The adoption of new technologies and practices is fundamental to having the capacity to adapt to climate change and ameliorate resource degradation. Consequently, having the ability to predict the scale and rate of adoption by farmers of agricultural innovations is central to gauging their adaptive capacity. It is also crucial to assessing the likely compliance of farmers with change-seeking incentives and regulations. In this paper we describe a novel approach to predicting rates of adoption with respect to agricultural technologies and practices drawing on a dual-process model of consumer decision-making and a method for describing the complexity of innovations in farm systems. We tested the approach using data collected through a survey of dairy farmers in the Waikato and Waipa regions of New Zealand. In the survey we asked 200 farmers, chosen at random, about their perceptions of the complexity and relative advantage of various agricultural and resource management practices, and collected information as to how long it took them to try, and then adopt, the practices. Our results confirm that the process of forming an intention to try or adopt a technology or practice may take several months for relatively simple technologies and practices, and several years for more complex ones. Importantly, we found that novelty in terms of the originality in the components and architecture of a technology or practice does not necessarily correlate with its complexity in terms of integrating it into farm systems. This means that apparently simple technologies and practices that are promoted to reduce resource degradation can be quite difficult to integrate into farm systems and, as a consequence, the costs of integration may act as a strong deterrent to adopting them. A logical implication of our findings is that a deep understanding of the nature of the integration task is essential to anticipating how long it might take for adoption (or compliance) to occur in agriculture and, therefore, to appreciate limits on the adaptive capacity of farmers. Such an understanding requires an intimate knowledge of the, sometimes diverse, farm systems and sub-systems in which the technology or practice is to be integrated.
Kaine, G; Wright, V
Relative advantage and complexity: Predicting the rate of adoption of agricultural innovations
Frontiers In Agronomy