Bridging the intention-action gap is key to driving sustainable consumer behavior. In this paper, we introduce the Change Factory, a methodology that applies behavioral science to design sustainable product experiences. We detail its four-step CODE framework – Change, Obstacles, Design, and Experimentation – and illustrate its application on fragrance refill. After identifying behavioral barriers, 33 gentle intervention ideas were generated to promote refill adoption, validating the method’s efficacy in translating behavioral insights into concrete, behavior-driven design solutions.

A lack of common terminology and shared understanding of behavioural interventions across academic disciplines and professional groups limits the multidisciplinary application of such interventions and our collective ability to share and compare their effects. The current study attempts to narrow this gap by developing a comprehensive classification system of nudges and similar behavioural interventions that can aid researchers and practitioners in understanding and describing such interventions to steer desired behaviour change. We develop an initial classification system drawing on our expert knowledge and subsequently validate it in an iterative procedure with 44 experts from various fields, disciplines and sectors during two feedback rounds (i.e. a Delphi approach). The result is META BI (Mapping of Environment, Target group and Agent for Behavioural Interventions), a classification system describing interventions across 20 dimensions and using 17 distinct psychological mechanisms. META BI is aligned with a system lens, shifting the focus from single true effects to contextualised assessments. It can help to understand, compare and evaluate nudges and selected interventions for the desired effects.

Physical inactivity is a leading cause globally of noncommunicable diseases such as diabetes, heart attacks, and strokes. Here, we present the results from a 4-week-long experimental test of a nudge designed to promote physical activity among 206 seniors in Abu Dhabi, United Arab Emirates—a population with one of the highest rates of physical inactivity in the world. We find that the “Forever Fit” nudge—a booklet containing a simple exercise program and information about the health benefits of physical activity—has a large positive effect on 93 previously inactive seniors. The nudge increases the time previously inactive participants spend being physically active from about 5 to about 15 minutes per day.

Our daily lives are shaped by the digital platforms we engage with, presenting both challenges and opportunities in the pursuit of health and social well-being. Despite extensive public efforts to increase physical activity, sedentary lifestyles and car-dependence persist; often exacerbated by digital apps functioning at odds with these initiatives. With growing urbanization, walking for transportation becomes a feasible way for many Americans to achieve daily activity goals. This work explores the potential of leveraging nudges within digital apps, specifically Google Maps, to encourage walking. I found that displaying walking directions as the default in Google Maps, instead of driving, and complemented by graphics depicting social norms, significantly increased the hypothetical choice to walk — particularly among less active individuals. This underscores the power of digital environments in shaping our choices and outcomes; and highlights the need for us to critically assess digital app design. I advocate for collaboration between ‘big tech’, policymakers, and the public to create digital tools that balance our immediate convenience with long-term health and environmental sustainability goals. Re-envisioning technology’s role in daily life, we can potentially harness its vast influence to foster choices that contribute to both personal well-being and the collective good.

Possibly the most important argument for the permissibility of choice architecture is the inevitability argument (IA), which states that if choice contexts are to inevitably influence individuals in some way, they should be arranged to best promote their welfare. Opponents point out a moral difference between influence from unmodified environments (including environments designed without any thought given to behavioral influence) and environments modified specifically to produce behavioral effects. Only the latter are said to subvert the will of those affected, and thereby raise concerns pertaining to manipulation, mistreatment of rational agency, etc. We argue, however, that if choice architects can reliably predict the behavioral effects of both the unmodified environment and available alternatives, the moral difference between these environments seems insignificant. In such cases, one version of the IA persists. This version establishes the permissibility of choice architecture in circumstances of reliable prediction, but is itself neutral toward available normative directions.

