Modeling construction cost overrun risks at the FEED stage for mining projects using PLS-SEM

The mining industry consistently faces significant cost overruns during construction, rooted in the Front-End Engineering Design (FEED) stage, with overruns reported between 25% and 37%, underscoring the need to investigate early-stage risk factors. This study utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) and has identified 10 critical risk factors that significantly influence cost overruns in mining projects. These critical factors include impractical project schedules, inadequate project feasibility studies, client pressure to minimize the initial capital requirements, inaccurate cost estimations, increase of inflation rates, increase of official exchange rate, poorly understood geological and geotechnical aspects of a deposit, permit acquisition and approval delay, supply chain delays, and Impact on local communities and infrastructure. The robust analysis demonstrated strong indicator loadings and validated the measurement model’s discriminant validity. Significant findings from this analysis revealed that technical risks have the most direct influence on inadequate project planning risks, while compliance risks notably affect contracting and procurement risks. Further findings indicated that management and funding risks significantly influence both technical risks and market and economic risks. This study enables stakeholders to implement proactive strategies during the FEED stage by providing actionable insights, leading to more predictable and successful project outcomes. Ultimately, it offers a robust framework for mitigating cost overruns in mining projects.

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Publication Details

Journal
Journal of Asian Architecture and Building Engineering
Published
2025-03-24
DOI
https://doi.org/10.1080/13467581.2025.2481242
Primary Topic
Mining Techniques and Economics
Type
article
Field-Weighted Citation Impact
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article

Modeling construction cost overrun risks at the FEED stage for mining projects using PLS-SEM

Gongfan Chen, Abdullah Alsharef, Maan Shafaay, Fahad Alqahtani
Journal of Asian Architecture and Building Engineering
Mining Techniques and Economics
article

Modeling construction cost overrun risks at the FEED stage for mining projects using PLS-SEM

Gongfan Chen, Abdullah Alsharef, Maan Shafaay, Fahad Alqahtani
article en

Abstract

The mining industry consistently faces significant cost overruns during construction, rooted in the Front-End Engineering Design (FEED) stage, with overruns reported between 25% and 37%, underscoring the need to investigate early-stage risk factors. This study utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) and has identified 10 critical risk factors that significantly influence cost overruns in mining projects. These critical factors include impractical project schedules, inadequate project feasibility studies, client pressure to minimize the initial capital requirements, inaccurate cost estimations, increase of inflation rates, increase of official exchange rate, poorly understood geological and geotechnical aspects of a deposit, permit acquisition and approval delay, supply chain delays, and Impact on local communities and infrastructure. The robust analysis demonstrated strong indicator loadings and validated the measurement model’s discriminant validity. Significant findings from this analysis revealed that technical risks have the most direct influence on inadequate project planning risks, while compliance risks notably affect contracting and procurement risks. Further findings indicated that management and funding risks significantly influence both technical risks and market and economic risks. This study enables stakeholders to implement proactive strategies during the FEED stage by providing actionable insights, leading to more predictable and successful project outcomes. Ultimately, it offers a robust framework for mitigating cost overruns in mining projects.

Journal of Asian Architecture and Building Engineering
University of North Carolina at Charlotte (US), King Saud University (SA)
Industry, innovation and infrastructure
Openalex Percentile: Top 94%
Mining Techniques and Economics
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