Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy

TLDR

Existing research identifies many factors influencing agricultural adoption, yet quantitative predictive models for planning research, extension, and policy remain scarce. The paper presents ADOPT and demonstrates its ability to predict adoption diffusion for new crop types, technologies, and grazing options, aiming to enhance understanding among researchers, developers, and policymakers. ADOPT predicts diffusion curves and sensitivity analyses by asking users 22 questions covering practice characteristics, adopter perceptions, learning ease, and farm/farmer attributes, integrating economic, risk, environmental, network, and convenience variables into a conceptual framework. Using case studies of new crop types, technologies, and grazing options, the model accurately predicts adoption diffusion, validating its predictive capability.

Abstract

There is much existing knowledge about the factors that influence adoption of new practices in agriculture but few attempts have been made to construct predictive quantitative models of adoption for use by those planning agricultural research, development, extension and policy. ADOPT (Adoption and Diffusion Outcome Prediction Tool) is the result of such an attempt, providing predictions of a practice's likely rate and peak level of adoption as well as estimating the importance of various factors influencing adoption. It employs a conceptual framework that incorporates a range of variables, including variables related to economics, risk, environmental outcomes, farmer networks, characteristics of the farm and the farmer, and the ease and convenience of the new practice. The ability to learn about the relative advantage of the practice, as influenced by characteristics of both the practice and the potential adopters, plays a central role. Users of ADOPT respond to 22 questions related to: a) characteristics of the practice that influence its relative advantage, b) characteristics of the population influencing their perceptions of the relative advantage of the practice, c) characteristics of the practice influencing the ease and speed of learning about it, and d) characteristics of the potential adopters that influence their ability to learn about the practice. ADOPT provides a prediction of the diffusion curve of the practice and sensitivity analyses of the factors influencing the speed and peak level of adoption. In this paper the model is described and its ability to predict the diffusion of agricultural practices is demonstrated using examples of new crop types, new cropping technology and grazing options. As well as providing predictions, ADOPT is designed to increase the conceptual understanding and consideration of the adoption process by those involved in agricultural research, development, extension and policy.