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ADOPT: Adoption andDiffusion OutcomePrediction Tool.  Geoff Kuehne (CSIRO) Rick Llewellyn (CSIRO)  Perry Dolling (DAFWA) D...
Aims          • Producing a tool and process toPredict   predict likely rate and level of          adoption for specific p...
Aims          • Producing a tool and process toPredict   predict likely rate and level of adoption          for specific p...
Aims          • Producing a tool and process toPredict   predict likely rate and level of adoption          for specific p...
What’s wanted
What’s wanted       Ongoing demandPast attempts –nothing or guesswork
The Literature
The LiteratureGrilliches (1957)       Lindner (1987)          Feder & Umali (1993)        Rogers (2003)   Pannell et al. (...
POPULATIONPopulation-specific      Relative Advantageinfluences on the        for the Populationability to learn aboutthe ...
RELATIVE ADVANTAGE           Population-specific      Relative Advantage           influences on theLEARNING              ...
Importance of RA
ADOPT: Adoption and Diffusion Outcome Prediction Tool.        Conceptual Framework             Learning of             Rel...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                                          Conceptual Framework• Ease...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                                          Conceptual Framework• Risk...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                         ADOPT: Adoption and Diffusion Outcome Predi...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                                          Conceptual Framework• Prof...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                                          Conceptual Framework• Rela...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                                               Conceptual Framework ...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                                               Conceptual Framework ...
ADOPT: Adoption and Diffusion Outcome Prediction Tool.                                               Conceptual Framework ...
Example questions
Example entry page
Example entry page
Example entry page
Response choices
Question explanation page
Example equation
Identify relationships
Formula for Trialability of Innovation= (varTrialable * weiTrialable +varInnovationComplexity *weiInnovationComplexity)/2
Networks                                                                 Profit Advantage=MIN((varGroupInvolv             ...
1. Introduction of narrow-leafed lupins                 1981
2. Crop/livestock farmers in the central wheat-belt               of Western Australia
Output
Output
Output rate & extent
Output extra data
Output relevant info
Output validation    Marsh et al. 2004           Wongan Hills           Wyalkatchem          Chapman Valley           Corr...
User feedback ~ 100 people ~ 35 projectsPREDICT            The rate of adoption calculated was often            really slo...
User feedback ~ 100 people ~ 35 projectsPREDICT            The rate of adoption calculated was often            really slo...
User feedback ~ 100 people ~ 35 projectsPREDICT            The rate of adoption calculated was often            really slo...
Future developments
ADOPT: Adoption and Diffusion Outcome Prediction Tool.             Conceptual FrameworkPopulation-specific                ...
Thank YouGeoff Kuehne (CSIRO), Rick Llewellyn (CSIRO)Perry Dolling (DAFWA), David Pannell (UWA)Roger Wilkinson (VicDPI), M...
Adopt: adoption and diffusion outcome prediction tool. Geoff Kuehne
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Adopt: adoption and diffusion outcome prediction tool. Geoff Kuehne

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A presentation from the WCCA 2011 event held in Brisbane, Australia.

