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Drones are one of the latest tools to have been added to farmers’ precision agriculture technology tool kit. Despite the proclaimed benefits, adoption rates of drones are low and literature regarding the adoption of drones in agriculture is scarce. Therefore, this study investigates whether an extended Technology Acceptance Model (TAM) can contribute to the understanding of latent factors influencing farmers’ intention to adopt a drone. The sample of 167 German farmers was collected in 2019 via an online survey. Using partial least squares structural equation modelling and a binary model, the TAM explains 69% of the variance in the intention to use a drone by German farmers. According to the results, raising farmers’ awareness of farm-specific areas of drone application and the confidence level of using a drone can increase farmers’ intention to adopt a drone. The results are of interest for agribusinesses developing drones as well as selling or providing drones. Furthermore, the results are of interest for researchers in precision agriculture technologies.

Despite the popularity of agricultural land markets as a research topic, a current literature review on price drivers on agricultural land rental markets is missing, which is crucial in order to gain an overview of the status quo. Furthermore, farmers’ perceptions of price drivers on agricultural land rental markets have not been considered sufficiently. Therefore, this study combines descriptive results from a survey with 156 German farmers conducted during 2019–2020 using purposive sampling and a systematic literature review. The systematic literature review reveals four important areas acting as price drivers in agricultural land rental markets: policy/Common Agricultural Policy (CAP), bioenergy, climate change, and market prices/competition. Based on the overview, several points of departure for further research are provided. Furthermore, results from the survey show that farmers’ perceptions of the relative importance of the price drivers differ from the results of scientific literature. Therefore, perceptions of farmers should be considered for possible policy interventions derived from scientific evidence.

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