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Early Contractor Involvement in Design and Its Impact on Construction Schedule Performance

2008· article· en· W2138906600 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Management in Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsScheduleConstruction managementProcess (computing)EngineeringConstruction industryQuality (philosophy)Project managementIntegrated project deliverySimulation modelingConstruction engineeringComputer scienceOperations researchSystems engineeringCivil engineering

Abstract

fetched live from OpenAlex

The importance of integrating construction knowledge into the design process has long been recognized by the construction industry. This paper studies early contractor involvement in design and its impact on construction schedule performance through a combined empirical case study and theoretical simulation analysis. Pipe and steel fabricators’ inputs at different design stages of industrial construction projects are identified. The case study shows that these inputs lead to improved drawing quality, material supply, information flow, and consequently improved construction schedule performance. This impact on construction schedule is illustrated using actual project data and simulation techniques. Simulation models were developed to demonstrate intuitively the impact at the construction operation level and they allow people to gain management insights through simulation experiments. Better understanding of the early contractor involvement process and its benefit can improve buy-in and help industry practitioners to reach the full potential of this concept.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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