Insights for farmer training programs from system dynamics: A case study from Northern Michigan

Keywords: training, systems modeling, evaluation, rural livelihoods, adoption


Training programs for new farmers are proposed as a solution to rural food insecurity, rural development, and the recruitment and training of younger farmers simultaneously. However, evaluation of these programs and evidence for their individual or collective impact is sparse. In this paper, we use in-depth interviews combined with an exploratory model to evaluate the current and potential effectiveness of a farmer training program in Michigan’s Upper Peninsula. We use the model to represent the theoretical progression of farmers through three subsequent stages of skill acquisition: training, new farmer (practicing skills on land owned by the program) and experienced (farming on their own). We find that recruitment, access to local markets, rapidity of skill acquisition, and access to start-up costs are all important factors that facilitate trainees’ transition to farming on their own, but of these, start-up costs for independent farming appear to be the most significant barrier. While this model is exploratory and not predictive, these insights can inform the design of effective programs for training farmers. In addition, this study also demonstrates how systems dynamics can be a valuable method to evaluate and maximize the effectiveness of training programs.


Amelia, D. F., Kopainsky, B., & Nyanga, P. H. (2014). Exploratory model of conservation agriculture adoption and diffusion in Zambia: A dynamic perspective. Paper presented at the 32nd International Conference of the System Dynamics Society, Delft, Netherlands.

Denney, J. T., Kimbro, R. T., Heck, K., & Cubbin, C. (2017). Social cohesion and food insecurity: Insights from the geographic research on wellbeing (GROW) study. Maternal and Child Health Journal, 21(2), 343-350.

Fisher, D. K., Norvell, J., Sonka, S., & Nelson, M. J. (2000). Understanding technology adoption through system dynamics modeling: implications for agribusiness management. The International Food and Agribusiness Management Review, 3(3), 281-296.

Forrester, J. W. (1968). Principles of Systems. Pegasus Communications.

Lantz, N., & Walk, M. (2011). Upper Peninsula agriculture assessment. Retrieved from East Lansing MI:

Meadows, D. (2008). Thinking in systems: A primer. Chelsea Green.

Merrill, J. A., Deegan, M., Wilson, R. V., Kaushal, R., & Fredericks, K. (2013). A system dynamics evaluation model: Implementation of health information exchange for public health reporting. Journal of the American Medical Informatics Association : JAMIA, 20(e1), e131-e138.

Ramirez, A. S., Diaz Rios, L. K., Valdez, Z., Estrada, E., & Ruiz, A. (2017). Bringing produce to the people: Implementing a social marketing food access intervention in rural food deserts. Journal of Nutrition Education and Behavior, 49(2), 166-174 e161.

Rogers, E. (2003). The diffusion of innovations. The Free Press.

Scott, R. J., Cavana, R. Y., & Cameron, D. (2013, July 21-25, 2013). Evaluating long-term impact of qualitative system dynamics workshops on participant mental models. Paper presented at the 31st International Conference of the System Dynamics Society, Cambridge, MA.

United States Senate. (2008). Harvest over the horizon [electronic resource]: The challenges of aging in agriculture : Hearing before the Special Committee on Aging, United States Senate, One Hundred Tenth Congress, first session, Washington, DC, June 21, 2007.

How to Cite
Schmitt Olabisi, L., Elegbede, O., & Raven, M. (2020). Insights for farmer training programs from system dynamics: A case study from Northern Michigan. Advancements in Agricultural Development, 1(2), 1-11.