Long-term engagement of residents is crucial for demand response management, and thus grid stability in energy systems, but current approaches often fail to maintain or even achieve the necessary changes in consumer behaviour. Thus future customer engagement approaches will have to relate more strongly to customer needs in order to achieve long-term engagement. This study presents an approach based on a central need identified in psychological research, namely the need to belong to a group. A mixed methods approach was used to examine how an energy feedback approach that connects to this need could be designed. First, based on the Theory of Planned Behaviour and Social Identity Theory, a survey was conducted to examine the influence of e.g. norms held by the local social group of neighbours on energy behaviour. In contrast to previous studies on the influence of social groups on sustainable behaviour, no significant influence was found. However, other findings indicated that this was due to the low level of group identity, leading to the assumption that the need for social belonging was not fulfilled in the survey group. Second, focus group discussions were conducted to test this assumption in more detail. Findings from the focus groups confirm the assumption and reveal detailed insights on residential needs for stronger connections between neighbours. We conclude that a local social network could be a suitable solution to the need for local social belonging and, while also providing a context for energy feedback. Thus, implementing a local social network could lead to both persistently engaging energy feedback and also improve human well-being.

Cites have been identified as one key arena to meet future sustainability challenges. However, if cites are to be part of the transition it must become possible to confirm results of ongoing actions. By the introduction information and communication technologies, it has become easier to collect performance parameters from the built environment, thereby enable more detailed evaluation. The aim of this paper is therefore to examine the potential and limitation of using dynamic and high resolution meter data for evaluation of energy consumption in buildings and households. The novelty of this approach is that dynamic and high resolution meter data can increase the level of detail in evaluation results and ease detection of deviations in the structures performance. However, most benefits are found from the occupant perspective, as more detailed evaluation information enable better inclusion of this stakeholder group. Furthermore this study has shown that the commonly used indicator energy use per heated floor area is an insufficient communication tool when taking holistic approach to building energy evaluation. Limitation to full use of dynamic and high resolution meter data have been identified to data collection and management, preservation of personal integrity and incentives to react on the given evaluation information.

Engaged households are needed for the future ‘smart grids’ to function, but it is difficult to engage residents in their household electricity consumption. Building on earlier research suggesting that a local social network could provide a suitable context for energy feedback, this paper examines how feedback presented in a social network should be designed in order to be better understood by the residents and encourage long-term engagement. A review of the literature on design principles and cases where they had been implemented identified 24 principles. A prototype feedback design adapted for a local social network was made, based on design principles deemed suitable for the screens designed. End-user feedback on the prototype was collected through a stakeholder consultation workshop. In the workshop dis- cussions, 17 identified principles were mentioned and there was support for 15 of these, one was both supported and contested and two were contested. Based on comments and suggestions from end-users, a revised version of the feedback prototype was made for implementation in a pilot study in Sweden and Portugal.

Households can provide demand-side flexibility by changing their consumption behaviour and shifting energy-intensive activities – such as vacuuming, cooking or charging electric cars – to off-peak hours. Such behaviour-based demand response management could balance out consumption peaks without the need for costly smart home devices or automation technologies. However, existing research has struggled to motivate consumers to adapt their behaviour or maintain behaviour change over extended periods of time. This field study explored a scalable and cost-effective behavioural demand response tool and investigated its short- and long-term impacts on average and peak hour electricity consumption under realistic conditions: A smartphone app provided users with social comparison feedback on their electricity consumption and invited them to participate in “pause hours” by avoiding energy- intensive activities during peak hours. To appeal even to hard-to-reach energy users and elicit longer-term engagement, the app also contained a neighbourhood newsfeed and was framed as a local social network. In a 15-month trial with 550 student apartments in Sweden, more than half of the residents voluntarily installed the app, many app users stayed engaged over an extended period of time and pause hour participants achieved substantial peak-load consumption reductions of 46% on average. These results indicate that smartphone apps can achieve peak load consumption reduction and long-term engagement, although they may be particularly attractive to already energy efficient households. Avenues for future research are discussed.

Improving households’ waste and recycling behavior is essential for achieving sustainable production patterns. However, the potential for sustainable waste service offerings remains untapped as existing research largely relies on estimated data, short study periods, and unscalable interventions. We conducted a longitudinal field study to investigate the influence of a scalable, app-based behavioral intervention building on social norms on households’ waste and recycling behavior in a multi- residential setting. Using ‘smart’ waste chutes equipped with novel technology to collect objective data for municipal waste (MMW), plastic waste (PW) and newspaper waste (NPW) of 153 households over the course of 12 months, we find that while MMW levels remain stable and do not differ between households that did (vs. did not) install the waste-oriented smartphone app, recycling rates of PW and NPW increased for all households as a function of the intervention. Moreover, app users threw significantly more PW than households not using the app after but not before the intervention. Together, our results suggest that digital behavioral interventions based on novel data through ‘smart’ technologies can significantly improve households’ waste and recycling behavior, thereby presenting a pathway for increasing the service character of waste disposal and management that enables customers’ sustainability practices.