Digitalisation is an integral part of modern agriculture. Several digital technologies are available for different animal species and form the basis for precision livestock farming. However, there is a lack of clarity as to which digital technologies are currently used in agricultural practice. Thus, this work aims to present for the first time the status quo in Swiss livestock farming as an example of a highly developed, small-scale and diverse structured agriculture. In this context, the article focuses on the adoption of electronic sensors and measuring devices, electronic controls and electronic data-processing options and the usage of robotics in ruminant farming, namely, for dairy cattle, dairy goats, suckler cows, beef cattle and meat-sheep. Furthermore, the use of electronic ear tags for pigs and the smartphone usage for barn monitoring on poultry farms was assessed. To better understand the adoption process, farm and farmer’s characteristics associated with the adoption of (1) implemented and (2) new digital technologies in ruminant farming were assessed using regression analyses, which is classified at a 10% adoption hurdle. The results showed clear differences in the adoption rates between different agricultural enterprises, with both types of digital technologies tending to be used the most in dairy farming. Easy-to-use sensors and measuring devices such as those integrated in the milking parlour were more widespread than data processing technologies such as those used for disease detection. The husbandry system further determined the use of digital technologies, with the result that farmers with tie stall barns were less likely to use digital technologies than farmers with loose housing systems. Additional studies of farmers’ determinants and prospects of implementation can help identify barriers in the adoption of digital technologies.

This paper presents the state of application of Precision Agricultural enabling Technology (PAT) in Swiss farms as an example for small-scale, highly mechanised Central European agriculture. Furthermore, correlations between farm and farmers’ characteristics and technology adoption were evaluated. Being part of a comprehensive and representative study assessing the state of mechanisation and automation in Swiss agriculture, this paper focuses on the adoption of Driver Assistance Systems (DAS) and activities in which Electronic Measuring Systems (EMS) are used. The adoption rate of DAS was markedly higher compared to EMS in all agricultural enterprises. The adoption rate was highest for high-value enterprise vegetables and surprisingly low for the high-value enterprise grapes. The results of a binary logistic regression showed that farmers located in the mountain zone were less likely to adopt PAT compared to farmers in the valley. Small farm size correlated with low adoption rates and vice versa showing adoption happens country-specific in the upper farm size distribution. The results show the potential for novel technologies to be adopted by farmers of high-value products. Furthermore, technologies have been partially used to reduce physical workload but not yet to evaluate crop or management performance to support decisions. However, automatic collection and forwarding of data is a fundamental step towards Smart Farming realizing its full potential in the future.

Farmers' subjectively perceived that administrative transaction costs are of high importance for the uptake of agri-environmental programs with direct effects on the effectiveness and efficiency of these programs and the well-being of farmers. This paper empirically estimates private administrative transaction costs resulting from an uptake of the newly introduced grassland-based milk and meat program in Switzerland, based on farmers' perceived administrative workload. Using ordered logit models, we analyze how the administrative tasks and farm and farmer characteristics influence the perceived administrative workload. We find that the time spent on monitoring or inspection tasks has no effect. In contrast, an outsourcing of program-related administrative tasks significantly reduces the perceived administrative workload. We also find that a better understanding of agricultural policy regulations significantly reduces the farmers' perceived administrative workload. We recommend that public administration improve the communication of agricultural policy regulations, rather than investing in the simplification of administrative forms.

In this study, we test the hypothesis that farmers' experienced administrative burden affects their policy perceptions. Based on survey data from 808 randomly chosen Swiss farmers, a latent class approach is used to depict the heterogeneity of farmers' policy perceptions. We find that 20 percent of farmers are grumpy with the current direct payment policy, 23 percent are supporters, and 57 percent are indifferent, meaning that the latter group of farmers neither agree nor disagree with the direct payment policy. Regression results indicate that the higher the perceived administrative burden, the higher the probability of belonging to the grumpy class of farmers. Additionally, our results show that grumpy farmers have less social exchange than their peers and exhibit lower environmental awareness. Our findings show that the bureaucracy involved in agricultural policy matters not only because it increases private and public administrative costs but also because it negatively shapes farmers' view of agricultural policy.