Abstract:
Objective: The objective of the article is to identify, assess, and classify complexity indicators based on the impact level of their emergence behaviour during mega infrastructure construction Research Design & Methods: The study adopted a quantitative methodology using an online questionnaire survey to gather data, analysed using exploratory factor analysis. Findings: Task difficulty, dispersed remote teams, multiple project locations, and project scope were identified as structural complexity indicators that surged extreme difficulty. In comparison, project duration, project tempo, construction method, and uncertainty in methods were found to trigger uncertainty during mega infrastructure construction. Implications & Recommendations: This study lays foundation for theoretical exploration of an important phenomenon in the global economy, i.e. development of mega-infrastructure projects. The contextualization of the study in Sub-Saharan Africa builds knowledge of complexity of such projects in an under-researched context. Practically, the results enable project managers to create tools and frameworks to assess overall project complexity level, evaluate their competence incongruent to the complexity inherent in a project, and select appropriate management strategies that contain complexity effects during infrastructure construction. Contribution & Value Added: The study provides a foundation for extensive research into infrastructure project complexity in Sub-Saharan Africa. Additionally, it provides insights to businesses willing to explore Public-Private infrastructure initiatives in Sub-Saharan Africa.
