Airborne wind energy (AWE) harnesses higher-altitude winds using kites to generate renewable electricity. As AWE technologies move closer to potential commercialization, understanding how local communities interact with and are affected by these technologies is crucial for socially responsible deployment. Identifying key predictors of community acceptance can help develop targeted measures to address potential impacts while the technology is still adaptable. This study tested the Integrated Acceptance Model (IAM) on survey data from two European AWE test sites. A linear regression analysis revealed that two of the five explanatory variables significantly predicted acceptance: perceived site impacts (e.g., sound emissions, landscape changes, and aviation lights), as well as developer transparency and fairness in site operations. In contrast, attitudes toward the energy transition, perceived economic impacts, and social norms did not predict acceptance. These findings suggest that while AWE developers prioritize technical challenges, attention must also be given to social factors, such as minimizing impacts and ensuring transparent and fair implementation. The results also have important policy implications, highlighting the need for AWE-specific regulations and socially responsible planning practices. Further research is required to investigate additional acceptance predictors, especially if AWE technologies continue to develop toward commercial applications.

Public charging points in neighbourhoods are essential for charging electric vehicles (EVs). Efficient use of these shared charging points requires cooperation from neighbours. Communication and agreements between neighbours regarding the use of charging points are important for cooperation, yet have received little attention in research. Therefore, we aimed to explore the extent to which residents communicate with their neighbours about the use of public residential charging points, whether they (want to) make agreements about their use, the types of agreements that they (want to) make, and the social-psychological factors that determine whether they (want to) make agreements. We analysed responses from an online survey of EV drivers in the Netherlands who charge at public residential charging points in their neighbourhood (N = 314). We found that few residents communicate with their neighbours regarding the use of the charging points, such as sending messages via their mobile phone. We identified an intention–behaviour gap for making agreements: although very few residents had made agreements, many more want to do so. Most want to make agreements about communication with their neighbours or about moving a vehicle from the charging point after it has been charged. Residents who made agreements with neighbours perceived greater social interdependence with their neighbours than residents who did not, and interpersonal trust and perceived social interdependence explained wanting to make agreements. We recommend that municipalities and charging point operators inform, encourage, and facilitate EV drivers in making agreements about sharing public residential charging points with their neighbours.

Public charging points are essential for the transition to electric mobility, but there is a lack of knowledge on electric vehicle (EV) drivers’ perceptions of explicit social norms regarding the appropriate usage of these shared charging points. Communicating to EV drivers how other EV drivers believe that public charging points should be used could improve the use of charging points and the development of social norm interventions. Hence, we aim to identify the injunctive norms for sharing public charging points from the perspective of EV drivers. We analysed responses from EV drivers to an open survey question about their perception of appropriate social behaviour at public charging points. We coded responses deductively with a set of previously identified prosocial charging behaviours and inductively to identify additional prosocial charging behaviours. Respondents (N = 246) referred to 11 different behaviours. The main injunctive norm is to move a fully or sufficiently charged vehicle from the charging spot after charging. Two less relevant injunctive norms are interpersonal interactions between EV drivers, such as contacting other charging point users about the charging point by sharing contact details and using apps, and charging only when necessary or only charging the necessary energy. Additionally, for these three injunctive norms, we coded details mentioned by respondents, such as motivations and considerations. We recommend that municipal policymakers and charge point operators make the social context of charging at public charging points salient in their communication, facilitate social interaction, and avoid communication on ambiguous behaviours.

