A theoretical framework for classifying project complexity at the preconstruction stage using cluster analysis techniques

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Journal / PublicationEngineering, Construction and Architectural Management
Online published25 Aug 2021
Publication statusOnline published - 25 Aug 2021

Abstract

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.

Research Area(s)

  • Clustering analysis, Construction project complexity, Pre-construction stage, Staffing allocation

Citation Format(s)

A theoretical framework for classifying project complexity at the preconstruction stage using cluster analysis techniques. / Sing, Michael C.P.; Edwards, David J.; Leung, Arthur W.T.; Liu, Henry; Roberts, Chris J.

In: Engineering, Construction and Architectural Management, 25.08.2021.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review