Login

Proceedings

Find matching any: Reset
Add filter to result:
Barriers to Adoption of Smart Farming Technologies in Germany
1M. Gandorfer, 1S. Schleicher, 2K. Erdle
1. Bavarian State Research Center for Agriculture, Institute for Agricultural Engineering and Animal Husbandry, Vöttinger Straße 36, 85354 Freising (Germany)
2. German Agricultural Society (DLG) e.V., Eschborner Landstraße 122, 60489 Frankfurt (Germany)

The number of smart farming technologies available on the market is growing rapidly. Recent surveys show that despite extensive research efforts and media coverage, adoption of smart farming technologies is still lower than expected in Germany. Media analysis, a multi stakeholder workshop, and the Adoption and Diffusion Outcome Prediction Tool (ADOPT) (Kuehne et al. 2017) were applied to analyze the underlying adoption barriers that explain the low to moderate adoption levels of smart farming technologies. Results of the media analysis show that incompatibility (between different software and/or hardware products), lack of decision algorithms, profitability, inconvenience issues, data protection, and data sovereignty are the most important adoption constraints. While low profitability seems to have declining importance over time, the lack of decision algorithms and inconvenience issues remain important. Despite expectations, incompatibility is gaining importance over time; and both data protection and data sovereignty are relatively new aspects in the discussion. These findings were largely confirmed by participants in the workshop conducted. ADOPT was applied to examine the use of sensor technology for site-specific nitrogen management. Based on available information on adoption rates of these technologies we see ADOPT as a valuable tool for predicting peak adoption levels and the time to peak adoption. Scenario analyses with ADOPT show that increasing the ease and convenience of use of nitrogen sensor technologies can significantly increase adoption levels of such environmentally friendly technologies. To conclude, our results provide useful information for industry and policy makers to increase adoption levels of environmentally friendly smart farming technologies.    

Keyword: Adoption and Diffusion Outcome Prediction Tool (ADOPT), Digital Farming, Media Analysis, Multi-stakeholder Workshop