The use of qualitative and quantitative methods to enhance occupant behaviour research in developing countries

Mateus Bavaresco
Enedir Ghisi, Coorientadora: Simona D'Oca

This research aims to assess occupant behaviour in offices using qualitative and quantitative approaches and propose alternatives to encourage similar evaluations in developing countries. For doing so, the method applied is divided into three main steps: literature reviews, a case study based on qualitative data collection, and a case study relying on quantitative measurements. The first literature review focused on innovative technologies to quantitatively assess the human dimension of building performance, and the following innovations were highlighted: Cyber-Physical Systems, behavioural sensing, Kinect technology, Internet of Things, human-in-the-loop, virtual reality, and immersive environments. Then, also based on advances from the literature, the challenges and opportunities of using the following social science methods to provide qualitative background for this field are presented: questionnaires, interviews, brainstorming, post-occupation evaluations, personal diaries, elicitation, ethnography, and cultural probes. The qualitative case study carried out in Florianópolis evidenced the feasibility of behavioural theories (Theory of Planned Behaviour and Social Cognitive Theory) to evaluate adaptive behaviours through structural equation modelling – a novel approach in this field. Furthermore, the analysis of subjective and comfort-related drivers for occupant behaviour confirmed the relationship between building adjustments and multi-domain comfort conditions. In other words, although environmental variables linked to different comfort domains (visual, thermal, acoustic, and air quality) impact occupant behaviour, such adjustments can also characterise new sources of discomfort. Then, the quantitative case study relied on six-year continuous monitoring carried out in offices in Perugia, Italy. Based on Information Theory concepts and deep learning algorithms, a method to determine the minimum duration of window operation monitoring that leads to reliable models was proposed. The results indicated that the colder seasons (winter and autumn) are less informative and, therefore, field monitoring with more significant influence from these seasons is more likely to result in underperforming models. The conclusions of this thesis outlined the importance of using qualitative and quantitative methods as their outcomes are complementary. By gathering occupant-related data using different approaches, building stakeholders can understand subjective and objective aspects that affect human-building interactions, as well as determine possible strategies to optimise building design and control. Indeed, this thesis provided detailed documentation of different approaches, and building stakeholders from developing countries can benefit from the highlighted opportunities and recommendations to boost occupant behaviour research in those countries. 

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