Although digitalization has become a prospect that is counted on for many problems in the construction industry, there have been limited attempts at exploring decision-making processes in construction firms concerning the integration of digital technologies and impacts beyond the projects. In this research, the system dynamics (SD) approach was proposed to investigate digitalization as a strategic decision considering the inherent relationships between project company and business levels. The SD model was conceptualized, formulated, and tested by conducting a demonstrative case study within a modular construction company. Conforming to the strategic priorities of the case company, business process engineering principles were adopted to model the existing practices and assess the impacts of implementing digital technologies such as building information modeling (BIM), enterprise resource planning (ERP), and radio frequency identification (RFID) at different maturity levels. The simulation tests revealed that the impacts of technologies are influenced by the internal dynamics of projects and company competencies as well as external uncertainties. The SD model has the potential to improve strategic decision-making by anticipating the causalities and feedback between the decisions and consequences of technology integration. The findings and model development steps proposed in this paper can be used by other companies that aim to make process improvements with digital technologies as well as researchers exploring the implications of digitalization in construction considering competencies and uncertainties.

Risk assessment in projects requires the integration of various information on project characteristics as well as external and internal sources of uncertainty and is based on assumptions about future and project vulnerability. Complexity is a major source of uncertainty that decreases the predictability of project outputs. In this research, the aim was to develop a decision-support tool that can estimate the level of risk and required contingency in a project by assessment of complexity factors as well as contextual information such as contract conditions and mitigation strategies. A process model and a tool were developed using the data of 11 mega construction projects. The tool was tested on a real project, and promising results were obtained about its usability. The tool has the potential to support decision-making during bidding in construction projects with its visualization and prediction features. On the other hand, as a limited number of cases and experts were involved in this study, findings on its performance cannot be generalized. The identified complexity and risk factors, proposed process model, and visual representations may help the development of similar decision-support tools according to different company needs.

Complexity is the property of a project that makes it difficult to understand, foresee and control its behaviour due to interrelatedness between various project attributes such as tasks, parties, disciplines, and interfaces. Project complexity is an inherent part of mega construction projects due to their large scale, long period, the multiplicity of disciplines, the high number of stakeholders, multi-nationality, and high level of public attention, as well as political interest. This paper depicts findings of a research project that aims to identify characteristics of and factors that contribute to project complexity by referring to the experiences of professionals involved in mega construction projects. For this purpose, data has been collected by interviewing 18 participants from 11 mega construction projects. Communication complexity, which reflects the amount of distributed communication channels between various stakeholders, has been identified as one of the major drivers of project complexity in megaprojects. Based on literature and semi-structured interview findings, a causal structure to represent communication complexity comprising of three components, which are; project, stakeholders, and communication management, was developed. The causal map, which represents the opinions of a limited number of experts, cannot be generalised; however, it can provide useful insights about drivers of communication complexity that can be used to develop strategies to manage complexity.