Identifying Moderation Effect between Project Delivery Systems and Cost Performance
Bibliographic record
Abstract
Identifying Moderation Effect between Project Delivery Systems and Cost Performance Hyosoo Moon, Hyun-Soo Lee, Moonseo Park and Bosik Son Pages 69-73 (2019 Proceedings of the 36th ISARC, Banff, Canada, ISBN 978-952-69524-0-6, ISSN 2413-5844) Abstract: This study was performed to identify the theoretical attribution of project type that moderates the impact of project delivery systems on cost performance. Previous studies have used direct relationship analysis to evaluate the project performance (e.g., the relationship between PDS and its cost performance, or the relationship between project type and cost performance). These analyses can cause inconsistent results and need to be analyzed in a single model. To combine the relationships between influential factors on cost performance, a causal model (i.e., moderation model) was suggested. The objective of this study is to develop a moderation model and test the statistical significance of moderation effect between PDS and cost performance. As a preliminary study, we established a simple moderation model and examine the moderation effect of project type. To test the model, 134 public sector projects completed between 1998 and 2013 in South Korea were utilized. The dataset consists of both Design-Build and Design-Bid-Build projects which are the most prevalent delivery systems. Even though the preliminary test results were not statistically significant, we can suggest the better way to understand the causal relationship moderated by project type between PDSs and their cost performance. This study is expected to provide the theoretical basis of the mechanism by which PDS impact cost performance, help project participants to select PDS by considering moderating effects in specific project types, and evaluate PDS appropriately in terms of cost performance. Keywords: Cost management; Project delivery system; Design-build(DB); Design-bid-build(DBB); Cost performance; Change order; Project type; Moderation effect DOI: https://doi.org/10.22260/ISARC2019/0010 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".