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<p>The success of construction projects relies heavily on selecting the right contractor, with many failures attributed to labor issues, financial constraints, poor workmanship, and management deficiencies. Recognizing the inadequacies of current contract awarding methods for Ethiopian road projects, this study employs the FUZZY TOPSIS approach using MATLAB software to aid in contractor selection. Through purposive sampling, mixed surveys, and primary and secondary data sources, primary data is collected via interviews, questionnaires, and case studies, complemented by secondary data obtained through document reviews. The study evaluates existing technical and financial evaluation methods, verifying contractor experience, licenses, finances, and bid price discounts. A comprehensive review of over 37 selection criteria, including inputs from the Ethiopian road authority, is conducted. Utilizing SPSS analysis, the study identifies the eight most critical factors for selecting ideal contractors. Finally, applying these findings to a case study, the study compares contractor selection using the Fuzzy TOPSIS model. The Ethiopian Road Authority seeks contractors with capabilities beyond price considerations, including management ability, quality assurance, and adherence to project schedules. By implementing this data-driven approach effectively, improvements in project outcomes such as timeliness, budget adherence, and overall quality are anticipated.</p>

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Fuzzy-topsis approach for contractor selection decision; a case of Ethiopia road projects

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月2日

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  • Bahiru Bewket Mitikie,
  • Genet Alemayehu Gonie,
  • Walied A. Elsaigh

摘要

The success of construction projects relies heavily on selecting the right contractor, with many failures attributed to labor issues, financial constraints, poor workmanship, and management deficiencies. Recognizing the inadequacies of current contract awarding methods for Ethiopian road projects, this study employs the FUZZY TOPSIS approach using MATLAB software to aid in contractor selection. Through purposive sampling, mixed surveys, and primary and secondary data sources, primary data is collected via interviews, questionnaires, and case studies, complemented by secondary data obtained through document reviews. The study evaluates existing technical and financial evaluation methods, verifying contractor experience, licenses, finances, and bid price discounts. A comprehensive review of over 37 selection criteria, including inputs from the Ethiopian road authority, is conducted. Utilizing SPSS analysis, the study identifies the eight most critical factors for selecting ideal contractors. Finally, applying these findings to a case study, the study compares contractor selection using the Fuzzy TOPSIS model. The Ethiopian Road Authority seeks contractors with capabilities beyond price considerations, including management ability, quality assurance, and adherence to project schedules. By implementing this data-driven approach effectively, improvements in project outcomes such as timeliness, budget adherence, and overall quality are anticipated.