How can you predict the rate of adoption?

Have you ever wondered as you’ve started a new extension project, just how many farmers will end up using the practice you’re promoting? It’s a great question because the ultimate goal of extension is change, and often it is about the adoption of a new practice or tool. 

So how on earth would you work this out? Where would you start? In this episode we’re going to tell you about the ADOPT model – a tool that can help you do just this. 

The ADOPT model was developed by a team of researchers who realised that although there has been a lot of research into the adoption of innovations, there was not much done in the way of using that information for predictions. ADOPT, the Adoption and Diffusion Outcome Prediction Tool, was developed to do just that!

The research team was Geoff Kuehne, Rick Llewellyn, David Pannell, Roger Wilkinson, Perry Dolling, Jackie Ouzman and Mike Ewing. And they’re all Australians! They wrote a paper about it back in 2017 and, as it’s open access, anyone can download it. There is a link to it in the notes below this blog post and it is worth a read as it provides a great deal of background and verification. As they say in their paper, they ‘set out to develop a tool with the joint aims of predicting the future level of adoption of a new farming practice by a particular population of farmers, and of enhancing the understanding of practice adoption by diverse agricultural stakeholders’ (Kuehne et al. 2017, p.116). 

The good news is that they succeeded in doing this! They developed the model and then tested it with some Australian case studies. The tool enables users to explore what the likely peak adoption of an innovation will be, understand some of the factors that impact adoption and do this in a way that allows transparency about the assumptions that have gone into that prediction.

The tool uses four aspects that influence adoption: 

  • characteristics of the innovation,
  • characteristics of the population that will be using the innovation, 
  • the relative advantage of using the innovation, and 
  • how easily you can learn about the advantage of the innovation. 

 

Users respond to 22 questions and the software then provides a prediction of not only the diffusion curve for the innovation, but also sensitivity analyses of the factors influencing the speed and peak level of adoption. 

Denise has been part of a group that has worked through the model and it was a great way of exposing assumptions and being able to have a robust discussion about these aspects of adoption. She believes this is the real power of the tool – being able to put some structure to discussions about what is realistically achievable in an extension project. 

In 2018 the model was moved online and there are now different options for accessing it. There is a trial account and paid versions (both individual and for teams) that provide a little more detail in the reporting function, as well as offering suggestions and ideas for increasing uptake. And it is not static. The team has added a version of ADOPT for developing countries, in addition to the standard tool, so it really is applicable wherever you are based!

So here is a way we can predict the adoption of a new practice or tool and this model is a great way of structuring a discussion with a team and ensuring that some of the challenges and barriers to adoption can be considered before we embark on an extension project.

Well, you’ve read our thoughts, now we would like to hear yours! Add a comment below this blog post and tell us about your experiences with the ADOPT model. Have you used it and if so what insights did you glean? Any tips for those considering using the model? We don’t want this to be just a one-way conversation – join in by sharing your thoughts and ideas with us! 

Thanks folks for reading this Enablers of change episode. Remember to subscribe to our newsletter if you’d like to know when new episodes are available. And if you liked what you’ve heard, please tell your friends so they can join the conversation!

Resources

Kuehne, G., Llewellyn, R., Pannell, D. J., Wilkinson, R., Dolling, P., Ouzman, J., & Ewing, M. (2017). Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy. Agricultural Systems, 156, 115-125. https://doi.org/10.1016/j.agsy.2017.06.007 

You can access the model here.

A short introductory video is available here.  

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