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Record W2183649514 · doi:10.5539/ijms.v7n6p162

Critical Barriers to BIM Implementation in the AEC Industry

2015· article· en· W2183649514 on OpenAlexvenueno aff
Shijing Liu, Benzheng Xie, Linda Tivendal, Chunlu Liu

Bibliographic record

VenueInternational Journal of Marketing Studies · 2015
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsBuilding information modelingBusinessConstruction industryProcess managementEngineering managementKnowledge managementConstruction engineeringComputer scienceOperations managementEngineering

Abstract

fetched live from OpenAlex

<p>Building Information Modelling (BIM) is one of the most significant technological advances in the building design and construction industry to date. Implementation of BIM has increased significantly over the past decade; and it enables the different stakeholders of a construction project to collaborate better throughout its lifecycle, and improves the opportunities to share data and decrease consumption. However, the implementation of BIM lags far behind its potential due to the existence of various barriers. This paper aims at identifying, classifying, and prioritising these barriers to BIM implementation through a survey. The research findings are expected to assist major stakeholders in the construction industry to promote BIM implementation.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.059
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.002
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.360
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations165
Published2015
Admission routes1
Has abstractyes

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