Evaluation and classification of risk from multi-party stakeholders of the construction industry

The presence of risk events in the construction industry is considered high among multiple industries. Furthermore, it results in construction projects having cost overruns with no precise mechanism to deal with it. Thus, this study focuses on the identification, assessment, and classification of such critical risk events as an essential substance for causing project cost overruns. The study identified 150 risk events, and assessed the refined 40 major risk events, adopted multi-party stakeholders’ perception evaluation surveys for the identification, and assessment based on the Relative Importance Index (RII), Kendall’s concordance (W), Cronbach’s alpha, Corrected Item-Total Correlation, and Validity test, the values were found to be statistically adequate. Classification relied on Principal Component Analysis (PCA). RII reveals that inaccurate material estimation got the highest rank among all other risk events, followed by financial difficulties faced by contractors. (PCA) classified 40 risk events into nine components with contractual and on-site risk components having higher risk factors. Furthermore, the study output may be used for better decision-making, as a result of assessed and classified risk events.

Authors

Institutions

Publication Details

Journal
Journal of Asian Architecture and Building Engineering
Published
2025-05-19
DOI
https://doi.org/10.1080/13467581.2025.2507863
Primary Topic
Economic and Technological Systems Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation and classification of risk from multi-party stakeholders of the construction industry

Solyman Ashrafi, Abdul Mateen Khan, Rana Rabnawaz Ahmed, Wesam Salah Alaloul et al.
Journal of Asian Architecture and Building Engineering
Economic and Technological Systems Analysis
article

Evaluation and classification of risk from multi-party stakeholders of the construction industry

Solyman Ashrafi, Abdul Mateen Khan, Rana Rabnawaz Ahmed, Wesam Salah Alaloul, Muhammad Saqib, Rizwan-Ul-Haq Farooqui
article en

Abstract

The presence of risk events in the construction industry is considered high among multiple industries. Furthermore, it results in construction projects having cost overruns with no precise mechanism to deal with it. Thus, this study focuses on the identification, assessment, and classification of such critical risk events as an essential substance for causing project cost overruns. The study identified 150 risk events, and assessed the refined 40 major risk events, adopted multi-party stakeholders’ perception evaluation surveys for the identification, and assessment based on the Relative Importance Index (RII), Kendall’s concordance (W), Cronbach’s alpha, Corrected Item-Total Correlation, and Validity test, the values were found to be statistically adequate. Classification relied on Principal Component Analysis (PCA). RII reveals that inaccurate material estimation got the highest rank among all other risk events, followed by financial difficulties faced by contractors. (PCA) classified 40 risk events into nine components with contractual and on-site risk components having higher risk factors. Furthermore, the study output may be used for better decision-making, as a result of assessed and classified risk events.

Journal of Asian Architecture and Building Engineering
NED University of Engineering and Technology (PK), Universiti Teknologi Petronas (MY), Mississippi State University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 85%
Economic and Technological Systems Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.