I am a PhD student at the Institute for Food and Resource Economics at the University of Bonn. I work with evaluating and improving the understanding of farm-level consequences of technology adoption, currently by employing the concept of eco-efficiency to assess the impact of automatic milking systems on Norwegian dairy farms. My work revolves around a hypothesis that effects of technology can be generalized across different technology-types and farming practices based on farmers behavior and farm structural changes.
As a PhD student at the Institute for Food and Resource Economics of the University of Bonn I explore farmers’ decision making to adopt new sustainable farming practices. With my passion for behavioral economics I investigate different decision factors such as the socio-spatial network. Currently I am focusing on mechanical weeding in sugar beets.
To achieve broad-scale sustainable crop production, novel technologies need to be adopted by farmers and used appropriately on farms. As agricultural economists, we can act as the link between technology developers and farmers by providing knowledge on how to get the technology from the lab to the fields and what happens after farms have adopted the technology. To develop cost- and environmentally efficient policies that promote adoption, we need to understand farmers’ adoption behavior: What factors drive adoption and how can we steer farmers’ decision making? To ensure that new technology contributes to sustainable crop production, the consequences of the technology need to be evaluated once applied.
However, the study of future technologies is limited since many of the technologies we wish to study are not yet widely adopted. Therefore, we assume that we can learn from current technology to make predictions about the adoption and consequences of future agricultural technologies. We believe this is a promising approach as we hypothesize that farmer motivation, technology traits and objectives, and context can be used to draw lessons from existing technologies for developing and evaluating new technologies.
We study the adoption factors in the case of mechanical weeding in German sugar beets, a currently highly relevant agricultural practice since the reduction of available active ingredients in herbicides due to environmental reasons causes a need for alternative measures such as mechanical weeding. To study the consequences of robotic systems an empirical assessment of Automatic milking systems (AMS) is conducted. This is one of few robotic systems which are already widely implemented on farms, thus offering a unique opportunity to study the consequences of a robotic system in practice.
We thank all who have been involved in our research so far. Especially, we would like to thank:
- Dr. Hugo Storm, supervision
- Dr. Klaus Mittenzwei, for guidance on the Norwegian context and FADN-database
- Prof. Anne-Katrin Mahlein, Dr. Christel Roß, Dr. Nicol Stockfisch, Dr. Sebastian Streit, Institute for Sugarbeet research (IFZ) , for expert knowledge on the sugar beet sector and survey design