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Record W2312521449 · doi:10.1061/41002(328)41

A Model to Predict the Impact of Excusable and Non-Excusable Delay on Selected Construction Projects

2008· article· en· W2312521449 on OpenAlexaboutno aff
Shervin Behboudi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsDamagesPostponementPre-construction servicesConstruction managementScheduleProcess (computing)Quality (philosophy)BusinessProject planningProject managementRisk analysis (engineering)Operations managementEngineeringComputer scienceCivil engineering

Abstract

fetched live from OpenAlex

Delays are the most common and also the most costly problem on construction projects. If the construction time period is extended, higher borrowing costs, inflation and other commercial factors will increase the construction costs. And if the construction costs increase, from an economic perspective, the project may lack an acceptable and functional performance. Thus, the primary objective during the construction process is to complete the project on time and within budget, while meeting established quality requirements and other specifications. However, in some cases, delays during construction can create huge cost damages, and these damages can result in the projects' parties taking legal action against each other through a construction claim. Historically, scheduling and finding the delays in big construction and commercial construction projects was based on discussion within an engineering department involved in the planning sector of the construction business. The reason for delay discussion is all about the effect of delays on the cost of construction. The amount of money involved in big construction is huge. And by extending the construction time, other expenses would be added to the original construction cost such as inflation, the cost of material and the interest costs of the investor's money. With smaller construction projects like housing, given that the amount of money involved was small, few investors were serious about the postponement of the completion time of the project. But today, the construction cost of a brand new high end house is more than in the past. In some places in the Toronto area, the cost of construction and land cost together become more than a few million dollars. This kind of cost causes investors to be far more interested in hiring a project scheduler to control the builder's time firmly in order to avoid the negative effects of the inflation cost of material and higher borrowing costs of the investor's money. Usually, the claims for residential projects are premised on two concepts: firstly, the costs of the late practice of a project, which is usually determined at the same rate as inflation; and secondly, the profit acquired from the investment, which is counted as interest on the of amount of money stock in the project for the duration of time (delay) that the project is not ready for use. The costs resulting from delays represent a percentage of the overall contract value, so, the cost of delay would be much greater in larger projects.

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 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.094
GPT teacher head0.348
Teacher spread0.255 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations8
Published2008
Admission routes1
Has abstractyes

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