Sustainable financial investments play a role in mitigating climate change. With this research, we explored how decision-makers use three investment strategies illustrating different primary motives: (1) money maximization (economic self-interest), (2) exclusion (not personally harming the environment), and (3) inclusion (helping the environment most efficiently). The relative use of these strategies was tested within a novel investment paradigm, aiming to artificially create a trade-off between financial payoffs (money maximization), environmental purity (exclusion), and environmental impact (inclusion). We recruited 1422 participants online and let them make ten consecutive investment choices, with incentivized outcomes, both monetary (i.e., potential bonus payment) and environmental (i.e., number of trees planted). We tested the change in investment choices using a between-subject design with four conditions, a control, and one default condition for each investment strategy. The three strategies were chosen about equally often in the control condition, but we find that this investment pattern could be altered by a default intervention. Preliminary evidence suggests that participants primarily using the exclusion and inclusion strategies differ in their moral reasoning. Utilitarianism better predicted the inclusion strategy, whereas high self-importance of moral identity better predicted the exclusion strategy.

Do people like financial nudges? To answer that question we conducted a pre-registered survey presenting people with 36 hypothetical scenarios describing financial interventions. We varied levels of transparency (i.e., explaining how the interventions worked), framing (interventions framed in terms of spending, or saving), and ‘System’ (interventions could target either System 1 or System 2). Participants were a random sample of 2,100 people drawn from a representative Australian population. All financial interventions were tested across six dependent variables: approval, benefit, ethics, manipulation, the likelihood of use, as well as the likelihood of use if the intervention were to be proposed by a bank. Results indicate that people generally approve of financial interventions, rating them as neutral to positive across all dependent variables (except for manipulation, which was reverse coded). We find effects of framing and System. People have strong and significant preferences for System 2 interventions, and interventions framed in terms of savings. Transparency was not found to have a significant impact on how people rate financial interventions. Financial interventions continue to be rated positive, regardless of the messenger. Looking at demographics, we find that participants who were female, younger, living in metro areas and earning higher incomes were most likely to favor financial interventions, and this effect is especially strong for those aged under 45. We discuss the implications for these results as applied to the financial sector.

Viewed from the perspective of public policy, behavioural public policy (BPP) faces challenges in four main areas: Systems, Impatience, Nudging, and Scaling. To address these challenges, several suggestions are proposed. First, understanding how BPP interventions unfold in complex systems requires better diagnostics and the development of predictive and generative models of human behaviour. Second, the rapid pace of policy processes necessitates a shift towards generating timely and fit-for-purpose evidence. Third, maximising the opportunities presented by BPP, beyond merely ‘nudging’, demands the early and proactive application of behavioural science in the policy cycle. Fourth, achieving widespread impact in BPP initiatives means considering scale-up from the start. Lastly, the consistent and comprehensive integration of behavioural science into standard policymaking practices would support sustainable progress in addressing these challenges.

Many real-world intertemporal decisions involve a group of two or more individuals making consensual decisions through group collaboration. Here, we ask how group collaboration affects intertemporal choices. In two experiments, participants completed intertemporal choices individually first (the precollaboration phase). Then, participants were placed into groups of two or three and completed a similar intertemporal task, with the group arriving at a consensual decision on each trial (the group collaboration phase). Finally, participants once again completed the intertemporal choices individually (the postcollaboration phase). Results showed that after group collaboration, the delay discounting significantly decreased compared to before collaboration both at group level and at individual level. The effect of group collaboration on individual intertemporal choices was no longer discernible by 1 week later. Therefore, the current research demonstrates the effectiveness of group collaboration and provides a way to nudge both groups and individuals to make farsighted choices.

We have previously argued thatbehavioral scientists have been testing and advocating individualistic (i-frame) solutions to policy problems that have systemic (s-frame) causes and require systemic solutions. Here, we consider the implications of adopting an s-frame approach for research. We argue that an s-frame approach will involve addressing different types of questions, which will, in turn, require a different toolbox of research methods.

Nudging is a policy tool that steers people’s behavior through noncoercive psychological pushes. This has consequences for people’s lives to varying degrees. For example, the nudge of a sticker of a fly in a urinal encourages peeing inside a urinal, while an organ donation default brings people to agree to donating their organs after their decease. Governments do not yet systematically examine which nudges have to be subjected to all safeguards of the rule of law—for example, parliamentary control, judicial review, or compliance with legal principles such as proportionality. This article argues that a legal doctrine is necessary to carry out this examination. Moreover, it contributes to the development of such a doctrine, using the approach of the European Court of Human Rights as a source of inspiration. The doctrine consists of a “de minimis” principle for nudges: Public institutions only need to ensure that a nudge complies with rule of law safeguards when the nudge has substantial consequences. In addition, the doctrine includes a criterion to determine which nudges have such substantial consequences. In particular, it is argued that a nudge should be subjected to at least some safeguards when it has a serious effect on people’s autonomy.

