Quantifying the Impact of Change on the Progress of Construction Projects
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.
Bibliographic record
Abstract
Change management is an integral part of any construction project. Although changes in scope in the construction phase are mainly caused by owners, they can occasionally be caused by contractors. Previous studies and experience have shown that scope change can have a substantial impact on the project’s progress, budget, schedule, and labor performance. In fast-tracking projects, sometimes poor-quality engineering drawings are issued for construction, which necessitates changes during the project’s execution. In this research, the authors address the indirect impact of engineering changes on construction labor performance during the project’s construction phase. This method involves using baseline schedule, earned value management system (EVMS), and an actual progress tracking tool. The occurrence of changes in the engineering scope is integrated with the EVMS charts to illustrate the impact of engineering changes on the construction labor performance factor (LPF). This method provides quantitative measurements of the labor performance loss due to engineering changes. It was applied using data from a real construction project to quantify the LPF loss due to changes. The results show that the LPF deteriorates in direct proportion with the number of changes made to the original scope.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it