A text mining approach to performance enhancement in BIM pervasive major project delivery

Bareka, Ambark

Thesis

A text mining approach to performance enhancement in BIM pervasive major project delivery

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Creator

Bareka, Ambark

Rights statement

Strathclyde Thesis Copyright

Awarding institution

University of Strathclyde

Date of award

2025

Thesis identifier

T17290

Person Identifier (Local)

201887253

Qualification Level

Doctoral (Postgraduate)

Qualification Name

Doctor of Philosophy (PhD)

Department, School or Faculty

Department of Architecture

Abstract

Purpose: This research aims to rigorously develop and implement a specialized TM technique to significantly enhance performance in BIM pervasive major project delivery. By addressing challenges related to errors, uncertainties, and expectations within this context, the study endeavours to offer substantial contributions to construction management knowledge. The research introduces the “BIM Text Analysis and Performance Enhancement” (BIMTAPE) framework, which synergizes the TM methodology with BIM to optimize project execution within the BIM pervasive major project delivery. Methodology: A holistic systematic literature review enabled by the Nine-Square Process (NSP) was conducted, entailing a thorough search of relevant literature from academic databases and other relevant sources, identifying current knowledge and the research gap on delivery. Additionally, the research process adhered to a sequenced approach, where the development of the BIMTAPE Framework took precedence before conducting specific experimental case studies. This structured framework provided a systematic and comprehensive approach to analyse diverse BIM-related texts. Findings: This research validates experimental findings and provides insights into the relationship between text analysis and performance enhancement in major project delivery, using Social Network Analysis. The study comprehensively understands the role of text analysis in major project performance, emphasizing BIM alignment with industry standards for value realization in contracts. Notably, the BIMTAPE Framework’s potential impact in addressing challenges, exemplified by the High Speed Two (HS2) project’s initiatives, enhances major project execution within the BIM pervasive major project delivery. Implications: The integration of BIM technology with TM within the BIMTAPE Framework excludes structured data standards like Industry Foundation Classes (IFC) and building SMART Data Dictionary (bSDD). In academic settings, the framework introduces a new approach for investigating unstructured textual data in BIM, encouraging further exploration. Limitations: This research’s applicability is constrained by the limited sample size. Expanding the scope to encompass larger studies will be crucial for generalisability. Further exploration across various contexts will provide a more comprehensive understanding of the framework’s implications.

Advisor / supervisor