Identifying and assessing complexity emergent behaviour during mega infrastructure construction in Sub-Saharan Africa

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: online questionnaire survey to gather data and Exploratory Factor Analysis (EFA) to analyse data. Findings: Task difficulty, dispersed remote teams, multiple project locations, and project scope were identified as structural complexity indicators that surged extreme difficult to project managers. In comparison, project duration, project tempo, construction method, and uncertainty in methods were found to trigger uncertainty during construction. Implications & Recommendations: This study lays foundation for theoretical exploration of an important phe-nomenon in the global economy, i.e. the development of mega infrastructure projects in developing countries. The contextualization of the study in Sub-Saharan Africa builds knowledge of such project complexity in an under-researched context. Practically, the results enable managers to create tools and frameworks to assess overall project complexity level and evaluate their competence incongruently to complexity to select appro-priate complexity management strategies. Policy makers are informed about factors which can impede execution of mega infrastructure projects, thus they adjust risk assessment in such projects and better allocate resources to facilitate sustainable development of developing economies. Contribution & Value Added: The study provides a foundation for extensive research into infrastructure complexity in Sub-Saharan Africa. Additionally, it provides insights to parties willing to explore Public-Private infrastructure initiatives in the region.