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

PurposeThe 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/approachEmpiricism 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.FindingsThe 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/valueWhile 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.

Automated summary

This study proposes a novel classification mechanism to define project complexity in a scientific and robust manner, focusing on work contents, scope, building structures, and site conditions. The research enables project managers to have a more accurate understanding of complexity at the pre-construction stage.