Developments to promote sustainable mobility require active and effective public participation projects in which the form of participation (e.g., consulting citizens), the objective of the project (e.g. harnessing local knowledge), and the indicators to assess if the project was effective (e.g., participants’ evaluations) are aligned. In practice, this alignment seems to be rare, but scientific research backing up this claim is lacking. For this scoping review, we have collected and analyzed peer-reviewed case studies on public participation projects for sustainable mobility in 14 countries. Per case, we identified forms, objectives, and effectiveness indicators and assessed their level of alignment. Our main findings show a wide variety of participation forms, of which consultation was the most dominant. Cases also often had multiple objectives, and many projects included measures to evaluate their effectiveness. Most relevant and in line with what we assumed, almost all of the projects demonstrated a degree of misalignment between objectives and effectiveness evaluation standards. Although these results do not imply that public participation projects in sustainable mobility are not effective, it does seem to suggest that participation can benefit from a more structured and aligned approach.

Households are crucial in the energy transition, accounting for over 25% of the European Union's energy consumption. To design effective policy measures that motivate households to change their behavior in favor of the energy transition, agent-based models (ABMs) are vital. For ABMs to reach their full potential in policy design, they must appropriately represent behavioral dynamics. One way to accomplish this is by strengthening the fit in ABMs between behavioral determinants (e.g., trust in energy companies) and the behavior of interest (e.g., adopting tariff structures). This study investigates whether a structured behavioral analysis improves this “determinants-behavior-fit.” A systematic review of 71 ABMs addressing household energy decisions reveals that models incorporating a behavioral analysis formalize nearly twice as many behavioral determinants, indicating a more systematic uptake. Subsequently, we find a difference between models focusing on investment-related behaviors (e.g., households buying solar panels) and those examining daily energy practices (e.g., households adjusting charging habits). Models in the first category integrate more social factors when incorporating behavioral analyses, corresponding with the influence of networks and peer effects on investment behaviors. Models in the second category emphasize individual and external factors in response to behavioral analyses, corresponding with the energy practices' habitual and contextual nature. Despite the benefits of a behavioral analysis for improving the determinants-behavior fit in ABMs, only one-third of the studies apply it partially. On top of that, almost half of the studies do not report a rationale for their choice of behavioral determinants. This suggests that many models may not fully capture the behavioral mechanisms underlying household energy decisions, limiting ABMs' potential to inform policymakers. Our findings highlight the need for systematic behavioral assessments in model development. We conclude that collaboration between behavioral scientists and modelers is crucial to accomplish such integration, and we emphasize the importance of allowing sufficient time and resources for meaningful exchange. Future research could further investigate empirical validation of behavioral insights in ABMs and explore how ABM results improve with a better determinants-behavior fit. By bridging behavioral science with computational modeling, ABMs' decision-support power to policymakers can be improved, ultimately accelerating the energy transition.

This theoretical paper aims to unravel the psychological mechanisms explaining how terrorism threat alerts can lead to public underestimation of the risk of a terrorist attack. We discuss, compare and critique a large variety of literature from psychology, public administration, and communication science. We found that throughout the world, people find threat alerts confusing. We provide an extensive psychological explanation of how confusion can lead to optimism bias and, ultimately, to underestimating terrorism threats. Literature suggests implementing three design elements to reduce the confusion that current (leveled) threat alerts create: keep it simple, call for action, and make international agreements for standardization. We discuss these practical design suggestions and give detailed directions for future research to assess the impact of terrorism threat alerts empirically.