This study focuses on the development of a creative model of SDGs education that promotes behavior change in upper secondary schools using an approach that combines design thinking and behavioral science nudge methods. The SDGs education for high school students, which utilized design thinking, was used as a case study. Questionnaire surveys of high school students and teachers who participated in the project were conducted. Based on the survey results, a new education model was proposed that can effectively improve SDGs education at the high school level and support educators in this field.

Behavioural public policy (BPP) operates within one of four cultural models of public management, an illustration of an influential scheme set out by Christopher Hood. Even though BPP can be fatalist, individualist or egalitarian, so far it has been hierarchicalist. Hallsworth’s manifesto is largely an expression of this hierarchicalist form of public management, with all its limitations and contradictions. As the manifesto pays relatively little attention to decentralist and egalitarian approaches, it misses a radical opportunity. Future work on BPP could incorporate entrepreneurial and egalitarian possibilities while recognising the difficulties of moving away from hierarchalism completely. Even though Hood cautions against a ‘public management for all seasons’, it remains a plausible path for the next generation of researchers and practitioners of BPP.

This article explains why hyper-engaging dark patterns should be considered unlawful in the European Union even though they are very common online, particularly on content-sharing platforms. A hyper-engaging dark pattern is a digital interface with an addictive design: it makes users spend more time interacting with the service by making use of big data analytics and one or more behavioural trait. Hyper-engaging dark patterns are a form of hypernudge. They exploit the dopamine cycle, reduce users’ autonomy and may have additional detrimental health effects. The Unfair Commercial Practices Directive should be interpreted as prohibiting them either as a form of undue influence or under the general test pursuant to Article 5. Both the Digital Services Act and the Artificial Intelligence Act can play a beneficial but merely complementary role in combatting the diffusion of hyper-engaging dark patterns.

Many philosophical accounts of manipulation are blind to the extent to which actual people fall short of the rational ideal, while prominent accounts in political science are under-inclusive. We offer necessary and sufficient conditions – Suitable Reason and Testimonial Honesty – distinguishing manipulative from non-manipulative influence; develop a ‘hypothetical disclosure test’ to measure the degree of manipulation; and provide further criteria to assess and compare the morality of manipulation across cases. We discuss multiple examples drawn from politics and from public policy with particular attention to recent debates about the ethics and politics of nudge.

Two preregistered web studies are presented that explore the impact of experience on the tendency to accept recommended defaults. In each of the 100 trials, participants (n = 180, n = 165) could accept a recommended default option or choose a less attractive prospect. The location of the options (left or right) was randomly determined before each trial. Both studies compared two conditions. Under Condition Dominant, the default option maximized participants’ payoff in all trials. Under Condition Protective, the default option protected the participants from rare losses and maximized expected return but decreased payoff in most trials. The results reveal a tendency to accept the default in Condition Dominant but the opposite tendency in Condition Protective. This pattern was predicted by assuming that in addition to promoting specific actions, the presentation of the default changes the set of feasible strategies, and choice between these strategies reflects reliance on small samples of past experiences.

Boosts and nudges are two separate types of behavioral public policies, distinguished by the mechanisms through which they operate. We investigated whether this theoretical distinction translates into different effects when instances of these policy types are implemented in the context of energy consumption. In a long-term field randomized controlled trial, we competitively tested boosts against nudges. We found that boosts outperform nudges throughout a seven-month period in a student dormitory setting – both in terms of accumulated energy savings, as well as in keeping consumption consistently low during the experimental period. Furthermore, we explored the processes behind the boosts and nudges through a number of mechanistic markers and showed that the tested interventions indeed are instances of the respective types.