The present research tries to promote circularity in steel structures by attempting to further incorporate technologies like BIM, the Internet of Things (IoT), and Blockchain in the AEC industry. BIM is already applied in construction projects but not yet focused on aspects that will enhance the reusability of steel structures. IoT and Blockchain, on the other hand, are implemented with success in other industries and according to researchers have the potential to add value to the AEC industry as well. The Design Science Research approach is used to develop a framework that will indicate what information should be registered in order to improve the decision making towards reuse when the structure has reached its end of life. During the different phases of a project and specifically the design, construction, operational, and maintenance phase various characteristics of the structure were indicated for registration. Moreover, a detailed roadmap on how they would be registered in each technology, what they would offer to the reuse process, and who is responsible for inserting them. To examine the soundness of the framework, it was validated through semi-structured interviews with experts from the AEC industry.

This research investigates how to break through intra-organizational data silos in multinational engineering companies by analyzing data sharing networks. Data occurs in many ways like numbers, statistics, and documents in structured and unstructured forms. Companies consider data as one of their most valuable assets for decision-making and to increase performance. Still, often they do not see the direct results of their data-driven investments back into the organization. The volume of generated data increases so rapidly that it exceeds our capabilities if not managed well, leading to organizational data silos. Engineering companies have to deal with unique and complex projects, temporary teams, fragmented departments, and lots of unstructured data. Multicultural teams that work from dispersed locations increase the probability of miscommunication and misinterpretation of project data. Data sharing between employees of three selected case projects within one multinational portfolio have been analyzed. First, the quantitative social network analysis in Python programming exposed the structures of and the node types in the data-sharing networks. Secondly, supported by the extensive literature review, qualitative in-depth interviews identified enabling and limiting factors that determine intra-organizational data sharing in the project life cycle. It was found that balanced networks contribute the most to the exploration and exploitation of intra-organizational data. Also, the multinational context is not acknowledged to limit data sharing, but weaker links do exist between geographically dispersed teams. Measures to create and maintain balanced data sharing networks are suggested on organizational, portfolio, and project level. Future research can focus on network dynamics over time, the effect of data sharing on project success criteria, and the effect of cultural dimensions on data sharing behavior.

The objective of this research is to explore the possibilities in the use of digital twins towards the maintenance and operation of tunnels. This is explored by looking at the end users of the technology, to profile their needs and requirements and consider a digital twin design that focuses on this. This research is the start of a human centred design for a digital twin and provides the opportunity for further investigation of applications and discussion of their usefulness. To map out the functional needs of facility managers within the Dutch tunnel sector, ten interviews were compiled. These interviews are based on digital twin literature in other sectors. The discovered needs within the interviews are analysed for patterns and compared to the characteristics of digital twins. This comparison is validated through a focus group with two digital twin experts and is done to consider if digital twins may offer opportunities for the needs mentioned. It is found that for a large majority of the identified functional needs of facility managers requires the mirror like characteristic of a digital twin, when focusing on the needs related to tunnel behaviour. A digital twin that is designed for the identified needs, should focus primarily on decision supporting services for these facility managers, in other words, providing them with relevant data about the tunnel, at the right time and in a comprehensive manner. An indication is given towards seven digital twin implementations that could benefit a tunnel facility manager. The first two are the monitoring of energy use, and monitoring the health of the tunnel system. It is concluded that energy use should be accounted for in a digital twin, and that the monitoring of system health is required for the quick understanding of problems in the tunnel and stakeholder management. The next three are predictive applications: predicting dependent relations between technical tunnel systems, maintenance scheduling, and operational simulations. These applications help anticipate risks during tunnel processes and provide opportunities for reaching better informed decisions regarding maintenance tasks, problem management and configuration management practices. One application, namely energy optimisation, can be considered fully autonomous, as such is not for decision support, but rather for tunnel optimisation, towards the control of energy use of tunnel technical installations.