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Record W2741899642 · doi:10.2495/sdp-v13-n1-121-129

The awareness of integrated project delivery and building information modelling - facilitating construction projects

2018· article· en· W2741899642 on OpenAlexvenueno aff
Krishna Govender, J. Nyagwachi, John Smallwood, Colin Allen

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicAdvanced Scientific and Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrated project deliveryBuilding information modelingConstruction engineeringSystems engineeringDesign–buildEngineering managementArchitectural engineeringProject managementEngineeringProcess managementComputer scienceCivil engineeringOperations management

Abstract

fetched live from OpenAlex

Construction projects are complex undertakings, which involve many different parties striving towards successful completion.Effective and efficient processes are based on collaboration with an integrated project delivery approach, the project team working together as a cohesive unit towards a common goal.However, the current procurement system adopted creates fragmentation of the design and construction teams, which results in projects being delivered late, constructability issues, final project cost exceeding the approved budget, and variation orders.A self-administered questionnaire was distributed to various built environment professionals within the Eastern Cape construction industry to determine the current awareness with respect to Integrated Project Delivery (IPD) and Building Information Modelling (BIM).The findings showed that these systems have many benefits, which can assist in mitigating the aforementioned issues.The respondents indicated that they were aware of IPD and BIM and the related benefits; however, there are barriers preventing the adoption of these systems, such as clients not identifying the advantages, clients being resistant to change, as well as a lack of the requisite-related knowledge and skills.Conclusions include that collaboration within the construction industry is imperative toward the successful completion of projects and that further information with respect to IPD and BIM is required to raise awareness and promote the adoption of these models.Recommendations include: all stakeholders need to commit to the ideology behind these concepts and develop an understanding of the concepts and related benefits, and industry associations need to publish information regarding IPD and BIM, as this will increase awareness.

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)0.017
metaresearch head score (Gemma)0.025
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.003
Scholarly communication0.0120.019
Open science0.0030.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.058
GPT teacher head0.336
Teacher spread0.277 · 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

Citations18
Published2018
Admission routes1
Has abstractyes

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