveal what speeds and what blocks BIM adoption in green building projects. A TOE meta-analysis of 62 studies and 11,228 subjects finds compatibility, organizational culture and mimetic pressure as the strongest drivers, with perceived usefulness and ease of use acting as mediators. A separate ISM‑ANP study maps 16 barriers and produces a prioritized action path: policy → management → technical/environmental → economic. Together the papers recommend phased regulatory mandates, financial and R&D support, industry training, and interoperability and management reforms to foster durable BIM uptake in sustainable construction.
New studies map drivers, 16 barriers and an action path to boost BIM use in green buildings
Two recent academic studies provide a clearer roadmap for expanding use of building information modeling (BIM) in green building projects. At the top level, a large meta-analysis using the Technology–Organization–Environment (TOE) framework found that compatibility, organizational culture and mimetic pressure are the most influential drivers of BIM adoption. Complementing that work, an ISM‑ANP study of BIM in green buildings identified 16 barriers and a prioritized action trajectory summarized as policy factor layer → management factor layer → technical and environmental factor layer → economic factor layer.
Top-line findings
The TOE meta-analysis titled Revisiting what factors promote BIM adoption more effectively through the TOE framework: A meta-analysis pooled evidence from 62 empirical studies published between 2012 and 2023, covering 11,228 study subjects across 13 countries. Using the TOE lens, the study systematically explored which factors and causal paths most effectively promote BIM adoption. The study reported that compatibility proved to be the major driver of BIM adoption in the technical dimension; organizational culture was a crucial factor promoting BIM adoption in the organizational dimension; and in the external-environment dimension mimetic pressure (pressure to imitate others) stood out as a primary external driver. The authors also found that perceived usefulness and perceived ease of use mediate influences of external factors on BIM adoption, and that national BIM maturity and contextual factors moderate specific pathways in the adoption framework. This paper was published in Frontiers of Engineering Management and is available at https://doi.org/10.1007/s42524-025-4056-8.
The Scientific Reports article titled The application obstacles of BIM technology in green building project and its key role path analysis mapped obstacles specifically for green buildings and produced a structured, weighted model of causes and recommendations. The article appears in Scientific Reports, volume 14, Article number: 30330 (2024), DOI https://doi.org/10.1038/s41598-024-81360-8. The authors used an ISM model improved with DEMATEL to quantify influence strengths and coupled that with ANP to assign weights and capture interdependencies, producing a combined ISM‑ANP result that isolates 16 influencing factors across five aspects: technology, economy, management, policy and environment.
What the green building study found
The ISM‑ANP study started from 47 candidate factors, reduced to 16 through expert interviews, and gathered 179 effective questionnaires (effective rate 75.53%). The study highlights that economic factors such as exorbitant BIM cost in green buildings, lack of evident investment return, and protracted cost recovery cycle sit at the top of the model and can directly deter enterprise adoption decisions. The authors reported a final adjusted hierarchy and an overall function rule expressed as Policy factor layer → Management factor layer → Technical and environmental factor layer → Economic factor layer.
Technical and environmental constraints identified include limited BIM software functionality for green building analysis, interoperability and compatibility issues, shortage of compound talents, and high initial investment with weak short-term economic benefits. Management gaps include imperfect implementation and management systems, coordination difficulties among project teams, and insufficient senior management endorsement. Policy gaps include imperfect laws, unclear responsibility sharing in multi‑party BIM projects, data privacy risks, and insufficient policy incentives and standards.
Methods that produced the results
The TOE meta-analysis synthesized 62 empirical studies and examined moderating effects of national BIM maturity and context. The Scientific Reports paper used a mix of literature review, expert interviews (ten experts), questionnaire surveys (179 responses), DEMATEL to quantify influence strengths, ISM for hierarchical stratification, and ANP (Super Decisions software) for network weighting. MATLAB R2023a and Python 3.8 were used for numerical computations and entropy weighting. The ISM‑ANP model passed consistency checks (example C.R. values reported as 0.029 and 0.070).
