Abstract

This research investigates the integration of a 5D framework within Building Information Modeling (BIM) using software to optimize efficiency in the design and construction of commercial projects, specifically within the hospitality, retail, and residential sectors. While the advantages of BIM are well documented, its full potential remains underutilized, particularly in large-scale commercial developments that significantly impact national economies. A structured methodology was employed to address this gap, beginning with a systematic literature review (SLR) to explore existing applications of 5D-BIM in commercial projects, focusing on trends, challenges, and implementation strategies. Expert interviews were conducted to gain insights from professionals experienced in BIM-enabled cost management, validating key findings and refining the research framework. A conceptual framework was then developed, integrating project governance, BIM policies and standards, digital platforms, BIM Level of Development (LOD), costestimation classification, and continuous improvement strategies to enhance 5D-BIM implementation. This framework was applied to multiple commercial projects, including hotels, malls, and residential compounds, assessing its effectiveness in improving cost management, quality assurance, and documentation accuracy. The literature review provided a foundational understanding of BIM adoption within the Architecture, Engineering, and Construction (AEC) industry, highlighting its significance in commercial developments and the predominance of BIM in Egyptian government-led projects. A survey was conducted to construct a checklist of BIM procedures, pinpointing critical aspects requiring evaluation. Emphasizing the need for robust training programs, centralized platforms, and continuous updates to improve model accuracy and collaborative effectiveness. Despite its substantial benefits, challenges remain, including data dependency, limited expertise in specialized designs, and market fluctuations. Addressing these challenges requires future advancements in predictive analytics, AI integration, and adaptive BIM models capable of mitigating risks associated with economic uncertainties. The results contribute valuable insights into the digital transformation of commercial construction, offering a structured approach for enhancing BIM adoption and optimizing project management practices.

School

School of Sciences and Engineering

Department

Construction Engineering Department

Degree Name

MS in Construction Engineering

Graduation Date

Spring 6-18-2025

Submission Date

5-11-2025

First Advisor

Ahmed Samer Ezeldin

Committee Member 1

Ibrahim Abotaleb

Committee Member 2

Ossama Elhossiny

Extent

143p.

Document Type

Master's Thesis

Institutional Review Board (IRB) Approval

Not necessary for this item

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