Navigating through the unknown: How conjoint analysis reduces uncertainty in energy consumer modelling

Decisions are always central to system dynamics (SD) models (Sterman, 2000), and whether it comes to consumers, managers or politicians, modelling their decisions is always challenging. Decisions are subject to various considerations that go beyond pure rational considerations (Kahneman, 2003; Tversky & Kahneman, 1974). Incorporating ‘soft’ variables in decision modelling is a key strength of SD models (Forrester, 1980; Sterman, 2018). Nevertheless, integrating behavioural and cognitive influences in a quantitative model remains challenging as the actors' preferences are often unknown. Measuring soft variables is challenging and requires careful consideration by the modeler. Therefore, it is important to select methods that help us quantify decision determinants of consumers, managers or politicians, in order to enhance decision modelling and ultimately provide recommendations for relevant problems.