Using a Fuzzy Model to Evaluate Risks caused by Variation Orders in Construction Projects

The construction industry is the main driving sector for any country's economy. However, it is too risky due to the many risks and challenges in this industry. One of the main challenges in construction projects is variation orders, as they lead to conflicts between project parties and cause poor project performance. This study aims to evaluate the risks associated with variation orders in construction projects using fuzzy risk assessment. The targeted population is the construction contractors in Palestine. A questionnaire survey was used to collect data on the severity and frequency of the 22 identified factors of variation orders. Then, a fuzzy logic system was developed to rate these factors. The factor risk level was determined by connecting the relationship between the severity and frequency indices using If-Then rules. The determination of risk level is a critical task in the proposed fuzzy system, which depends on the complex combinations of all If-Then rules. Risk is determined not only by the If-Then rules but also by the weight of each rule. This study shows that the factors with the highest risk levels are scope change by the client, client financial problems, unavailability of required materials, poor design documents, and modification of specifications. The results can serve as guidelines for project participants who need to prepare and implement a comprehensive and effective risk management plan to meet project goals. To improve project performance, construction parties are recommended to implement the proposed method to assess risks related to construction projects. Finally, the proposed risk model demonstrates the ability to evaluate risk levels by aggregating rules and combining the project risk factors using a fuzzy logic model and MATLAB.

Authors

Institutions

Publication Details

Journal
Engineering Technology & Applied Science Research
Published
2025-02-01
DOI
https://doi.org/10.48084/etasr.8558
Primary Topic
Construction Project Management and Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using a Fuzzy Model to Evaluate Risks caused by Variation Orders in Construction Projects

Ibrahim Mahamid, Allam Abu Mwais
Engineering Technology & Applied Science Research
Construction Project Management and Performance
article

Using a Fuzzy Model to Evaluate Risks caused by Variation Orders in Construction Projects

Ibrahim Mahamid, Allam Abu Mwais
article en

Abstract

The construction industry is the main driving sector for any country's economy. However, it is too risky due to the many risks and challenges in this industry. One of the main challenges in construction projects is variation orders, as they lead to conflicts between project parties and cause poor project performance. This study aims to evaluate the risks associated with variation orders in construction projects using fuzzy risk assessment. The targeted population is the construction contractors in Palestine. A questionnaire survey was used to collect data on the severity and frequency of the 22 identified factors of variation orders. Then, a fuzzy logic system was developed to rate these factors. The factor risk level was determined by connecting the relationship between the severity and frequency indices using If-Then rules. The determination of risk level is a critical task in the proposed fuzzy system, which depends on the complex combinations of all If-Then rules. Risk is determined not only by the If-Then rules but also by the weight of each rule. This study shows that the factors with the highest risk levels are scope change by the client, client financial problems, unavailability of required materials, poor design documents, and modification of specifications. The results can serve as guidelines for project participants who need to prepare and implement a comprehensive and effective risk management plan to meet project goals. To improve project performance, construction parties are recommended to implement the proposed method to assess risks related to construction projects. Finally, the proposed risk model demonstrates the ability to evaluate risk levels by aggregating rules and combining the project risk factors using a fuzzy logic model and MATLAB.

Engineering Technology & Applied Science ResearchVol. 15(1)
Arab American University (PS)
Openalex Percentile: Top 98%
Construction Project Management and Performance
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.