This research intended to understand the effect of renovation solutions on occupants’ behaviour, and the effects of the behaviour on the indoor environmental quality of the buildings. The investigation is based on the findings from a short, in-depth monitoring campaign in four apartments in the Netherlands. The results showed that the households studied have different preferences for comfort, as well as ways to interact with the building. The small range of options provided by the systems created some level of dissatisfaction in three out of the four households studied regarding temperature (control), air quality, or noise produced by mechanical ventilation system. The monitoring results confirmed that the apartments were within a good range of thermal comfort, however the residents complained about lack of control over the indoor environment. Furthermore, high CO₂ levels were found in three of the four apartments, especially at night. In these homes, the residents kept the ventilation setting on the lowest due to the noise produced by it, or due to lack of knowledge on the functioning of the system. In addition to the lack of control and lack of knowledge, the residents reported a lack of feedback from the Heating Ventilation and Air Conditioning systems to know whether they are working correctly. These results emphasize the need of user-centric design, and the need for people to be able to control their environment. Systems design should consider the actual needs and preferences of the occupants, while interfaces should be designed to provide timely and accurate feedback to the user.

In this paper, we develop a comprehensive behaviour model for residential buildings that considers the diversity among households. While existing behavioural theories from social and psychological sciences have been used in building research, they often lack technical detail, contextual aspects, and focus primarily on behavioural change. The authors propose an interdisciplinary theoretical model that integrates insights from behavioural science and engineering dimensions. This model aims to link measurable drivers directly to energy outcomes, consider building-related contexts, and reflect the complexity of high-performance buildings. The research consisted of the quantitative analysis of building monitoring data and the analysis of interviews using thematic analysis. The mix-methods approach allowed to obtain new insights into the relationship between the aspects that affect occupants' behaviour. An interdisciplinary model is developed based on the results from the analysis, existing theoretical models used in building research, and previous studies on occupants' behaviour. The model is intended to support the identification of occupants' behaviour drivers, inform user-centric and energy-efficient building design, enhance decision-making for building monitoring and simulations, and aid in various practical applications such as performance assessment and energy contracting.