Developing a project complexity measure using Structural Equation Modelling and Fuzzy AHP

In today’s global economy, characterised by variable demand and complex project environments, project managers face significant challenges in assessing project complexity and mitigating risks. This study addresses the problem of effectively measuring project complexity, offering an innovative methodology that combines Structural Equation Modelling (SEM) and the Fuzzy Analytical Hierarchy Process (FAHP) to provide a comprehensive approach. The research follows a two-stage methodology. The first stage applies SEM to model the interrelationships between key organisational complexity factors. In the second stage, the Project Complexity Rank (PCR) is introduced, utilising FAHP to handle uncertainty in project assessments. To validate the SEM model, a survey was conducted with 150 project management professionals. The outcomes from SEM were then used as inputs for FAHP, generating PCR-based rankings to assess and compare project complexity. The methodology was successfully applied at an educational institute to evaluate ongoing projects. Judgements from the Project Director, Manager, and team, based on SEM-derived criteria, were collected to calculate the PCR rankings. The findings reveal that project size, variety, and interdependencies are critical factors influencing project complexity. This study contributes to the field of project management by providing a novel hybrid methodology for project complexity assessment. It also advocates for the use of this ranking mechanism to inform organisational structure changes and enhance the management of complex risks.