ADOPT 2012 FFI CRC
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ADOPT 2012 FFI CRC

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ADOPT 2012 FFI CRC ADOPT 2012 FFI CRC Presentation Transcript

  • ADOPT the A doption and D iffusion O utcome P rediction T ool
    • What ADOPT does
    • Who is involved with ADOPT
    • How it works
      • The Conceptual Framework
      • The ADOPT tool
      • Testing & Validation
    Guide to this Presentation
  • What does ADOPT do?
    • ADOPT makes adoptability knowledge and considerations readily available, understandable and applicable for R, D & E managers and practitioners.
    • It predicts likely rate and level of adoption for specific practices and informs R,D & E strategies.
    • Its use on projects during development can lead to more adoptable technology packages
  • Assumptions
    • ADOPT deals with populations (diffusion)
    • Not pretending to predict decisions of individuals
    • Not attempting to include all factors
    • Geoff Kuehne (CSIRO)
    • Rick Llewellyn (CSIRO)
    • Perry Dolling (DAFWA)
    • David Pannell (UWA)
    • Roger Wilkinson (VicDPI)
    • Mike Ewing (FFI CRC)
    Who has developed ADOPT?
  • What are the goals for ADOPT?
    • It is designed to:
    • PREDICT the time to peak adoption and peak level of adoption
    • INFORM users about influences on adoption and diffusion
    • ENGAGE users in thinking about adoption and diffusion when designing projects
  • Adoption influences conceptualised as quadrants Relative Advantage for the Population Population -specific influences on the ability to learn about the Innovation Learnability Characteristics of the Innovation Relative Advantage of the Innovation
  • ADOPT Conceptual Framework ADOPT Conceptual Framework Relative Advantage for the Population Population -specific influences on the ability to learn about the Innovation Learnability Characteristics of the Innovation Relative Advantage of the Innovation 11.Group involvement 10. Advisory support 12. Relevant existing skills and knowledge Networks Farmers networks & skills Learning of Relative Advantage Time to Peak Adoption Trialability of innovation 8. Innovation complexity 7. Trialing ease 9. Observability 13. Innovation awareness Peak Adoption Level 14. Relative upfront cost of innovation 15. Reversibility of innovation 3. Risk orientation 4. Enterprise scale 5. Management horizon 1. Profit orientation 6. Short-term constraints 2. Environmental orientation 18. Time for profit benefits to be realised 20. Time for environmental benefits to be realised 19. Environment 22. Ease & convenience 21. Risk Investment cost 17. Profit benefit in future 16. Profit benefit in years used Relative Advantage
  • Data entry page (22 questions)
  • Each question requires users to make a choice between responses
  • Numeric outputs are: Time to Peak Adoption & Peak Adoption Level
  • A sensitivity chart can be generated This allows users to identify the variables having the largest effect on adoption and diffusion
  • All outputs can also be generated as a printed report
  • Feedback from Users (1)
    • Its greatest value is its ease of use. It’s quick and potentially very powerful .
    • The tool has potential for anyone involved in practice change projects. It was worth doing as it was easy to populate and quick to do.
    • Just responding to the questions made you think, especially about the audience, the social factors and the risk aspects. It made you consider a broad range of parameters – the constraints and leverages.
    • I reckon this tool has great potential to improve our extension effort. If we can make show which attributes are positive for change and which are holding us back, we should be able to actively address both of them.
    • It could be used to evaluate projects to invest in – or it could be used with advisors, farming systems groups, NRM groups, and individual farmers to understand the process.
  • Feedback from Users (2)
    • The rate of adoption calculated was often really slow – depressing! Even fast was 5 to 10 years. It shows good reasoning why it would be slow....
    • Add some explanation as to why the question is being asked- the theory or science - and a guide to credible ranges & examples.
    • There would be some valuable learning to be gained if people could appreciate the reasoning behind the question, based on extension theory.
    • Reconsider the emphasis on risk, given this has so many dimensions.
    • The useful bit was that it made you think why, especially when the results were slower than we anticipated. This did prompt us to go back and question things.
    • It has great potential to be used as a learning tool for extension, both public and private - It could be used as a training opportunity.
  • ADOPT was validated using the introduction of narrow-leafed lupins in Western Australia The prediction provided by ADOPT Actual lupin diffusion curves
  • For more information on ADOPT contact: Dr. Geoff Kuehne   [email_address] or Dr. Rick Llewellyn (project leader) [email_address]