Ex-ante assessment of vulnerability to uncertainty in complex construction project organizations

Modern construction projects are operated in extremely uncertain environments. Uncertainties affect the performance of projects. Despite an extensive body of literature in the area of performance assessment, there is a gap in knowledge pertaining to an integrated methodology for ex-ante evaluation of vulnerability of project organizations to the impacts of uncertainties. The objective of this paper is to address this gap in knowledge by creating a framework for ex-ante assessment of vulnerability in construction project organizations. In the proposed framework, construction project organizations are conceptualized as complex meta-networks and analyzed using dynamic network analysis. Accordingly, the impacts of the uncertain events (e.g., late design deliverables, equipment breakdown, safety accident and injury, and severe weather conditions) are translated into perturbations in different node entities (i.e., human agent, information, resource and task) and the corresponding links in project meta-networks. These uncertainty-induced perturbations cause transformations in the project topological structure, and thus, negatively affect the efficiency of project organizations’ meta-networks. The extent of the variation in the efficiency is used as an indicator of a project organization’s vulnerability to uncertainties. The application of the proposed framework is shown in a numerical example related to a tunneling project. Various scenarios related to different uncertain events were simulated to quantitatively investigate the vulnerability of the project and evaluate the impacts of different planning strategies on mitigating vulnerability. The results demonstrate the capability of the proposed framework for quantitative assessment of vulnerability and evaluation of planning strategies in construction projects. Hence, it provides a tool for proactive evaluation and mitigation of vulnerability in construction project organizations.

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