Airborne wind energy (AWE) is an emerging renewable energy technology that uses kites to harvest winds at higher altitudes than wind turbines. Understanding how residents experience a local AWE system (AWES) is important as the technology approaches commercialization. Such knowledge can help adjust the design and deployment of an AWES to fit locals' needs better, thereby decreasing the technology's burden on people. Although the AWE literature claims that the technology affects nature and residents less than wind turbines, empirical evidence has been lacking. This first community acceptance study recruited residents within a 3.5 km radius of an AWE test site in Northern Germany. Using structured questionnaires, 54 residents rated the AWES and the closest wind farm on visual, sound, safety, siting, environmental, and ecological aspects. Contrary to the literature's claims, residents assessed the noise, ecological, and safety impacts similarly for the AWES and the wind farm. Only visual impacts were rated better for the AWES (e.g., no shadows were perceived). Consistent with research on wind turbines, residents who rated the site operation as fairer and the developer as more transparent tended to have more positive attitudes towards the AWES and to experience less noise annoyance. Consequently, recommendations for the AWE industry and policymakers include mitigating technology impacts and implementing evidence-based strategies to ensure just and effective project development. The findings are limited to one specific AWES using soft-wing kites. Future research should assess community responses across regions and different types of AWESs to test the findings' generalizability.

Residential public charging points are shared by multiple electric vehicle drivers, often neighbours. Therefore, charging behaviour is embedded in a social context. Behaviours that affect, or are influenced by, other public charging point users have been sparsely studied and lack an overarching and comprehensive definition. Consequently, very few measures are applied in practice to influence charging behaviour. We aim to classify and define the social dimension of charging behaviour from a social-psychological perspective and, using a behaviour change framework, identify and analyse the measures to influence this behaviour. We interviewed 15 experts on residential public charging infrastructure in the Netherlands. We identified 17 charging behaviours rooted in interpersonal interactions between individuals and interactions between individuals and technology. These behaviours can be categorised into prosocial and antisocial charging behaviours. Prosocial charging behaviour provides or enhances the opportunity for other users to charge their vehicle at the public charging point, for instance by charging only when necessary. Antisocial charging behaviour prevents or diminishes this opportunity, for instance by occupying the charging point after charging, intentionally or unintentionally. We then identified 23 measures to influence antisocial and prosocial charging behaviours. These measures can influence behaviour through human–technology interaction, such as providing charging etiquettes to new electric vehicle drivers or charging idle fees, and interpersonal interaction, such as social pressure from other charging point users or facilitating social interactions to exchange requests. Our approach advocates for more attention to the social dimension of charging behaviour.

Airborne wind energy (AWE) systems use tethered flying devices to harvest higher-altitude winds to produce electricity. For the success of the technology, it is crucial to understand how people perceive and respond to it. If concerns about the technology are not taken seriously, it could delay or prevent implementation, resulting in increased costs for project developers and a lower contribution to renewable energy targets. This literature review assessed the current state of knowledge on the social acceptance of AWE. A systematic literature search led to the identification of 40 relevant publications that were reviewed. The literature expected that the safety, visibility, acoustic emissions, ecological impacts, and the siting of AWE systems impact to which extent the technology will be accepted. The reviewed literature viewed the social acceptance of AWE optimistically but lacked scientific evidence to back up its claims. It seemed to overlook the fact that the impact of AWE’s characteristics (e.g., visibility) on people’s responses will also depend on a range of situational and psychological factors (e.g., the planning process, the community’s trust in project developers). Therefore, empirical social science research is needed to increase the field’s understanding of the acceptance of AWE and thereby facilitate development and deployment.

Design for behaviour change is a young and developing practice grounded in the belief that using insights from the behavioural sciences leads to more effective interventions for behaviour change. Although a wide range of tools, techniques and methods exist to support this, few are well introduced in terms of their underlying values or paradigm for understanding behaviour. As a result, designers are often limitedly aware of why and how methods fit their personal beliefs and way of working. This not only obstructs professional development; it decreases the effectiveness and efficiency of behavioural design. In this paper we present an initial set of heuristics for designers to anticipate the appropriateness of a method, given the task at hand and their preferred way of working. These heuristics have been developed through an analysis and comparison of nine behavioural design methods. We conclude with discussing their potential in framing and staging behavioural design methods and studying method usage.