Document Type



Doctor of Philosophy (PhD)


Civil Engineering

First Advisor's Name

Ali Mostafavi

First Advisor's Committee Title

Committee Co-Chair

Second Advisor's Name

Ioannis Zisis

Second Advisor's Committee Title

Committee Co-Chair

Third Advisor's Name

Atorod Azizinamini

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Ton-Lo Wang

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

Edward Jaselskis

Fifth Advisor's Committee Title

Committee Member


Resilience, System-of-Systems, Metanetwork, Simulation, Complex Construction Projects

Date of Defense



Uncertainty is a major reason of low efficiency in construction projects. Traditional approaches in dealing with uncertainty in projects focus on risk identification, mitigation, and transfer. These risk-based approaches may protect projects from identified risks. However, they cannot ensure the success of projects in environments with deep uncertainty. Hence, there is a need for a paradigm shift from risk-based to resilience-based approaches. A resilience-based approach focuses on enhancing project resilience as a capability to cope with known and unknown uncertainty. The objective of this research is to fill the knowledge gap and create the theory of resilience in the context of complex construction project systems.

A simulation approach for theory development was adopted in this research. The simulation framework was developed based on theoretical elements from complex systems and network science. In the simulation framework, complex projects are conceptualized as meta-networks composed of four types of nodes: human agents, information, resources, and tasks. The impacts of uncertainty are translated into perturbations in nodes and links in project meta-networks. Accordingly, project resilience is investigated based on two components: project vulnerability (i.e., the decrease in meta-network efficiency under uncertainty) and adaptive capacity (i.e., the speed and capability to recover from uncertainty). Simulation experiments were conducted using the proposed framework and data collected from three complex commercial construction project cases. Different scenarios related to uncertainty-induced perturbations and planning strategies in the cases were evaluated through the use of Monte Carlo simulation.

Three sets of theoretical constructs related to project resilience were identified from the simulation results: (1) Project vulnerability is positively correlated with exposure to uncertainty and project complexity; (2) Project resilience is positively correlated with adaptive capacity, and negatively correlated with vulnerability; (3) Different planning strategies affect project resilience either by changing the level of vulnerability or adaptive capacity. The effectiveness of a planning strategy is different in different projects. Also, there is a diminishing effect in effectiveness when adopting multiple planning strategies. The results highlighted the significance of the proposed framework in providing a better understanding of project resilience and facilitating predictive assessment and proactive management of project performance under uncertainty.





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