Urban areas face an increasing urgency to adapt to climate change, yet adaptation efforts remain insufficient. Addressing this adaptation gap requires an understanding of the psychological mechanisms and contextual influences shaping climate adaptation behaviour. Whereas behavioural scientists have explored citizens’ climate adaptation behaviours, the decision-making of policymakers is often overlooked despite its importance in closing the adaptation gap. To address this, we conducted a behavioural systems analysis to uncover behavioural dynamics that shape policymakers' decision-making, based on 32 semi-struct ured interviews and a workshop with Dutch urban climate adaptation policymakers. Combing thematic and content analysis with behavioural system mapping, our results highlight the importance of an integrated, dynamic system approach to understand psychological and contextual influences on policymakers' decision-making. We identified nine central themes reflecting key behavioural dynamics: reliance on precedents; fragmented roles and responsibilities; habitual thinking based on longstanding processes; policy stringency, clarity and process; conflicting political priorities; importance of individuals; externally-motivated action; illusion of local actor engagement; moving from awareness creation to mainstreaming. Furthermore, analysis of behavioural influences using the Theoretical Domains Framework identified policymakers’ beliefs about consequences, environmental context and resources, and goals as most influential determinants of behaviour. Behavioural system mapping revealed three impactful levers for interventions, namely supporting precedent identification, stimulating information gathering, and boosting mainstreaming processes, to improve decision-making in urban climate adaptation. By integrating behavioural insights and systems analysis, this work proposes a novel approach to analyse contextual, dynamic influences and determinants of behaviour that shape adaptation policymaking. Therefore, it aligns with recent calls from behavioural scientists highlighting the need for systemic approaches in behavioural science.

Low-carbon energy transitions are being increasingly developed at sub-national or regional levels, forming, thus, energy regions. More energy regions have been formed as energy systems become more decentralized, and national governments devolve decision-making power to local authorities. Energy regions have been studied in several countries, but no study has yet overviewed these regions' variety, transition process, and governance approach. It is important to draw lessons for other cases worldwide, like coal and carbon-intensive regions, to understand what type of regions and how they have stimulated their energy transition. Thus, this study investigated i) the concepts of energy regions that have been published and ii) the way energy regions have transitioned in terms of governance arrangements and innovation processes. A systematic literature review was conducted covering forty-seven academic publications and three grey literature reports of energy regions in ten countries. This review covered three academic (sub-)disciplines: i.e. sustainability transitions, regional studies, and innovation studies. Results show five concepts of energy regions: city-regions, peripheralized regions, coal and carbon-intensive regions, learning regions, and renewable energy regions. The formed typology shows the possible transition pathways that regions can follow. Interestingly, only those energy regions that adopted social innovations had the potential to empower their region, its organizations, and its citizens. Finally, recommendations for practitioners in similar regions worldwide are outlined to help overcome obstacles and advance their low-carbon transition.

Research into the impact of innovative sustainable energy experiments and demonstrations is crucial to diversifying, scaling up, and accelerating the sustainable energy transition. Although there is vast research into sustainable energy experiments and demonstrations, research literature offers a fragmented collection of findings. A coherent overview of themes and insights regarding the transformative impact of innovative sustainable energy experiments and demonstrations on sustainable energy systems from the past, present, and near future is lacking and necessary to increase experiments and demonstrations' impact on the sustainable energy transition. The research in this study fills this knowledge gap by providing such an overview and yields novel insights into the organized function and impact of experiments and demonstrations. It spans a broad spectrum of sustainable energy technologies, the empirical domains where these are invented, developed and applied, and the stakeholders involved. The overview is the outcome of a Delphi study in which the insights of 47 international scientific research experts in sustainable energy experiments and demonstrations are bundled and explained. This study presents a thematic overview of the significant insights regarding past and current sustainable energy experiments and demonstrations and outlines a research agenda for the future. Policymakers, practitioners, and scientists can leverage this to inform their sustainable energy policies, business strategies, and research programs.

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.

The installation of solar panels by residential households is vital for the energy transition. However, the rapid uptake of solar panels by households leads to congestion in the electricity grid. Specifically, when the sun shines, these solar panels simultaneously produce a lot of electricity that is fed into the grid, which is inefficient and can destabilize the grid. Consequently, it is better if self-produced solar energy is directly consumed when the sun is shining. Loadshifting involves shifting energy use (e.g., doing laundry) to periods in which energy is produced. This necessitates behavior change within the household, and it is not yet well understood why people struggle to loadshift. To assess the individualistic and contextual factors influencing laundry loadshifting behavior in the Netherlands, we conducted a survey among 283 Dutch households with solar panels. The survey builds on a framework that integrates aspects of the theory of planned behavior and social practice theory. The framework comprises eight factors (sufficiency attitude, user beliefs, know-how, monitoring skills, habits, hassle, practical knowledge provided, and feedback provision by system design), which are quantitatively measured and analyzed. We used multiple regression analysis to explore the collected responses. Results show the relevance of monitoring skills, strong habits, passive user beliefs and practical knowledge for laundry loadshifting behavior. Findings highlight that instead of asking people to adjust to technologies, technologies should support behavior change and understand its intricacies and connections to its broader context. Additionally, it is important to strengthen households' beliefs regarding their active role in the energy system.