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Adopt: adoption and diffusion outcome prediction tool. Geoff Kuehne

  1. 1. ADOPT: Adoption andDiffusion OutcomePrediction Tool. Geoff Kuehne (CSIRO) Rick Llewellyn (CSIRO) Perry Dolling (DAFWA) David Pannell (UWA) Roger Wilkinson (VicDPI) Mike Ewing (CRC FFI)
  2. 2. Aims • Producing a tool and process toPredict predict likely rate and level of adoption for specific practices • A tool to help inform R,D & EInform strategies • Making adoption and diffusionEngage considerations more available, understandable and applicable
  3. 3. Aims • Producing a tool and process toPredict predict likely rate and level of adoption for specific practices • A tool to help inform R,D & EInform strategies • Making adoption and diffusionEngage considerations more available, understandable and applicable
  4. 4. Aims • Producing a tool and process toPredict predict likely rate and level of adoption for specific practices • A tool to help inform R,D & EInform strategies • Making adoption and diffusionEngage considerations more available, understandable and applicable
  5. 5. What’s wanted
  6. 6. What’s wanted Ongoing demandPast attempts –nothing or guesswork
  7. 7. The Literature
  8. 8. The LiteratureGrilliches (1957) Lindner (1987) Feder & Umali (1993) Rogers (2003) Pannell et al. (2006)
  9. 9. POPULATIONPopulation-specific Relative Advantageinfluences on the for the Populationability to learn aboutthe InnovationLearnability Relative AdvantageCharacteristics of of the Innovationthe Innovation INNOVATION
  10. 10. RELATIVE ADVANTAGE Population-specific Relative Advantage influences on theLEARNING for the population ability to Learn about the innovation Learnability Relative Advantage characteristics of of the innovation the innovation
  11. 11. Importance of RA
  12. 12. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework Learning of Relative Advantage Relative Advantage Peak Adoption Level Time to Peak Adoption
  13. 13. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework• Ease & Convenience 10. Advisory support 11.Group involvement12. Relevantexisting skills andknowledge13. Innovationawareness 7. Trialing ease Learning of Trialability of Relative Innovation 8. Innovation Advantage complexity Relative Advantage Relative Advantage of the Innovation Peak Adoption 22. Ease & Level convenience Time to Peak Adoption
  14. 14. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework• Risk• Risk 10. Advisory support Orientation 11.Group involvement 3. Risk orientation12. Relevantexisting skills andknowledge13. Innovationawareness 7. Trialing ease Learning of Trialability of Relative Innovation 8. Innovation Advantage complexity Relative Advantage Relative Advantage of the Innovation Peak Adoption 22. Ease & Level convenience 21. Risk Time to Peak Adoption
  15. 15. ADOPT: Adoption and Diffusion Outcome Prediction Tool. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework Conceptual Framework• Environment 2. Environmental• Time for 10. Advisory support orientation environmental 11.Group involvement 3. Risk orientation benefits to be12. Relevantexisting skills and realisedknowledge13. Innovationawareness• Environmental orientation 7. Trialing ease Learning of Trialability of Relative Innovation 8. Innovation Advantage complexity Relative Advantage 19. Environment 20. Time for Relative environmental Advantage of benefits to be the Innovation realised Peak Adoption 22. Ease & Level convenience 21. Risk Time to Peak Adoption
  16. 16. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework• Profit in year Relative Advantage used 10. Advisory 2. Environmental orientation for the Population support• Profit in future 11.Group involvement 1. Profit 3. Risk orientation 6. Short- term constraints orientation 5. Family• Profit12. Relevant succession &existing skills and managementknowledge horizon Orientation13. Innovationawareness 4. Enterprise scale• Enterprise 17. Time for profit scale 7. Trialing ease benefits to be realised Learning of• Management Trialability of 16. Profit in Relative years used Innovation 8. Innovation Advantage complexity 18. Profit Horizon Relative Advantage in Future 19. Environment• Time for Profit Relative 20. Time for environmental benefits to be Advantage of the Innovation benefits to be realised realised9. Observability Peak Adoption Level 22. Ease & convenience 21. Risk Time to Peak Adoption
