Evidence map›Paper›PMID 42722705›Full record

ArticleScientific reports2026

Assessing the impact of construction material waste drivers on project cost overrun across material processing stages: a structural equation modeling approach.

Lobna Kamal, Mohamed S Yamany, Hossam E Hosny, Student

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lobna KamalDepartment of Construction Engineering, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt.
Mohamed S YamanyDepartment of Construction Engineering, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt. mohamedyamany9@gmail.com.
Hossam E HosnyDepartment of Construction Engineering, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt.
StudentDepartment of Construction Engineering, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A considerable quantity of materials supplied to construction sites becomes waste, hence escalating project costs. Nevertheless, research lacks a thorough assessment of the intricate, indirect, and non-linear correlation between material waste drivers at different processing stages and project cost overruns. This research study investigates this correlation using an advanced multivariate statistical technique known as structural equation modeling (SEM). Data were collected through a questionnaire survey to evaluate the construction material waste factors (CMWFs) and their association with cost overruns in construction projects in Egypt. An exploratory factor analysis was conducted to categorize CMWFs into material processing phases: (1) design and documentation, (2) material procurement, (3) material handling, storage, and transportation, and (4) on-site management. An SEM model was developed to uncover the impact of latent material processing phases on project cost overruns. The model's consistency, reliability, and accuracy were verified employing various performance metrics, including Cronbach's Alpha, composite reliability, and root mean squared error. The results demonstrate that factors related to material handling, storage, and transportation exhibit the highest correlation and impact on project cost overruns, as reflected by an R

Indexed as

Construction projectsCost overrunsMaterial wastePLS-SEMStructural equation modeling

Identifiers

PMID42722705
PMCPMC13562747

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.