Abstract

۱٫ Introduction

۲٫ Material and methods

۳٫ Results and discussion

۴٫ Conclusion

Author contribution statement

Acknowledgements

References

Abstract

     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.

Introduction
Digital technologies and FMIS in agriculture

     The use of digital technologies in agriculture can facilitate the recording of data, support the sustainable use of resources, and make everyday work easier for farmers (Groher, Heitkamper, et al., 2020a, b). Digital technologies include a wide range of applications such as robots (e.g. for milking or hoeing), GPS applications (e.g. driver assistance or precision farming), sensors (e.g. measuring ammonia levels in barns or soil moisture), and smart phone applications.

     One digital technology that helps farmers collect, manage, and interpret their data is the farm management information system (FMIS). In essence, FMIS are farm record systems, which provide information that supports decision making related to the farm business (Lewis, 1998). They can further assist inexperienced farmers in their decision making by compensating for a relative lack of farming experience (Lewis, 1998). FMIS are a heterogeneous group of systems that cover a range of different functions. Fountas et al. (2015) identified in their review four clusters of FMIS: (1) basic systems, (2) sales-oriented systems, (3) site-specific systems, and (4) complete systems. Basic systems offer a limited set of functions that mainly support traditional farm management. Sales-oriented systems focus on sales and marketing, inventory management, and finance functions. The third group, site-specific systems, focuses on precision agriculture. The final group of complete systems offers a wide range of functions, some of which are also covered by the other three clusters. In this group, the percentage of web-based and mobile functions is the highest (Fountas et al., 2015).

Conclusion

     This work is among the first to investigate the role that digital technologies and FMIS play in agricultural training in Switzerland and what the predictors are for their adoption. The current study finds that only about 60% of the students of the farm management programme learned about digital technologies, and around 50% learned about FMIS during their agricultural training. Whether students had learned about FMIS in their agricultural training, however, had no significant effect on their adoption of FMIS. In line with previous research, which investigated the adoption of other technologies as measured with the TTMA, the current research also identified gender, perceived ease of use, and intention to use more digital technologies in the future as important predictors for the adoption of FMIS. These findings are relevant for both research and practice. For researchers, a better understanding of the predictors of the adoption of FMIS can help build prognoses for their future development. Further, an analysis of the situation in Switzerland complements the numerous studies conducted in Germany and helps reflect the situation in Europe. In terms of practical relevance, this knowledge can be useful to adapt the educational and advisory offers to fit the needs and skill levels of future farm managers. Policymakers can use the information to develop measures supporting the improvement of teaching materials and learning content.