To meet EU climate goals, reducing fossil fuel use is crucial, and transitioning domestic energy consumption to sustainable sources like heat pumps offers a potential solution. However, uptake in Flanders remains low. This study explores predictors of heat pump adoption intention among Flemish homeowners using a mixed-methods approach. A quantitative survey based on an extended Theory of Planned Behaviour model (Study 1, n = 692, M_age = 55.03, SD_age = 15.54, male/female = 335/357) is complemented by semi-structured interviews with homeowners who do not own a heat pump (Study 2, n = 16, M_age = 41, SD_age = 35, male/female = 8/8). Study 1 indicates that perceived behavioural control and subjective norms positively influence heat pump adoption intention, with perceived behavioural control enhanced by product knowledge and technological innovativeness. Surprisingly, a positive attitude towards heat pumps is associated with a lower adoption intention. Study 2 reveals cost concerns, uncertainties about energy cost savings and property value increases as barriers to adoption intention, alongside a temporal disconnect between attitude and intention due to practical constraints. Our findings offer suggestions for communication strategies of policy makers such as addressing financial and practical barriers, mitigating practical constraints and enhancing public knowledge. Lastly, our survey results suggest the presence of yet unidentified moderating variables affecting the attitude-intention relationship, which could be determined in future research.

Households equipped with flexible technologies, such as electric vehicles, can support the energy transition by shifting electricity consumption to times of high renewable supply and by preventing consumption peaks that cannot be covered by existing grid and generation infrastructure. Demand response services support households in performing these consumption shifts. Households ask for specifications of services that stand partly in contrast to each other. For instance, while electric vehicle owners tend to insist on retaining control over their charging, others prefer data-driven automation to minimize their active involvement. Recent studies exploring the acceptance of demand response services focused either solely on specific household groups (e.g. electric vehicle users) or on a broad representative sample without further differentiation. Complementarily to fill this gap, we examine differences in preferences for contrasting service designs between household groups. Specifically, we consider: (i) the type of flexible technology to which demand response is applied, and (ii) the adoption level, i.e., whether the households plan to, or currently own, a flexible technology. In a vignette survey, we examine the preferences towards four contrasting service designs with German households that either own or have expressed interest in acquiring a flexible technology (n = 962). Our results show that the preferences do not fundamentally differ between the kind of flexible technology and adoption level. Generally, participants prefer automated demand response services with data sharing. The added value of realizing energy cost savings effectively and efficiently stands out as the main driver for the diffusion of demand response services, outweighing data privacy concerns. Contrary to our expectations, electric vehicle owners did not show a special need for control and households not yet owning flexible technologies did not express a need for little effort. We discuss the implications of our findings for demand response service providers and outline pathways of future research in this domain.

Since heating-related energy consumption is one of the main sources of greenhouse gas emissions and accounts for a large part of domestic energy use in Europe, reducing heating-related energy consumption has great potential to reduce Europe’s greenhouse gas emissions. This study examines which factors determine people's intention to decrease heating-related energy usage, specifically lowering the temperature in winter. It was part of a larger European project focused on promoting energy reduction. This study presents a smaller-scale model tested among 363 individuals from five pilot countries, i.e., Belgium (n = 58), Croatia (n = 82), Germany (n = 105), Greece (n = 33), and Portugal (n = 85). We applied three robust theoretical frameworks: the Theory of Planned Behaviour, the Value Belief Norm Theory, and the Prototype Willingness Model. We conducted a confirmatory factor analysis to ensure construct validity, followed by a structural equation model. Our findings suggest that willingness (from the Prototype Willingness Model) is the most important predictor in explaining someone’s intention to reduce heating-related energy consumption. Additionally, perceived behavioural control, subjective norms, and attitudes (part of Theory of Planned Behaviour) also play an important role in predicting the intention to reduce energy consumption. Lastly, personal moral norms (from the Value Belief Norm Theory) have a significant impact, but their effect is moderate compared to the other predictors.

Electric vehicle (EV) users who aim to become flexibility providers face a tradeoff between staying in control of charging and minimizing their electricity costs. The common practice is to charge immediately after plugging in and use more electricity than necessary. Changing this can increase the EV’s flexibility potential and reduce electricity costs. Our extended electricity cost optimization model systematically examines how different changes to this practice influence electricity costs. Based on the Prospect Theory and substantiated by empirical data, it captures EV users’ tradeoff between relinquishing control and reducing charging costs. Lowering the need to control charging results in disproportionally large savings in electricity costs. This finding incentivizes EV-users to relinquish even more control of charging. We analyzed changes to two charging settings that express the need for control. We found that changing only one setting offsets the other and reduces its positive effect on cost savings. Behavioral aspects, such as rebound effects and inertia that are widely documented in the literature, support this finding and underline the fit of our model extension to capture different charging behaviors. Our findings suggest that service providers should convince EV-users to relinquish control of both settings.

Aligning prosumers' electricity consumption to the availability of self-generated electricity decreases CO₂ emissions and costs. Nudges are proposed as one behavioral intervention to orchestrate such changes. At the same time, fragmented findings in the literature make it challenging to identify suitable behavioral interventions for specific households and contexts - specifically for optimizing self-consumption. We test three sequentially applied interventions (feedback, benchmark, and default) delivered by digital tools in a field experiment with 111 German households with rooftop-photovoltaics. The experiment design with a control-group, baseline measurements, and high-frequency smart-meter-data allows us to examine the causal effects of each intervention for increasing self-consumption. While feedback and benchmark deliver small self-consumption increases (3–4 percent), the smart changing default leads to a 16 percent increase for active participants. In general, households with controllable electric vehicles show stronger effects than those without. For upscaling behavioral interventions for other prosumers, we recommend interventions that require little interaction and energy literacy because even the self-selected, motivated sample rarely interacted with the digital tools.