Integration of Fuzzy-Analytical Hierarchy Process and TOPSIS model for road maintenance contractor selection

Purpose Choosing the right contractor is very important for the successful management of construction projects, especially when it comes to road maintenance. In order to improve the contractor for road maintenance, this study aims to create a thorough and efficient multiple-criteria decision-making (MCDM) model that goes beyond price-only assessments to include a wider range of criteria. Design/methodology/approach The study used both the Fuzzy Analytic Hierarchy Process (F-AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). There were six main groups of 26 sub-criteria: Contract Bid Price and Financial Capacity, Technical Capacity, Experience, Management Capacity, Safety and Environment. F-AHP was used to figure out how important each of these groups was compared to the others. TOPSIS was then used to rank possible contractors based on these weighted criteria. Findings The analysis showed that some criteria were especially important when choosing a contractor. Bid Price, Financial Performance, History of Non-Performance of Contracts, and Timely Completion of Projects were the most important factors in deciding whether a contractor was right for the job. These results show how important it is to use both financial and performance-related indicators when evaluating the appropriate contractor. Originality/value By addressing significant flaws in the conventional selection model, this study offers a fresh methodical approach to contractor evaluation. It provides a standard for enhancing the Roads Administration's procurement procedures and establishes a strong basis for upcoming studies and policy creation targeted at boosting accountability, efficacy and transparency in the execution of road maintenance.

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Publication Details

Journal
Engineering Computations
Published
2026-04-22
DOI
https://doi.org/10.1108/ec-07-2025-0779
Primary Topic
Construction Project Management and Performance
Type
article
Field-Weighted Citation Impact
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article

Integration of Fuzzy-Analytical Hierarchy Process and TOPSIS model for road maintenance contractor selection

Bahiru Bewket Mitikie, Walied A. Elsaigh, Tamrat Beyene Degu
Engineering Computations
Construction Project Management and Performance
article

Integration of Fuzzy-Analytical Hierarchy Process and TOPSIS model for road maintenance contractor selection

Bahiru Bewket Mitikie, Walied A. Elsaigh, Tamrat Beyene Degu
article en

Abstract

Purpose Choosing the right contractor is very important for the successful management of construction projects, especially when it comes to road maintenance. In order to improve the contractor for road maintenance, this study aims to create a thorough and efficient multiple-criteria decision-making (MCDM) model that goes beyond price-only assessments to include a wider range of criteria. Design/methodology/approach The study used both the Fuzzy Analytic Hierarchy Process (F-AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). There were six main groups of 26 sub-criteria: Contract Bid Price and Financial Capacity, Technical Capacity, Experience, Management Capacity, Safety and Environment. F-AHP was used to figure out how important each of these groups was compared to the others. TOPSIS was then used to rank possible contractors based on these weighted criteria. Findings The analysis showed that some criteria were especially important when choosing a contractor. Bid Price, Financial Performance, History of Non-Performance of Contracts, and Timely Completion of Projects were the most important factors in deciding whether a contractor was right for the job. These results show how important it is to use both financial and performance-related indicators when evaluating the appropriate contractor. Originality/value By addressing significant flaws in the conventional selection model, this study offers a fresh methodical approach to contractor evaluation. It provides a standard for enhancing the Roads Administration's procurement procedures and establishes a strong basis for upcoming studies and policy creation targeted at boosting accountability, efficacy and transparency in the execution of road maintenance.

Engineering Computations
University of South Africa (ZA), Bahir Dar University (ET)
Openalex Percentile: Top 7%
Construction Project Management and Performance
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