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 research maps drivers, barriers and an action path to boost BIM in green buildings
Two recent studies together sharpen understanding of what makes building information modeling (BIM) spread — and what still blocks it in green building projects. At the top level, a broad meta‑analysis using the Technology–Organization–Environment (TOE) framework finds compatibility, organizational culture and mimetic pressure are the strongest drivers of BIM adoption. A detailed empirical study that combines ISM and ANP methods maps 16 barriers and produces a recommended policy→management→technical→economic action sequence to push BIM into mainstream green building practice.
Top findings first
Key TOE meta-analysis results: The meta-analysis synthesized 62 empirical studies published between 2012 and 2023. The pooled evidence covered 11,228 study subjects and the synthesized studies spanned 13 countries. Using the Technology–Organization–Environment (TOE) framework, the study showed that compatibility lead the technical dimension, organizational culture was crucial in the organizational dimension, and mimetic pressure was the chief external‑environment driver. The study also found perceived usefulness and perceived ease of use mediated the influences of external factors on BIM adoption, and that national BIM maturity and contextual factors moderated specific paths in the adoption framework.
Key ISM‑ANP study results: The application obstacles of BIM technology in green building project and its key role path analysis identifies 16 influencing factors across five aspects: technology, economy, management, policy and environment. The ISM‑ANP coupling yields a four‑level hierarchy and an overall function rule: Policy factor layer → Management factor layer → Technical and environmental factor layer → Economic factor layer. The study highlights that exorbitant BIM cost, lack of evident investment return and protracted cost recovery cycle sit at the top of the barrier hierarchy.
Why the findings matter
Both studies make clear that short‑term economics often determine whether companies deploy BIM for green projects, even when long‑term gains exist. The ISM‑ANP paper stresses that economic factors are immediate barriers but argues these will only be sustainably reduced through technological advancement and development of interdisciplinary talent and management systems — not by temporary subsidies alone.
Study details, methods and scope
The TOE meta-analysis, titled Revisiting what factors promote BIM adoption more effectively through the TOE framework: A meta-analysis. lists authors Wenshun WANG, Min TAO, Sen GONG, Lingyun MI, Lijie QIAO, Yuguo ZHANG, and Xinyu ZHANG and was published in Frontiers of Engineering Management. The paper examined moderating effects of national BIM maturity and other contextual factors and reports that its findings help resolve lingering debates in existing literature and offer theoretical and practical support for promoting wider BIM adoption in the AEC industry. Full text DOI: 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. appears in Scientific Reports, volume 14, Article number: 30330 (2024), DOI: https://doi.org/10.1038/s41598-024-81360-8. The study used an ISM (Interpretive Structural Modeling) optimized by DEMATEL combined with ANP (Analytic Network Process) — an ISM‑ANP coupling model — and drew on literature research, expert interviews and questionnaires. Initially 47 factors were identified and reduced to 16 indicators through expert interviews. Questionnaires produced 179 effective questionnaires; effective rate reported as 75.53%.
Computation and modeling tools included MATLAB R2023a to calculate normalized direct influence matrices, Super Decisions software for ANP supermatrix modeling, and Python 3.8 for entropy weight calculations. The study reports final importance weights and ranks via ANP and adjusted ISM layers to yield a clear action path from policy to management to technical/environmental to economic outcomes.
Top barriers and the recommended action path
- Top economic barriers: Exorbitant BIM cost in green buildings (S5), lack of evident investment return (S6), and protracted cost recovery cycle (S7).
- Technical and environmental issues: Limited BIM software functionality for green building tasks, interoperability and compatibility problems, lack of interdisciplinary expertise and shortage of BIM professionals.
- Management gaps: Inadequate implementation systems, coordination difficulties, weak senior management support and shortage of systematic training.
- Policy weaknesses: Imperfect legal system, unclear responsibility allocation in multi‑party projects, data privacy and IP risks, insufficient policy incentives and lack of unified BIM standards for green buildings.
The ISM‑ANP study summarizes a key action path: Insufficient government intervention in the application of green building BIM → Insufficient high‑level support and imperfect management system; Insufficient R&D of domestic BIM core technology combined with green building → BIM technology is difficult to innovate and spread in the field of green building; Lack of compound talents → Insufficient economic benefits of green building BIM application → Affecting BIM in green building.
Practical recommendations
Policy and industry prescriptions in the ISM‑ANP study include incorporating BIM application standards into building regulations, mandatory phased roll‑outs for specified project types, financial incentives and technical support, creation of a targeted innovation fund, tax incentives, promotion of domestic R&D and industry alliances, and reinforced BIM teaching, training and enterprise internal capacity building. The paper suggests combining policy intervention with enterprise adjustments to reduce long‑term dependence on external incentives.
Implications for practitioners and policymakers
For firms, the studies point to investing in compatibility, staff training and management systems as high‑impact steps. For governments, the studies point to targeted policy measures and standards, sustained R&D support and market incentives to bridge the gap between technical potential and economic reality.
FAQ
Q1: What did the TOE meta-analysis cover?
A1: The meta-analysis synthesized 62 empirical studies published between 2012 and 2023. The pooled evidence covered 11,228 study subjects and the synthesized studies spanned 13 countries.
Q2: What were the main TOE drivers of BIM adoption?
A2: The study showed that compatibility proved to be the major driver of BIM adoption; organizational culture was a crucial factor promoting BIM adoption; mimetic pressure (pressure to imitate others) stood out as a primary external driver.
Q3: What does the Scientific Reports paper analyze?
A3: The application obstacles of BIM technology in green building project and its key role path analysis analyzed five aspects — technology, economy, management, policy and environment — and identified 16 influencing factors; focused on nine key factors such as insufficient technology maturity and high-cost issues.
Q4: How many questionnaire responses did the ISM‑ANP study use?
A4: Questionnaires produced 179 effective questionnaires; effective rate reported as 75.53%.
Q5: What is the final recommended action sequence?
A5: The ISM‑ANP paper presents an overall function rule: Policy factor layer → Management factor layer → Technical and environmental factor layer → Economic factor layer.
Key features at a glance
Feature | Detail |
---|---|
TOE meta-analysis scope | The meta-analysis synthesized 62 empirical studies published between 2012 and 2023; pooled evidence covered 11,228 study subjects across 13 countries. |
Top TOE drivers | Compatibility (technical), Organizational culture (organizational), Mimetic pressure (external). |
Scientific Reports analysis | The application obstacles of BIM technology in green building project and its key role path analysis; 16 influencing factors across five aspects. |
Methodology (Scientific Reports) | ISM improved by DEMATEL combined with ANP (ISM‑ANP); literature, expert interviews, questionnaires (179 valid responses; 75.53% effective rate). |
Main barrier layers | Policy factor layer → Management factor layer → Technical and environmental factor layer → Economic factor layer. |
Top economic barriers | Exorbitant BIM cost (S5); Lack of evident investment return (S6); Protracted cost recovery cycle (S7). |
Computation tools | MATLAB R2023a, Super Decisions, Python 3.8, Excel. |
Policy recommendations | Incorporate BIM standards into regulations, phased mandates, financial incentives, innovation fund, tax incentives, strengthen training and domestic R&D. |
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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