Several food crises damaged the image of the agricultural sector and consumers have lost trust, especially in animal production practices. Large parts of society believe that animal welfare standards in livestock production need to be improved. As a result, numerous animal welfare products have emerged on the market. This consumer paper identifies five clusters and, thus, strategic groups for the purchase of animal welfare products within the large group of consumers that differ significantly in their attitudes towards modern agriculture, their perception of animal welfare, their social acceptance of meat consumption and their shopping behaviour. Even personal differences are found between the clusters. Based on the results, we derived specific marketing implications for each cluster. These implications can help to develop a more differentiated market segment for animal welfare products in terms of animal welfare level and required price premium, enabling consumers to make product choices according to their preferences.

In recent years, the fourth industrial revolution has found its way into agriculture. Under the term smart farming, various so-called smart products are offered that may positively influence both the daily work of farmers and animal welfare. These smart products can collect data from the farm, extract important information, and in some cases even make decisions independently. Particularly in Germany, where intensive livestock farming is criticized by society, such smart products could make a significant contribution to improving animal welfare. However, an important prerequisite is the acceptance of the users, who are usually the livestock farmers themselves. So far, there is little knowledge about farmers’ attitudes towards smart products in livestock production. In this study, a factor analysis and a cluster analysis are conducted to evaluate the attitudes of German livestock farmers towards smart products. Based on the analysis of an online questionnaire in which German livestock farmers (n = 422) participated, four clusters could be derived. The main distinguishing characteristics of the clusters are the influence of the social environment, the expected effort for implementation, the general trust in smart products, and the technology readiness of the farms. As a result, this study provides valuable insights for technology providers of smart products for livestock farming as well as for policy makers.

Agricultural production methods in Europe are increasingly subject to public criticism from which many farmers suffer. This applies, among other areas, to the widespread use of pesticides. Autonomous field robots (AFR), as the next stage of agricultural automation, have the potential to farm more intensively and, at the same time, in a more environmentally friendly way. However, a certain skepticism towards autonomous systems is suspected among farmers. Whether farmers adopt a technology depends largely on their uncertainty about the consequences of its use and the resulting attitude on the adoption. In order to quantify the attitude on adopting AFR in Germany and to identify possible group differences within the population, 490 German farmers were surveyed using an online questionnaire, which is based on an extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT). In the subsequent cluster analysis, the statements inquiring the intention to use AFR served as cluster-forming variables. As a result, three groups (“openminded AFR supporters”, “convinced AFR adopters”, “reserved AFR interested”) could be identified according to their response behavior. Despite existing group differences, an overall attitude in favor of autonomous field robots was observed. The results complement the existing research with a further empirical study and provide interesting starting points for further analysis, field robot manufacturers, and political decision makers.

Farmers are considered a highly important stakeholder group for the successful implementation of higher farm animal welfare (FAW) standards, but so far little is known about their attitudes and the determinants of their participation in programs that request higher FAW standards. To close this research gap, fattening pig farmers in Germany were questioned via a large-scale online survey in 2018 (n = 239). Based on the Unified Theory of Acceptance and Use of Technology, a partial least squares path modeling (PLS) was run. Results show that the expected performance as well as the expected costs associated with the Initiative Animal Welfare (IAW) substantially influence fattening pig farmers’ behavioral intention to participate in the IAW. Furthermore, the decision is influenced by social determinants and facilitating conditions such as deadweight effects. Farmers’ hedonic motivation, fair remuneration and previous experiences with the establishment of higher FAW standards can influence their intention to take part in the IAW. In addition, farmers’ trust in the program is a major determinant. There are also moderating variables such as age and work experience that influence farmers’ intention to take part in the IAW. Our results have important managerial implications for the IAW and can help to design further tailor-made animal welfare programs (AWPs) that fulfill the requirements of both fattening pig farmers and the broader public not only in Germany but the European Union.

Innovative technologies in the context of smart farming are expected to play a significant role in the adaptation of the agricultural sector to climate change and sustainable agriculture. However, the adoption of smart farming solutions, in this case so-called smart products, depends indispensably on the acceptance of farmers. For this reason, it is important to develop an understanding of what determinants are decisive for farmers in the adoption of these technologies. In order to address this research gap, farmers in Germany were surveyed via a large-scale online survey in 2020 (n = 523). Based on an extended version of the Unified Theory of Acceptance and Use of Technology, a Partial Least Squares (PLS) analysis was performed. The results indicate that hedonic motivation significantly influences farmers’ behavioral intention to use smart products. In addition, behavioral intention is affected by social determinants and the personal performance expectations of smart products. Trust, as well as facilitating conditions, also has an impact on behavioral intention. Furthermore, facilitating conditions are an important determinant of the actual use behavior. In addition, use behavior is influenced by behavioral intention. It was further found that technology readiness plays a significant role in the adoption of smart products. Moderating effects of age, work experience, and farm size were identified that influence farmers’ willingness to use smart products. The study holds important managerial implications for technology companies in the field of smart farming and can help develop approaches for tailored technical solutions that meet farmers’ needs.