Thesis subject

Watch your step: the cost of taking a short-cut (MSc)

Use two recently published journal articles as the basis for building a new agent-based model (ABM). The background to the topic of safety culture, systems and behaviours is described in a concept article submitted by Goede and Hofstede (2021). The article by Zhang et al. (2019) provides a description of the work that happens on a construction site, which was used for their ABM. However, we want to superimpose the specific compliance behaviours in the article by Hu et al. (2020), onto our model.

Short description
In the construction work environment there are many reasons why we tend to take shortcuts, resulting in unwanted safety outcomes collectively called incidents. One of the reasons for taking shortcuts that we want to study here is the issue of compliance to the policies, procedures, regulations and rules (collectively called rules) of the organisation. When we do not comply to the rules, we take shortcuts and fall from the site.

The world view is that of a construction site as described by Zhang et al. (2019), see photos above. The workers (agents) are moving around on the site and have to walk on top of the built walls and are not supposed to take shortcuts. That is tiring and time consuming and as a result, some agents will try to take shortcuts to get the work done quickly, when under pressure.

The agents are all members of the construction team. There are three types of agents ranging in seniority in the organisation that are present on this construction site: supervisors, safety officers and operators (worker agents). Supervisors and safety officers move around randomly on the site, only congregating where and when an incident happens. The worker agents move from the central stockyard and the edges, towards the centre and carry and place the pieces of construction material on top of the pillars, slowly increasing the height. What goes wrong is that the agents are not the same and not all are complying. Some agents have a shallow, “surface” compliance and just tick the boxes. They only follow the rules when being watched by bosses, so the more safety officers the better they behave. Other agents have “deep” compliance, fully understanding the safety risks and behave safely, doing whatever it takes to be safe. We aim to model this world playing out in the workplace.


  1. Understand from literature the most important behavioural variables that explain the sociotechnical safety system in high-risk industrial sector
  2. From published data define the relationships, sequences and strengths of variables influencing safety in the workplace using Hu et al. (2020) as a guide to define hypotheses
  3. Construct an agent-based model reflecting the sociotechnical safety system according to Zhang et al. (2019), indicating the role of the identified variables
  4. Present the results comparing shallow and deep compliance behaviours as presented by Hu et al. (2020) and how these relate to safety outcomes
  5. Introduce a slider on the amount of work pressure (to finish quickly, on time, on budget etc.) on the workforce, well described by Dahl and Kongsvik (2018). They used the outcome of mindfulness, a failure of which will result in the same safety incidents

The work in this master thesis entails:

  • To collect similar articles on sociotechnical systems and ABMs and understand the field of research
  • To familiarize yourself with and use the open access Netlogo software (NetLogo Home Page (, which includes a library of example models
  • To use the information provided above and plan, program and run the agent-based model with different configurations to test the hypotheses, provide sensitivity analyses and validate the model
  • To report in detail and assist the supervisors with the writing of an article suitable for publication after the study is completed


  • Dahl, Ø., & Kongsvik, T. (2018). Safety climate and mindful safety practices in the oil and gas industry [Article]. Journal of safety research, 64, 29-36.
  • Goede, J., & Hofstede, G. (2021). Pride and pressure: A systemic perspective on safety. In preparation.
  • Hu, X., Yeo, G., & Griffin, M. (2020). More to safety compliance than meets the eye: Differentiating deep compliance from surface compliance [Article]. Safety science, 130.
  • Zhang, P., Li, N., Jiang, Z., Fang, D., & Anumba, C. J. (2019). An agent-based modeling approach for understanding the effect of worker-management interactions on construction workers' safety-related behaviors. Automation in Construction, 97, 29-43.


  • Recommended courses: Programming in Python (INF-22306), Agent-Based Modelling of complex adaptive systems (INF-34806)
  • Required skills/knowledge: Basic programming skills and interest in safety and human behaviour

Key words: Agent-based modelling, artificial sociality, computational social simulation, sociotechnical systems, safety management, practices, behavioural responses, incidents

Contact persons