Abstract
ContextIn Sweden, 34% of herds in official statistics 2021 (77% of the cows) have an automatic milking system (AMS) and keep 19% of the dairy cows. ObjectiveThis study should be considered in relation to the rapid increase of digitalisation in agriculture. It aimed at investigating Swedish farmers’ experiences and reflections in dairy farming concerning AMS use from a care perspective, based on two research questions: 1) What kinds of success factors and management challenges do farmers experience with AMS usage? and 2) How do farmers view their work environment in this kind of system? MethodsA mixed method approach was performed, using method triangulation through a questionnaire, interviews, and field visits. The Activity Theory (AT) was used as a theoretical lens to consider care practice in the dairy farming as a learning system. ResultsAND CONCLUSIONS: Participating dairy farmers were found to be in a continuous learning process on different levels in their system, from detailed problems with an individual cow or the herd to the whole dairy system. Implementation of AMS required learning in order to manage, and thus care for, a system comprising of animals, technology, and humans, to increase business viability. In successful AMS use, willingness to learn, adapt to the local situation, and continually improve practice, or care as a patterning of activities, appeared to be the most important factors. With more people involved, differentiations were possible, which in turn accentuated the need for more trained staff who can perform more complicated tasks. The findings indicated high importance of experience and a ‘stockperson's eye’, in combination with tool-mediated seeing using data from the robot, in developing enhanced professional vision and good care. A good stockperson had broad competence combining a stockperson's eye with experience with robot data. One of the greatest challenges for dairy farms was finding a good stockperson as staff or advisor. Increased flexibility in work and better physical health were important driving forces for implementing AMS, while handling alarms was mentally stressful and gave different perspectives on AMS vulnerability. Overall, the analysis of the collected data showed that AMS had brought major, primarily positive, changes in daily work and increased work satisfaction for most farmers, with a clear majority of the respondents feeling good in their work situation and enjoying their work. SignificanceApplication of AT in studying AMS from a care perspective, represents a shift from traditional research that normally addresses technological inventions, to studying farmers’ socio-technical system. The AT lens revealed the work practices in performing care, as a patterning of activities accomplished by a tinkering learning process, in the rich and messy matrix of humans, cows, and technology.
Highlights
The recent and rapid development of technology-oriented agricul tural trends, such as smart farming, digital agriculture and agriculture4.0, reflects agricultural production within the dominant technocratic paradigm (e.g. Ayre et al, 2019; Clay et al, 2020; Finstad et al, 2021; Klerkx et al, 2019; Lioutas et al, 2019; Rijswijk et al, 2021)
The automated milking systems (AMS) provides much data for each cow, sug gesting that the care perspective in AMS could be based on robot data, replacing the physical contact and visual inspection of each individual cow in conventional milking systems (CMS)
We apply the eight-step model of focal points devel oped by Mwanza and Engestrom (2005) and present more detailed findings on the focal points related to success factors and challenges in using AMS
Summary
The recent and rapid development of technology-oriented agricul tural trends, such as smart farming, digital agriculture and agriculture4.0, reflects agricultural production within the dominant technocratic paradigm (e.g. Ayre et al, 2019; Clay et al, 2020; Finstad et al, 2021; Klerkx et al, 2019; Lioutas et al, 2019; Rijswijk et al, 2021). Some research indicates that care in AMS must be based on more than robot data to be successful (Lundstrom and Linblom, 2020; Stræte et al, 2017). In a socio-technical perspective on dairy farming, the AMS is dependent on the farmer’s work practice (Finstad et al, 2021; Rijswijk et al, 2021). The digital transformation of AMS introduction meant replacement of CMS with milking robots based on digital technology and automation to handle the daily milking of dairy cows (Douphrate et al, 2013; Holloway et al, 2014b; Karttunen et al, 2016; Lunner Kolstrup and Horndahl, 2013; Lunner Kolstrup et al, 2018; Rijswijk et al, 2021; Salfer et al, 2017). Implementation of AMS is complex, due to the interactions between the social, the cyber, and the physical (Rijswijk et al, 2021), where much can go wrong in daily operations (Gustafsson, 2009)
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