This research investigates the influence of socio-technical factors on the evacuation performance of university buildings. While prior studies have examined individual factors affecting evacuation, this thesis adopts a comprehensive socio-technical systems perspective, by considering the interactions of social, structural, and technical components within the complex context of university building evacuation systems.

To explore this, an agent-based simulation model was developed using NetLogo. The model simulates evacuation scenarios in two structurally different campus buildings at TU Delft: the Applied Sciences building and the Civil Engineering & Geosciences building. The key variables studied were familiarity with the building layout and exits, social influence behaviour, egress width, and signage. Evacuation performance was assessed using three metrics: 75% evacuation time, mean density, and exit choice.

Following a full factorial simulation experiment of 54 different scenarios per building totalling 10800 individual runs, a standardised ranking was created to equitably rank the scenarios based on their relative evacuation time, density, and exit choice, to determine the performance of the factors. A general linear model was created to determine the effect size of both the individual factors and all possible interactions.

The simulation results demonstrate that familiarity and egress width had the most significant impact on evacuation efficiency. In buildings with limited exits, egress width outweighed the effect of familiarity. While signage and social influence showed modest or statistically non-significant impacts overall, signage became more effective in low-familiarity contexts. The effect of social influence appeared to be sensitive to its level of formalisation in the model, underscoring its context-dependent nature.

Strengths of this study lie in the multi-metric perspective on evacuation performance, the use of multiple buildings to test effects in different structural environments, the possibility to include all possible interactions through a full factorial design, and the adaptability of the simulation model. Also, this study has several limitations, namely the balance between model correctness and performance, the difficulty to detect behavioural patterns, and software-based limitations.

From a policy perspective, the findings suggest that improving occupant familiarity with building layouts, through orientation, drills, or signage, can substantially improve evacuation performance. Furthermore, structural adjustments such as widening exits can mitigate congestion in critical zones, although its effect is dependent on hallway width. Although advanced signage technologies offer some improvements, their individual effectiveness is limited without complementary strategies.

The study highlights the importance of addressing evacuation preparedness as a multi-factorial challenge, especially in complex university settings where population heterogeneity and architectural diversity intersect. The model and methodology offer a flexible tool for future research and scenario testing.