L. Shang et al.: Adoption and diffusion of digital farming technologies – Integrating farm-level evidence and system-level interaction

Linmei Shang is a doctoral student in the Institute for Food and Resource Economics (ILR), University of Bonn. She is interested in various modeling methods of agricultural economics, including farm-level optimization, agent-based modeling, and machine learning algorithms.

Adoption and diffusion of digital farming technologies are expected to transform current agriculture towards a more sustainable system. Yet, to enable a targeted transformation we need to understand the mechanisms of adoption and diffusion in a holistic manner. Our current understanding comes from separate empirical farm-level studies on individual adoption and agent-based models (ABMs) simulating systemic diffusion mechanisms. Our objective is to bring both strands of literature together. We review 32 empirical farm-level studies on the adoption of precision and digital farming technologies and 27 ABMs on the diffusion of agricultural innovations. Results show that farm-level studies focus on farm and operator characteristics, but pay less attention to attributes of technology, interaction, institutional and psychological factors.

ABMs, despite their usefulness for representing interaction on higher scales, only loosely connect with empirical farm-level findings. Based on the identified gaps, we develop a conceptual framework integrating farm-level evidence on adoption with system-level interaction of technology diffusion. It may serve as a reference for future ABMs modeling adoption and diffusion of digital farming technologies at larger scales.

Authors: Linmei Shang, Thomas Heckelei, Jan Börner, Maria K. Gerullis, Sebastian Rasch