  17. 17. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework• Relative Relative Advantage upfront cost of 10. Advisory 2. Environmental orientation for the Population innovation support 6. Short- 11.Group 3. Risk term 1. Profit involvement constraints• Reversibility of orientation orientation Networks 5. Family12. Relevant succession &existing skills and management innovationknowledge horizon13. Innovation 4. Enterpriseawareness scale 17. Time for profit 14. Relative 15. benefits to be upfront cost Reversibility of realised 7. Trialing ease of innovation innovation Learning of 16. Profit in Trialability of Relative years used Innovation Investment cost 8. Innovation Advantage complexity 18. Profit Relative in Future Advantage 19. Environment 20. Time for Relative environmental Advantage of benefits to be the Innovation realised Peak Adoption 22. Ease & Level convenience 21. Risk Time to Peak Adoption
  18. 18. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework Need: • Consistency Population-specific influences on the ability to learn about the Innovation Relative Advantage for the Population 2. Environmental 10. Advisory orientation support • Direction of 6. Short- 11.Group term involvement Networks relationship 1. Profit orientation 3. Risk orientation 5. Family constraints12. Relevant succession & management • Dataexisting skills andknowledge horizon13. Innovation Farmersawareness skills requirements networks & 4. Enterprise scale • Strong 14. Relative upfront cost 15. Reversibility of 17. Time for profit benefits to be realised 7. Trialing ease influence Learning of of innovation innovation Trialability of 16. Profit in Relative years used Innovation • Age – Advantage Investment cost 8. Innovation complexity 18. Profit Relative in Future inconsistent Advantage 19. Environment Learnability Characteristics • Education – 20. Time for of the Innovation Relative environmental Advantage of benefits to be 9. Observability too hard the Innovation Peak Adoption 22. Ease & realised Level convenience 21. Risk Time to Peak Adoption
  19. 19. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework Population-specific influences on the Relative Advantage ability to learn about the Innovation 2. Environmental for the Population 10. Advisory orientation support 6. Short- 11.Group 3. Risk term 1. Profit involvement orientation constraints orientation 5. Family Networks12. Relevant succession &existing skills and managementknowledge horizon13. Innovation Farmers networks & 4. Enterpriseawareness scale skills 17. Time for profit 14. Relative 15. benefits to be upfront cost Reversibility of realised 7. Trialing ease of innovation innovation Learning of 16. Profit in Trialability of Relative years used Innovation Investment cost 8. Innovation Advantage complexity 18. Profit Relative in Future Advantage 19. Environment Learnability Characteristics 20. Time for of the Innovation Relative environmental Advantage of benefits to be the Innovation realised 9. Observability 22. Ease & Peak Adoption Level convenience 21. Risk Time to Peak Adoption
  20. 20. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual Framework Population-specific influences on the Relative Advantage ability to learn about the Innovation 2. Environmental for the Population 10. Advisory orientation support 6. Short- 11.Group 3. Risk term 1. Profit involvement orientation constraints orientation 5. Family Networks12. Relevant succession &existing skills and managementknowledge horizon13. Innovation Farmers networks & 4. Enterpriseawareness scale skills 17. Time for profit 14. Relative 15. benefits to be upfront cost Reversibility of realised 7. Trialing ease of innovation innovation Learning of 16. Profit in Trialability of Relative years used Innovation Investment cost 8. Innovation Advantage complexity 18. Profit Relative in Future Advantage 19. Environment Learnability Characteristics 20. Time for of the Innovation Relative environmental Advantage of benefits to be the Innovation realised 9. Observability 22. Ease & Peak Adoption Level convenience 21. Risk Time to Peak Adoption
  21. 21. Example questions
