German farmers’ intention to use autonomous field robots: a PLS-analysis

Autonomous field robots are a promising technology for solving several problems in agriculture, as they are electrical driven, can control weeds single-plant based mechanically or with microdoses of pesticides and exert less ground pressure on the field. Whether such robots will be applied on a large scale in German agriculture depends on various parameters. Therefore, the factors influencing the behavioural intention of farmers with respect to their future adoption of autonomous field robots were investigated. The analysis applies a structural equation model based on an extended version of the Unified Theory of Acceptance and Use of Technology. The dataset, collected in 2019, consists of 500 German farmers. The results reveal significantly positive effects of farmers’ expected performance, social influence and trust as well as significantly negative effects of farmers’ effort expectancy and anxiety on the behavioural intention to use autonomous field robots. Additionally, moderating effects of age on the relationship of individual constructs to the behavioural intent to use robots could be confirmed. The results provide important information for various stakeholders. Robot suppliers should better inform farmers about the performance of their products, for instance by involving farmers in the development process of the robots. The ecological benefits attributed to field robots could meet public expectations and should be better communicated to address farmers’ social influence on the behavioural intention to use the robots. Policymakers could try to create better framework conditions, for example by establishing a stable legal situation for autonomous systems or promote its use.

     

Adoption of precision agriculture technologies by German crop farmers

In recent years, precision farming has been receiving more attention from researchers. Precision farming, which provides a holistic system approach, helps farmers to manage the spatial and temporal crop and soil variability within a field in order to increase profitability, optimize yield and quality, and reduce costs. There has been considerable research in farmers’ adoption of precision agriculture technologies. However, most recent studies have considered only a few aspects, whereas in this study a wide range of farm characteristics and farmer demographics are tested to gain insight into the relevant aspects of adoption of precision farming in German crop farming. The results of a logistic regression analysis show that predictors with positive influence on the adoption of precision farming are agricultural contractor services such as an additional farming business, having under 5 years’ experience in crop farming, having between 16 and 20 years’ experience in crop farming, and having more than 500 ha of arable land. However, having a farm of less than 100 ha and producing barley are factors that exert a negative influence on the adoption of precision farming. The results of this study provide manifold starting points for the further proliferation of precision agriculture technologies and future research directions.