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

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 2 value of 0.441 and a p-value below 0.05. This research helps decision-makers prioritize mitigation strategies for material waste and cost overruns, hence enhancing construction project performance.

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Publication Details

Journal
Scientific Reports
Published
2026-09-10
DOI
https://doi.org/10.1038/s41598-026-63008-x
Primary Topic
Recycled Aggregate Concrete Performance
Type
article
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article

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

Hossam E. Hosny, Lobna Kamal, Student, Mohamed S. Yamany
Scientific Reports
Recycled Aggregate Concrete Performance
article

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

Hossam E. Hosny, Lobna Kamal, Student, Mohamed S. Yamany
article en

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 2 value of 0.441 and a p-value below 0.05. This research helps decision-makers prioritize mitigation strategies for material waste and cost overruns, hence enhancing construction project performance.

Scientific ReportsVol. 16(1)
Zagazig University (EG)
Openalex Percentile: Top 14%
Recycled Aggregate Concrete Performance
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