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.

Automated vehicles (AVs) may transform not only our travel experience but our complete daily schedules. This study analyses the data from an interactive stated activity-travel survey using latent class cluster analysis to uncover the types and prevalence of schedule changes with AVs. The analysis reveals that the majority of respondents expected little to no changes in their schedules. Importantly however, these responses are correlated with low commitment to the survey, evident in unrealistically short response times to non-central survey parts and simpler representations of their current schedules. The remaining responses reveal significant and varied changes in activities on board and outside travel, and in commute departure times. We conclude that the prevalence of schedule changes may be underestimated in our and possibly other AV studies due to low survey commitment. Our findings also highlight diverse potential motivations behind schedule changes with AVs: while some travellers may desire to free up time for other activities during the day (time saving), others may satisfy an unmet activity need by engaging in on-board activities (time spending). Considering this heterogeneity is crucial in endeavours to quantify the total benefits and costs that automated vehicles will bring to their users.

CO₂ emissions need to be reduced drastically to fight climate change and minimise the further increase of average global temperatures. The decarbonisation of the energy system aims at reducing CO₂ emissions and is thus urgently needed. This transition is facilitated by inter alia switching to renewable energy sources and more efficient technologies. In the past, the energy transition has mostly focused on supply-side measures. However, at least since the publication of the 6th IPCC assessment report, demand-side measures have gained attention. Thereby, the roles individuals play in achieving this transition is recognised as important. This Special Feature is dedicated to exploring the roles of individuals within the energy transition. The nine thematically featured articles provide insights on this topic using different foci and angles, such as the information to guide individuals' behaviour, the influence of media in framing roles, and technology acceptance. To contextualise and synthesise these diverse contributions, this editorial introduction outlines three different, complementary clusters of roles: technology adoption, lifestyle choices, and political action. By theorising users as participants in transitions through diverse practices, we widen the basis for future research to address and incorporate the roles users play in engaging with and shaping these transitions.

In democratic societies, governments cannot act in isolation from public opinion. This is especially true regarding terrorism, where public perception is the instrument targeted by terrorists to achieve their political goals. Nevertheless, governments must also be able to resist public pressure and preserve individual rights. All this suggests that researching public perception of terrorist attacks is crucial. We make an important contribution in this direction by measuring the importance the public assigns to various attributes of terrorist attacks. Using novel methodology (conjoint experiment) and survey data from the UK and The Netherlands (N = 6,315), we find that people are concerned with attacks by immigrants (in the Netherlands), and by individuals acting as part of a terror cell, and with jihadist motivation. Furthermore, past experience with specific terrorist tactics drive preference to address such attacks more than others. In both countries people strongly focus on the severity of attacks, and under-weigh probabilities. The terror attack in the Netherlands in 2019 provided an opportunity to examine perception right after an actual attack. Also there we have found that people’s concerns are driven by experience with specific attacks. A better understanding of terrorism perception can inform policymakers about the gap between optimal strategies to combat terrorism and the expectations of the public.

In the built environment sector, enhancing energy efficiency through energy retrofitting is a key strategy to mitigate climate change. Despite the efforts made by local municipalities to offer technical and financial support, the rate of home energy retrofit remains low. The decision to undertake home energy retrofit is complex for homeowners. It involves high upfront financial and nonfinancial costs, as well as various benefits over the long term. Substantial costs and ambiguous benefits may prevent homeowners from investing in retrofit measures. Moreover, existing research and policy interventions have rarely accounted for the nonfinancial costs of energy retrofitting. Therefore, this study aims to understand homeowners’ evaluation of nonfinancial transaction costs against financial upfront investment costs. To this end, we design a discrete choice experiment, in which recruited homeowners are presented with a series of decision-making scenarios where they must choose their preferred investment option from two alternatives, alongside the option to maintain the current status quo (no investment). For each retrofit package, we provide information on five attributes: upfront investment cost, time investment, disruption during implementation, energy bill savings, and energy independence. Furthermore, we investigate whether scalable behavioural interventions can be designed to boost homeowners' longtermoriented thinking, thereby increasing their tolerance to short-term costs. A treatment is designed to emphasise long-term financial and nonfinancial benefits of energy retrofitting. We expect that boosting long-term thinking will reduce the negative effects of upfront investment cost, time investment, and disruption on individual utilities, thus increasing homeowners’ preferences for energy retrofit investments.

