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The use of digital technologies in agriculture offers various benefits, such as site-specific application, better monitoring, and physical relief. The handling of these technologies requires a specific skill set. Therefore, the question arises of when and how farm managers learn about digital technologies. Aiming to analyse the current situation, the present research investigated the role that digital technologies play in vocational training for future farm managers. Taking the example of farm management information systems (FMIS), the present study also analysed various predictors of adoption, including the effect of training. To investigate these research questions, an online survey among teachers and students of the farm management vocational programme across Switzerland was conducted in the spring of 2021. In total, 150 individuals participated, 41 of whom were teachers. Participants answered questions about the learning content in the farm management programme and their perception of digital technologies in general. Students further reported whether they already had a farm they would be managing in the future and how they perceived FMIS. The results indicate that both teachers and students are convinced that digital technologies play an important role in agriculture and will gain more importance in the future. A substantial part of 43% of the students who participated indicated that they had learned neither about digital technologies during their basic agricultural training nor the subsequent farm management programme. In terms of FMIS, 51% of the student sample indicated that they had never heard about FMIS during their agricultural training. While having learned about FMIS was not a significant predictor for adoption, gender, perceived ease of use, and intention to use more digital technologies in the future significantly predicted the adoption of FMIS. The paper concludes that, to support the adoption of digital technologies and FMIS specifically, training for future farm managers should focus on how to operate an FMIS to increase the perceived ease of use of this technology. [Display omitted] • 57% of the students learned about digital technologies during vocational school. • 49% of the students learned about FMIS during vocational school. • Intention to use digital technologies is an important predictor for the TTMA. • Perceived ease of use of FMIS is an important predictor for the TTMA. [ABSTRACT FROM AUTHOR]

To reduce the negative impacts of agricultural production, Switzerland and the EU introduced environmental and animal welfare regulations in their direct payment policy schemes. Compliance with these regulations is monitored, and fines are imposed if deficiencies in implementation are identified. Non-compliance with these regulations reduces the effectiveness of direct payment measures and creates public and private administrative transaction costs. Therefore, a better understanding of the reasons behind farmers' non-compliance with direct payment regulations can help the government develop targeted measures to increase the effectiveness of direct payment policies. We used data on self-reported compliance with direct payment regulations from a survey of 808 Swiss farmers to develop a framework that explains the likelihood of receiving penalties based on the following influencing factors: (1) knowledge of rules, (2) acceptance of rules, (3) costs and benefits of non-compliance, and (4) farmer and farm characteristics. We found that 28% of the participants had experienced receiving penalties because of non-compliance with direct payment rules. Based on a hierarchical binary logistic regression model, our findings revealed that better knowledge of inspection measures, higher educational levels, and higher acceptance of entrepreneurial restrictions associated with direct payment regulations significantly reduced the likelihood of receiving penalties as a result of non-compliance. We further found that non-compliance with direct payment rules could hardly be explained by farm size or farm types. Information about the reasons for farmers' non-compliance with direct payment regulations can help the government develop targeted measures to increase the effectiveness of policy measures. • Non-compliance with these regulations reduces the effectiveness of direct payment measures. • We analysed reasons behind farmers' non-compliance with direct payment regulations based on self-reported survey data. • We found that 28% of the participants had experienced receiving penalties. • Better knowledge of inspection measures, higher education, higher acceptance of entrepreneurial restrictions reduced the likelihood of receiving penalties. [ABSTRACT FROM AUTHOR]

• Food waste quantities reported using FWQ and FWD are highly correlated. • Amounts reported in the FWQ and FWD share the same psychological predictors. • Amounts reported using the FWD are higher than the amounts from the FWQ. The huge amount of food wasted at the consumer or household level has severe environmental and economic consequences. In the present work, we compared two self-report measures for the assessment of food waste quantities at the household level in Switzerland. Participants (N = 223) were asked to complete an online food waste questionnaire (FWQ), in which they were instructed to report the average amount of food waste produced in their households. In the second step, participants were asked to maintain a food waste diary (FWD) for 21 days. They were instructed to write down all food waste items, including their relative amounts, as well as the reason and method for their disposal. Using correlation and regression analyses, we found that the amount of food waste reported on the FWQ and in the FWD were highly correlated, revealing similar patterns in terms of their psychological predictors. In the context of the range of different methods available for the assessment of household food waste, our study has provided valuable insights into two of the most used self-report measures. Similarities between and limitations of the methods have also been discussed. This knowledge can be used to contextualise the available results, to design future studies, and ultimately, to help develop intervention strategies to reduce household food waste. [ABSTRACT FROM AUTHOR]