Can a sequential analysis provide a more robust understanding of farmers' adoption decisions? An example from an agroforestry adoption study in Ethiopia

Abstract

Farm level factors continue to be the mainly investigated variables for adoption of innovations (e.g., new crop cultivars). This research explores how adoption of agroforestry innovations (i.e., new agroforestry trees or management practices) is associated with the farm level conditions of the farmers over time. Retrospective data was collected from 327 households on three agroforestry innovations. We analyzed all adoption events starting from the year at which a farmer began adopting the innovation over the next five adoption cycles (spanning 50 years based on recall data), irrespective of the calendar year. We discovered that adoption intensified in the 2000s, and the frequency of adoption is largely limited to two or three cycles. After first adoption, 32.11%, 14.68%, 3.36% and 0.92% of the farmers made second, third, fourth and fifth cycle follow-up adoptions of the specific agroforestry innovations, respectively. Farm size and family size are significant drivers of the adoption decision consistently; household decision making pattern is important for making first and second cycle adoption. Farming income is also vital to arrive at second and third cycle adoption decisions. Herd size is also associated with first cycle adoption. Farm level variables accounted for 55–70% of the variation in adoption decisions. Our study confirmed that farm level variables are still relevant to explaining decisions to adopt agroforestry innovations by smallholder farmers. The sequential analysis provided insightful information on the variability of factors affecting these decisions over time. Lessons based on this data and the extant literature are discussed for both development and research.