This paper reviews the findings from the last 20 years on the behavioural factors that influence farmers’ decisions to adopt environmentally sustainable practices. It also proposes policy options to increase adoption, based on these behavioural factors and embedded in the EU Common Agricultural Policy. Behavioural factors are grouped into three clusters, from more distal to more proximal: (i) dispositional factors; (ii) social factors and (iii) cognitive factors. Overall, the review demonstrates that considering behavioural factors enriches economic analyses of farmer decision-making, and can lead to more realistic and effective agri-environmental policies.

The theory of planned behavior (TPB) has received its fair share of criticism lately, including calls for it to retire. We contribute to improving the theory by testing extensions such as the model of goal-directed behavior (MGDB, which adds desire and anticipated positive and negative emotions) applied to physical activity (PA) intention. We also test the inclusion of a descriptive norms construct as an addition to the subjective norms construct, also applied to PA, resulting in two additional models: TPB including descriptive norms (TPB + DN) and MGDB including descriptive norms (MGDB + DN). The study is based on an online survey of 400 young adult Internet users, previously enrolled in a subject pool. Confirmatory factor analysis

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Purpose-This commentary argues that social marketing and the application of behavioural sciences to policy constitute two converging paths towards better policies. It highlights points of convergence and divergence between both disciplines and the potential benefits of further embedding social marketing principles and methods within the recent trend of applying behavioural sciences to policy. Design/methodology/approach-The commentary relies on a review of the behavioural sciences and social marketing literatures and on an analysis of institutional reports reviewing cases of behaviourally informed policies. Findings-Behavioural sciences are increasingly informing policies to promote societal well-being. Social marketing has seldom been explicitly considered as being part of this phenomenon, although it is de facto. Both disciplines share similar end-goals, inform similar policy applications and are rooted in behavioural analysis. They diverge in their theoretical frameworks, their relative emphasis on behaviour change and the span of interventions they generate. Several benefits of embedding social marketing principles and methods within the current way of applying behavioural sciences to policy are identified. Practical implications-Scholars applying behavioural sciences to policy are encouraged, when appropriate, to use the insights and methods from social marketing. Social marketing can engage in a dialogue with behavioural sciences to explore how to pilot the convergence of both approaches in practice. Originality/value-The novelty of this contribution lies in providing the first comparison of the application of behavioural sciences to policy with social marketing, and in using the policy-making cycle framework to map the contributions and complementarities of both disciplines.

Ensuring safe and satisfactory online shopping activity, especially among vulnerable consumers such as elderly and less educated citizens, is part of a larger set of consumer policy objectives seeking to strengthen trust in the electronic marketplace. This article contributes to that goal by testing the effectiveness of nudges intended to prevent the purchase of 'incompatible' digital products (i.e., those which cannot be used with the devices owned by consumers or the systems they operate). We ran a computerised lab experiment (n = 626) examining three types of nudges, the effects of age and education, and interaction effects between these variables and the nudges. Results show that emotive warning messages and placing incompatibility information at the checkout page rather than earlier in the purchasing process were effective in reducing the purchase of incompatible goods. Age was also a relevant factor: older participants were more likely to purchase incompatible goods. In addition, there was an interaction effect between all nudges and age: two nudges exacerbated the effect of age, while another mitigated it. These results suggest nudges can be an effective policy tool, confirm a generational gap in online behaviour, and highlight how nudges can moderate the effect of socio-demographic variables.

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Normative messages have been shown to increase intention to do physical activity. We traced how "positive" and "negative" normative messages influenced physical activity intention by comparing constructs of the model of goal-directed behavior with descriptive norms (MGDB + DNs) across control and treatment groups in an experiment. For this purpose, 16-24-year-old respondents (n = 1,200) in Bulgaria, Croatia, and Romania were asked about their age, sex, and levels of physical activity before being exposed to positive and negative normative messages and completing a questionnaire with MGDB + DNs scales. Different MGDB + DNs constructs were influenced by the normative messages: compared with the control, the negative message group showed stronger attitudes (p = .003) and the positive message group showed higher positive anticipated emotions (p = .005). The positive message's effect is consistent with the literature on conformity to social norms. The negative message's effect lends itself to interpretations based on social identity and deviance regulation theories.Keywords: descriptive norms, exercise psychology, health behavior, model of goal-directed behavior, theory of planned behavior, young adults