4.7 Article

Automatic milking systems and farmer wellbeing-exploring the effects of automation and digitalization in dairy farming

期刊

JOURNAL OF RURAL STUDIES
卷 80, 期 -, 页码 469-480

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jrurstud.2020.10.028

关键词

Automatic milking systems; Wellbeing; Income; Job satisfaction; Mental health; Family work balance

资金

  1. Norwegian Research Funding for Agriculture and Food Industry [352030/1202027322]
  2. dairy cooperative Tine

向作者/读者索取更多资源

In recent years the concept of wellbeing, encompassing an individual's satisfaction with different aspects of their life, has received increased attention in literature. However, we find few studies of wellbeing in dairy farming. Therefore, the aim of this paper is to explore the wellbeing of Norwegian dairy farmers with automatic milking systems, and which factors are associated with wellbeing. We explore four dimensions of wellbeing; income, job satisfaction, mental health and family work balance. Data were collected from 739 Norwegian farmers using automatic milking systems. Linear regression, exploratory factor analysis and structural equation modelling were used to analyse the data. The results show that the following factors are associated with farmer wellbeing; gender, education, having a successor and colleagues, herd size and experience with automatic milking systems, together with training in use of the system and access to counselling. Our findings show that while being a female farmer is strongly associated with better family-work balance, it is negatively associated with mental health. Furthermore, we find that training in AMS, better management systems which avoids data overload, and access to extension services and colleagues are important for farmer wellbeing. Finally, our findings show that having a successor increases wellbeing, while increasing herd size reduces wellbeing. The findings have implications for farmers, extension services and for suppliers of automated systems to farmers. Suppliers and advisory services need to provide adequate training in AMS. Future advisory service models could offer back-office services monitoring key performance variables and help farmers interpret data for better decision making. Suppliers, preferrably in collaboration with extension services, should improve the AMS management software to avoid farmer technostress. Furthermore, suppliers and advisory services should facilitate networking among AMS-farmers to promote their wellbeing.

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