Changing Land Management by Pannell David;Vanclay Frank;

Author:Pannell, David;Vanclay, Frank;
Language: eng
Format: epub
Publisher: CSIRO Publishing

Information and learning as adoption drivers

The potential for extension to influence learning changes as the diffusion process progresses. In the early phases of diffusion, when relatively little is known about a new practice, information and learning-related factors are major determinants of the speed of adoption (Feder and Umali 1993; Lindner 1987; Marsh et al. 2000). This is when there is a greater scope for extension to influence the rate of adoption.

Essentially, information can have the greatest impact on learning when the decision maker is not yet well-informed about the innovation and has a high level of uncertainty about the innovation’s likely performance. The information gained contributes to a learning process through which decision makers adjust their perceptions. As examples, this can involve shifts in the perceived outcome or cost if a particular practice is used; reduced (or increased) uncertainty that a particular outcome will occur when used on-farm; or awareness of a new effect of the innovation that was not previously considered that may influence its overall relative advantage if adopted.

Innovations that offer greater relative advantage to decision makers are more likely to generate more positive messages about the value of adopting (Lindner 1987). When these advantages are highly observable, the likelihood that more will adopt earlier increases (Pannell et al. 2006). As diffusion proceeds, there is a greater likelihood that highly relevant information will be obtained at less or no cost as a result of observation and contact with multiple neighbours, for example.

An abundance of readily accessible local information is also likely to mean an abundance of information with perceived ‘quality’ or effectiveness in terms of being able to influence learning (Fischer et al. 1996; Marra et al. 2001). Local sources of information are likely to have greater effectiveness than more distant sources (Lindner et al. 1982). Being local means that uncertainty (and variance) surrounding the relevance and applicability of the information to the decision maker’s own on-farm use is often reduced. Therefore, information produced by local use of a new innovation, or especially an on-farm trial, is likely to have higher ‘quality’ or value (Abadi Ghadim 2005; Llewellyn 2007). Similarly, perceived information quality and effectiveness can also be influenced by factors such as perceived validity of the source (Leathers and Smale 1991). As more information becomes more readily available there is greater opportunity for non-adopters’ perceptions of particular features or components of the innovation to become more consistent with those held by adopters.

Considering all of these factors, it is argued that more can be done to target extension resources (and research and development) to improve its effectiveness. By adequately considering the information and learning aspects of the adoption decision, information and learning can be directed towards factors that (a) are influential in the adoption decision, and (b) can be influenced by extension. Decisions to adopt or not adopt can therefore be improved and accelerated. Improved targeting of extension has the potential to improve the cost-effectiveness not only of investments in extension but also of farmer time and resources spent participating in extension and learning.

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