Practical implications and recommendations
Both studies point to a combination of market, management and policy actions rather than single fixes. The green building paper proposes targeted policy measures including incorporation of BIM application standards into fundamental building regulations, mandatory BIM for certain project types with phased rollouts, financial incentives and technical support, a suggested Green Building BIM Innovation Fund, tax incentives, promotion of domestic R&D and industry alliances, and reinforcement of BIM education and enterprise training. The authors emphasize that economic barriers are immediate obstacles and sustained cost reduction requires technological progress and development of interdisciplinary talent.
Why these studies matter
Together, the meta-analysis and the ISM‑ANP study clarify both broad adoption drivers and the detailed barrier pathways in green building contexts. The TOE work helps resolve lingering debates about what drives BIM adoption globally, while the ISM‑ANP study offers a ranked, actionable route planners and policymakers can use: strengthen policy, shore up management, invest in technical capability and talent, and address the economic case for enterprises.
FAQ
What did the TOE meta-analysis find?
The TOE meta-analysis found that compatibility proved to be the major driver of BIM adoption; organizational culture was a crucial factor promoting BIM adoption; and mimetic pressure (pressure to imitate others) stood out as a primary external driver.
How large was the TOE meta-analysis sample?
The study pooled evidence from 62 empirical studies published between 2012 and 2023, covering 11,228 study subjects across 13 countries.
What did the Scientific Reports paper identify?
The Scientific Reports paper identified 16 influencing factors across technology, economy, management, policy and environment and proposed an overall function rule: Policy factor layer → Management factor layer → Technical and environmental factor layer → Economic factor layer.
Which economic factors top the green building barrier model?
The first (top) layer (economic factors) consists of exorbitant BIM cost in green buildings (S5), lack of evident investment return (S6), and protracted cost recovery cycle (S7).
Where can I read the full studies?
The TOE meta-analysis is published in Frontiers of Engineering Management, DOI https://doi.org/10.1007/s42524-025-4056-8. The Scientific Reports article is volume 14, Article number: 30330 (2024), DOI https://doi.org/10.1038/s41598-024-81360-8.
Key features at a glance
| Feature | Details |
|---|---|
| TOE meta-analysis scope | 62 empirical studies (2012–2023), 11,228 study subjects, 13 countries; Frontiers of Engineering Management; DOI https://doi.org/10.1007/s42524-025-4056-8 |
| TOE meta-analysis key drivers | compatibility, organizational culture, mimetic pressure |
| Scientific Reports study scope | Scientific Reports volume 14, Article number: 30330 (2024); 16 influencing factors across five aspects; DOI https://doi.org/10.1038/s41598-024-81360-8 |
| Analytic approach (green building paper) | ISM optimized by DEMATEL combined with ANP (ISM‑ANP coupling); MATLAB R2023a, Super Decisions, Python 3.8 used |
| Top-level action path | Policy factor layer → Management factor layer → Technical and environmental factor layer → Economic factor layer |
| Top economic barriers | Exorbitant BIM cost in green buildings (S5); lack of evident investment return (S6); protracted cost recovery cycle (S7) |
Deeper Dive: News & Info About This Topic
Additional Resources
- Newswise: Revisiting what factors promote BIM adoption more effectively through the TOE framework
- Wikipedia: Building information modeling
- Scientific Reports: The application obstacles of BIM technology in green building project and its key role path analysis
- Google Search: BIM green building barriers
- Nature Scientific Reports: 2025 study on BIM adoption (s41598-025-06662-x)
- Google Scholar: TOE framework BIM adoption
- AEC Magazine: BIM — the Chinese way
- Encyclopedia Britannica: Building Information Modeling
- ScienceDirect: Article S0926580524000372 (BIM adoption research)
- Google News: BIM adoption green buildings
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