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A trans-theoretical model for the adoption of drones by large-scale German farmers

To analyse the adoption of drones in agriculture as the latest tool added to the set of precision agriculture technologies, this paper makes use of a novel application of the trans-theoretical model of behavioural change by analysing a sample of 167 large-scale German farmers collected in 2019. The...

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Bibliographic Details
Published in:Journal of rural studies 2020-04, Vol.75, p.80-88
Main Authors: Michels, Marius, von Hobe, Cord-Friedrich, Musshoff, Oliver
Format: Article
Language:English
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Summary:To analyse the adoption of drones in agriculture as the latest tool added to the set of precision agriculture technologies, this paper makes use of a novel application of the trans-theoretical model of behavioural change by analysing a sample of 167 large-scale German farmers collected in 2019. The model provides a gradual measure of farmers' decision making with respect to the adoption of drones, which gives more detailed insight into farmers' adoption processes than the more common approach of applied binary classifications. Ordinal logit regression results show that, among other factors, farmers' age, precision agriculture technology literacy and farm size affect farmers’ adoption process. Thus, this paper contributes to the literature by identifying key determinants of the drone adoption process in agriculture. Furthermore, this study provides information about the fields of drone application as well as reasons that oppose the usage of drones by farmers. The results are of interest for policy makers and suppliers of drones. •Drones are the latest tool added to set of precision agriculture technologies.•Novel application of the Trans-theoretical model of behavioral change to the adoption of drones in agriculture.•First analysis of drone adoption and use in agriculture.•Farmers’ characteristics as well as farm characteristics influence the adoption of drones.•Recommendations for providers and policy makers are made.
ISSN:0743-0167
1873-1392
DOI:10.1016/j.jrurstud.2020.01.005