  22. 22. Example entry page
  23. 23. Example entry page
  24. 24. Example entry page
  25. 25. Response choices
  26. 26. Question explanation page
  27. 27. Example equation
  28. 28. Identify relationships
  29. 29. Formula for Trialability of Innovation= (varTrialable * weiTrialable +varInnovationComplexity *weiInnovationComplexity)/2
  30. 30. Networks Profit Advantage=MIN((varGroupInvolv =(((varProfitBenefitNow*weiProfitBenefitNow)*(varEnterpriseement*weiGroupInvolv Scale*weiEnterpriseScale)/5)+(1/8*(varProfitBenefitLater*weiement)+( ProfitBenefitLater)*(varEnterpriseScale*weiEnterpriseScale)*varAdvisorySupport*w (1/(POWER((1+(varManagementHorizonDiscountFactor)),(veiAdvisorySupport),5) arTimetoProfitBenefitYears))))/4.761904762*8))/2FNSK=(=varA+varBOne*(varRESK*weiRESK)+varBTwo*(varNetworks*weiNetworks)+varBT Envirronmental advantagehree*(varRESK*weiRESK)*(var =(varEnvironmentalBenefits *Networks*weiNetworks) Investment Costs weiEnvironmentalBenefits ) =(varUpfrontCosts * *(varEnvironmentalOrientation weiUpfrontCosts + *weiEnvironmentalOrientation)IAwareness=varA+varBOne varReversibility * *(1/(POWER((1+(varEnvironmentalCostsBenefit*(varAwareness*weiAwaren weiReversibility)/2 sDiscount)),ess)+varBTwo*(varObserva (varTimetoEnvironmentalBenefitsYears))))/4.761bility*weiObservability)+var 904762BThree*(varAwareness*wei Learning of Relative Advantage=(((((varProfitOrientation * weiProfitOrientation)Awareness)*(varObservabili RA=((weiTrialabilityInnovation*v * (varProfitAdvantage * weiProfitAdvantage)))ty*weiObservability) arTrialabilityInnovation)+(weiFar + ((varRiskOrientation * weiRiskOrientation)/5 mersNetworksSkills*varFarmers * (varRiskEffect * weiRiskEffect)) NetworksSkills)+(weiRelativeAd + (varEaseConvenience * weiEaseConvenience) vantage*varRelativeAdvantage)) + (varEnvironmentalAdvantage * weiEnvironmentalAdvantage)) /3 - ((varInvestmentCosts*weiInvestmentCosts)*-1+5))/10Trialability=(varTrialable * Time to Peak=(=MAX((-weiTrialable + (varSlope*(IF((varRelativeAdvantage*weiRelativeAdvantage)<1,1,(varRelativvarInnovationComplexity * eAdvantage*weiRelativeAdvantage))))+varIntercept)weiInnovationComplexity)/2 +(IF(varUpfrontCosts=5,0,(IF(varUpfrontCosts=4,IF(varShortTermConstraint Peak s>=4,0,(varShortTermConstraints*- Adoption=varBaseRate+(varMax1+4)/2),((IF(varShortTermConstraints>=4,0,varShortTermConstraints*- Rate-varBaseRate)/(1+EXP(- 1+4)))))*weiShortTermConstraints) -(IF(varAwarenessScore<=2,0,varAwarenessScore- ((varRelativeAdvantage*weiRelati veAdvantage)*2-5))) 2)*weiAwarenessScore)), 1)
  31. 31. 1. Introduction of narrow-leafed lupins 1981
  32. 32. 2. Crop/livestock farmers in the central wheat-belt of Western Australia
  33. 33. Output
  34. 34. Output
  35. 35. Output rate & extent
  36. 36. Output extra data
  37. 37. Output relevant info
  38. 38. Output validation Marsh et al. 2004 Wongan Hills Wyalkatchem Chapman Valley Corrigin Lake Grace
  39. 39. User feedback ~ 100 people ~ 35 projectsPREDICT The rate of adoption calculated was often really slow—depressing! ... It shows good reasoning why it would be slow ...
  40. 40. User feedback ~ 100 people ~ 35 projectsPREDICT The rate of adoption calculated was often really slow—depressing! ... It shows good reasoning why it would be slow ...INFORM The real value is that it makes you think why we do something – the constraints and leverages.
  41. 41. User feedback ~ 100 people ~ 35 projectsPREDICT The rate of adoption calculated was often really slow—depressing! ... It shows good reasoning why it would be slow ...INFORM The real value is that it makes you think why we do something – the constraints and leverages.ENGAGE … responding to the questions made you think, especially about the audience, the social factors and the risk aspects.
  42. 42. Future developments
  43. 43. ADOPT: Adoption and Diffusion Outcome Prediction Tool. Conceptual FrameworkPopulation-specific Relative Advantageinfluences on the for the Populationability to learn aboutthe InnovationLearnability Relative AdvantageCharacteristics of of the Innovationthe Innovation
  44. 44. Thank YouGeoff Kuehne (CSIRO), Rick Llewellyn (CSIRO)Perry Dolling (DAFWA), David Pannell (UWA)Roger Wilkinson (VicDPI), Mike Ewing (CRC FFI)

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