- Title
- A theoretical framework for classifying project complexity at the preconstruction stage using cluster analysis techniques
- Creator
- Sing, Michael C. P.; Edwards, David J.; Leung, Arthur W. T.; Liu, Henry; Roberts, Chris J.
- Relation
- Engineering, Construction and Architectural Management Vol. 29, Issue 9, p. 3754-3774
- Publisher Link
- http://dx.doi.org/10.1108/ecam-09-2020-0726
- Publisher
- Emerald
- Resource Type
- journal article
- Date
- 2022
- Description
- Purpose: The accuracy and reliability of subjectively assessing a construction project's complexity at the pre-construction stage is questionable and relies upon the project manager's tacit experiences, knowledge and background. The purpose of this paper is to develop a scientifically robust analytical approach by presenting a novel classification mechanism for defining the level of project complexity in terms of work contents (WCs), scope, building structures (BSs) and site conditions. Design/methodology/approach: Empiricism is adopted to deductively analyze variables obtained from secondary data within extant literature and primary project data to develop project type classifications. Specifically, and from an operational perspective, a two-stage “waterfall process” was adopted. In stage one, the research identified 56 variables affecting project complexity from literature and utilized a structured questionnaire survey of 100 project managers to measure the relevance of these. A total of 27 variables were revealed to be significant and exploratory factor analysis (EFA) is adopted to cluster these variables into six-factor thematic groups. In stage two, data from 62 real-life projects (including the layout and structural plans) were utilized for computing the factor score using the six-factor groups. Finally, hierarchical cluster analysis (HCA) is adopted to classify the projects into collected distinctive groups and each of a similar nature and characteristics. Findings: The developed theoretical framework (that includes a novel complex index) provides a robust “blueprint platform” for main contractors to compile their project complexity database. The research outputs enable project managers to generate a more accurate picture of complexity at the pre-construction stage. Originality/value: While numerous research articles have provided a comprehensive framework to define project complexity, scant empirical works have assessed it at the pre-construction stage or utilized real-life project samples to classify it. This research addresses this knowledge gap within the prevailing body of knowledge.
- Subject
- construction project complexity; clustering analysis; staffing allocation; pre-construction stage
- Identifier
- http://hdl.handle.net/1959.13/1465383
- Identifier
- uon:47261
- Identifier
- ISSN:0969-9988
- Language
- eng
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