Climate change is one of the biggest global challenges the earth faces. It comes with a need to change the way we produce, supply, distribute and use energy. For this energy transition, we not only need money and technology, we also need a change in behaviour on multiple levels. Psychological perspectives, theories, and research methods are essential to discover behavioural patterns among different stakeholders, varying from end-users, producers, policymakers and installers. This article describes the role of psychology in behavioural research on the energy transition. Furthermore, it describes how research findings are applied in energy policy and technology.

Public and private organisations have several instruments at hand to reduce consumer demand for energy. These instruments can take the form of information campaigns, various subsidy programs, or regulations to encourage consumers to adopt greener technology, develop energy-efficient habits or travel more sustainably. However, the well-intended programs often stumble over people’s unwillingness to change, lack of interest, or limited attention. As part of this workshop, we will introduce an online toolkit developed by the Users TCP Behavioural Insights Platform that helps policymakers consider psychological factors that might affect the success of their policy. In the workshop, participants will learn how use the tool to make energy programs and policies more behaviourally informed and ultimately more likely to succeed.

The complex and uncertain environment of the humanitarian response to crises can lead to data bias, which can affect decision-making. Evidence of data bias in crisis information management (CIM) remains scattered despite its potentially significant impact on crisis response. To understand what biases emerge in complex crises and how they affect CIM, we conducted a combined interview and document analysis study. Focusing on the largest humanitarian crisis in the world, i.e., the conflict in Yemen, we conducted 25 interviews with managers and analysts of response organizations, and assessed 47 reports and datasets created by response organizations in Yemen. We find evidence of a cycle of bias reinforcement through which bias cascades between field, headquarters and donor levels of crisis response. Researchers, as well as practitioners, need to consider these underlying biases and reinforcement loops because they influence what data can be collected when, by whom, from whom, and how the data is shared and used. To the CIM literature, we contribute an in-depth understanding of how four types of data bias emerge in crises: political, accessibility, topical, and sampling bias.

A crisis requires the affected population, governments or non-profit organizations, as well as crisis experts, to make urgent and sometimes life-critical decisions. With the urgency and uncertainty they create, crises are particularly amenable to inducing cognitive biases that influence decisionmaking. However, there is limited empirical evidence regarding the impact of cognitive biases on estimation, judgment, and decision-making tasks in crises. Possible biases occurring in crises are: (1) to be influenced by how information is framed (i.e., framing effect), (2) to overly rely on information that confirms rather than opposes preliminary assumptions (i.e., confirmation bias), (3) to rely heavily on a skewed informational cue when making estimations (i.e., anchoring bias), and (4) to see the own decision-making as less biased than decision-making of others (i.e., bias blind spot). We investigate these four cognitive biases using three online survey experiments targeting crisis-affected people of the general public (n = 460, mTurk workers), governmental and non-profit workers (n = 50, mTurk workers), and crisis experts (n = 21, purposefully sampled). Our findings show that crisis experts are the least biased group but are still significantly affected by anchoring, framing, and bias blind spot. Crisis-affected people from the general public showed the strongest susceptibility to all four biases studied. The findings have implications for future research on crisis information systems (IS) design. As crisis response is increasingly facilitated through IS, we propose debiasing functions that account for biased user behavior in crises.

'Help eigenaren van monumenten en woningen binnen beschermd stadsgezicht bij het verduurzamen op een mooie manier.' Klimaatpsycholoog Gerdien de Vries werkt aan de TU Delft en doet al 10 jaar onderzoek naar het gedoe dat mensen ervaren als ze hun woning willen verduurzamen. Ook zichzelf kon ze tot nu toe niet over die drempel tillen, en dus deed ze nog maar even niks. Maar het is tijd 'to put your money where your mouth is'. Haar eigen woning moet van het gas af. De komende maanden neemt ze ons in haar blog mee op weg naar een gasvrije woning.