A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI

A Master of Science thesis in Construction Management by Faisal Ayman Mustafa Alhendi entitled, “A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI”, submitted in November 2023. Thesis advisor is Dr. Sameh El-Sayegh. Soft copy is available (Thesis, Completion Certifica...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Alhendi, Faisal Ayman Mustafa (author)
التنسيق: doctoralThesis
منشور في: 2023
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/25463
الوسوم: إضافة وسم
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author Alhendi, Faisal Ayman Mustafa
author_facet Alhendi, Faisal Ayman Mustafa
author_role author
dc.contributor.none.fl_str_mv El-Sayegh, Sameh
dc.creator.none.fl_str_mv Alhendi, Faisal Ayman Mustafa
dc.date.none.fl_str_mv 2023-11
2024-02-26T08:42:59Z
2024-02-26T08:42:59Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2023.54
http://hdl.handle.net/11073/25463
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Two Stage Early Contractor Involvement (2S-ECI)
Analytic Hierarchal Process (AHP)
Contractor Prequalification Criteria
dc.title.none.fl_str_mv A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Construction Management by Faisal Ayman Mustafa Alhendi entitled, “A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI”, submitted in November 2023. Thesis advisor is Dr. Sameh El-Sayegh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
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network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/25463
publishDate 2023
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spelling A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECIAlhendi, Faisal Ayman MustafaTwo Stage Early Contractor Involvement (2S-ECI)Analytic Hierarchal Process (AHP)Contractor Prequalification CriteriaA Master of Science thesis in Construction Management by Faisal Ayman Mustafa Alhendi entitled, “A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI”, submitted in November 2023. Thesis advisor is Dr. Sameh El-Sayegh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The construction industry is distinguished by its complexity and the requirement for innovation and efficiency. The Two-Stage Early Contractor Involvement (2S-ECI) delivery approach has attracted international attention for its potential to address industry difficulties. This thesis examines the applicability of 2S-ECI in the United Arab Emirates (UAE) and develops a customized prequalification method for first-stage contractors’ selection to ensure its successful implementation. The primary goals of this research are twofold: first, to identify and assess the benefits and challenges of using the 2S-ECI delivery method in the unique context of the UAE construction industry; and second, to categorize and adapt 2S-ECI prequalification criteria to create a decision support model specifically tailored for evaluating 2S-ECI contractors operating in the UAE. In order to achieve the first goal, the benefits and challenges were identified through literature review. This is followed by a survey to determine their importance using Likert scale. The results revealed that the main benefits include incorporating contractor input during the design process, accelerating the project schedule, and improving the mitigation of risks. Additionally, the results revealed that the main challenges include unavailability of a clear first-stage contractor prequalification assessment, lack of ECI experience, and that 2S-ECI might not be suitable for all types of projects. To accomplish the second goal, sixteen prequalification criteria were identified through literature review, followed by a second survey using the Analytical Hierarchy Process (AHP) to determine the weights of the selected prequalification criteria. The results indicate that the main criteria include demonstrated experience in previous projects involving 2S-ECI, proven expertise and proficiency in the specific project type, and positive references and a history of satisfied past clients. A tailored decision-support model is proposed for evaluating and selecting 2S-ECI contractors in the UAE. The methodology ensures that the contractors selected for the first stage of the 2S-ECI process are best prepared to satisfy the specific demands and requirements of construction projects in the UAE. The findings of this study have the potential to transform the UAE construction industry.College of EngineeringMultidisciplinary ProgramsMaster of Science in Construction Management (MSCM)El-Sayegh, Sameh2024-02-26T08:42:59Z2024-02-26T08:42:59Z2023-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2023.54http://hdl.handle.net/11073/25463en_USoai:repository.aus.edu:11073/254632025-06-26T12:25:53Z
spellingShingle A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
Alhendi, Faisal Ayman Mustafa
Two Stage Early Contractor Involvement (2S-ECI)
Analytic Hierarchal Process (AHP)
Contractor Prequalification Criteria
status_str publishedVersion
title A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
title_full A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
title_fullStr A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
title_full_unstemmed A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
title_short A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
title_sort A Decision Support Model for Pre-qualifying Construction Contractors using 2S-ECI
topic Two Stage Early Contractor Involvement (2S-ECI)
Analytic Hierarchal Process (AHP)
Contractor Prequalification Criteria
url http://hdl.handle.net/11073/25463