Insights into energy behaviour: Assessments of users’ interactions with energy-efficient technologies

Recent decades have seen rapid development of energy-efficient technologies and designs.However, despite significant effort to ensure that new technologies meet energy-efficiency criteria, thereare discrepancies between predicted and actual energy use. To bridge this gap, it is important that suchtechnologies and designs align with users’ experiences and behaviours. This Ph.D. thesis aims to castlight on how users interact with energy-efficient technologies by focusing on relevant factors influencingusers’ experiences and behaviours in residential and non-residential contexts. The project examinesenergy-efficient technologies at multiple scales, encompassing large-scale solutions such as energy-efficient buildings and small-scale interventions including technical appliances and specific buildingfeatures. The thesis includes a literature review and empirical studies exploring the influence ofpsychological factors (motivation, acceptance, and emotions) on energy-efficient behaviour. Thesefactors were examined through the lens of Self-Determination Theory (SDT; Deci and Ryan, 1985) andthe extended Unified Theory of Acceptance and Use of Technology model (UTAUT2; Venkatesh et al.,2012). The findings highlight the importance of considering key psychological factors as well as users’experiences (e.g., visual comfort and visual satisfaction) for promoting energy-efficient behaviour. Inaddition, the thesis presents methodological advances that can be used to better understand users’interactions with energy-efficient technologies. Collectively, the findings deepen the understanding offactors influencing users’ interactions with energy-efficient technologies. The insights derived from thisthesis can be used to inform the development of advanced energy-efficient technologies tailored tospecific contexts and to users’ psychological factors. Additionally, they can serve as a basis for the designand establishment of regulations that target users’ motivational factors as well as expectancies topromote and sustain energy-efficient practices, thereby reducing the gap between actual and predictedenergy use in energy-efficient buildings.