Modeling post adoption decision in precision agriculture: A Bayesian approach

Abstract Farmer’s post-adoption responses about technology are important in continuation and diffusion of technology in precision agriculture. We studied farmer’s frequency of application decisions of GPS guidance system, after adoption. Using a Cotton grower’s precision farming survey in the U.S. and Bayesian approaches, our study suggests that ‘meeting expectation’ plays an important positive role. We derived posterior predictive density plots of farmers meeting expectation and not meeting expectations. Additionally, we found that farmer’s income level, farm size, and farming occupation are other important factors in modeling GPS guidance system adoption and application.