Identifying cogs in the adoption wheel: opportunities to target extension
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Transcript of Identifying cogs in the adoption wheel: opportunities to target extension
www.RuralPracticeChange.org
Department ofPrimary Industries
Identifying cogs in the adoption wheel -
opportunities to target extension
Rick LlewellynCSIRO Sustainable Ecosystems
Adelaide, SA
www.RuralPracticeChange.org
Initially decision makers do not know everything that matters
Hiebert
Adoption as a learning process
Learning of relative advantage
An economic basis
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Targeting information and extension
Many projects have aims of extensive adoption and impact
Most projects don’t have close personal contact with all potential adopters
Many projects involve practices that aren’t ‘new’
Many projects have information and learning as their primary tool
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Key Points Understanding adoption decisions so that you
can see where you can make a difference
You can identify and quantify the key (non) adoption drivers
You can identify where information and learning can be most effective
You can target extension and consider information effectiveness
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Identifying common drivers
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Steps to more effective targeting of information
1. Explore factors that may influence the relative value of the innovation for individual growers on their farm
2. Collect quantitative data from a representative sample of growers, including perceptions
3. Identify inconsistencies, high uncertainties and likely misperceptions
4. Conduct analyses to identify variables that have the biggest influence on the likelihood of adoption
5. Identify what influential variables can be influenced by learning (if any) and targeted R, D and/or E
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Adoption of no-till and conservation farming practices
Public good aim of reduced soil erosion
Still the focus of major public investment
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Adoption of no-till cropping practices
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GRDC, SANTFA, DAFF (2008)
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Factors influencing no-till adoption Years since first awareness of nearby no-till adopter Use of directly paid consultant Higher participation in extension activities Prior year much drier than average Higher education
Perceived relative effectiveness of pre-emergent weed control Perceived soil moisture conserving benefits and improved seeding timeliness
Relative price of glyphosate herbicide Location (region/state) and average rainfall82% of decisions correctly predicted
(logit and duration analysis)
Source: D’ Emden et al. 2007 (SA, Vic, NSW, WA 2003)
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No-till adoption strategiesWHAT TO TARGET:
Early-season weed control
Water use efficiency benefits
Benefits of ability to seed on time
WHAT NOT TO TARGET:
Ability of no-till to reduce erosion
2005
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Where to now?
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% farmers using some no-till
Llewellyn & D’Emden and 2008
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Extent of no-till use% using no-till % users using all
NTYear 03 08 13* 08Vic Mallee 40 68 88 44WA Northern 84 92 96 64SA Western EP 48 55 73 30
•Adoption AND probably extent of use will have lower peak in some districts•Some disadoption (5% disadopted; 10% reduced area)•Still some opportunities to target some information •But most farmers now have some on-farm experience•Only 20% of non-adopters use a paid cropping adviser •Options for lower-cost ‘farm-specific’ information e.g. local clusters with shared agronomy consultant?
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Location, location, location
Walker et al. 2005.
0
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< 10 10 to 50 50 to 200 over 200
Distance from trial (km)
Willingness to pay ($)
The value placed on trial report information by WA growers
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CORRIGINFarm Improvement Group
FARMER GROUPS
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Considering learning and information quality
Relative Advantage →
Prob.
Actual Average Advantage of
Practice
Actual Variance
Of Practice
Grower perception of
practice
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Perception of trial results when
considering own farm
Perception of trial results when
considering own farm
Considering information quality
Relative Advantage →
Prob.Observed trial
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Factors associated with adoption of multiple integrated weed management practices
Perception of higher ryegrass control (efficacy) Perception of higher economic value of practices in farming system Perception of a longer time until effective new herbicide Level of uncertainty of when a new herbicide will become available Higher use of information/extension Higher education
Higher proportion of the farm cropped Lower discount rate for future returns The resistance status of the farm
86% of decisions correctly predicted (logit)
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0 20 40 60 80 100
Efficacy (% weed reduction)
ProbabilityPerceived efficacy of weed seed
capture
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0 20 40 60 80 100
ProbabilityPerceived efficacy of weed seed
capture
Efficacy (% weed reduction)
Non-adoptersAdopters
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Factors associated with first use of durum wheat in WA
Higher expected durum: bread wheat yield ratio Perception of higher rust resistance of durum Involvement in cropping extension events Larger farm size
84% of decisions correctly predicted (logit) Source: Nguyen et al. 2007
Past durum growing was not a significant predictor of future durum growing
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Recognising information and learning costs
“.. a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it"
Herbert Simon
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Recognising the appeal of ‘convenience agriculture’
Less managers per hectare ; More management demands
‘Attention’ is scarce and valuable
The challenge for ‘inconvenient’ agricultural & NRM practices
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The future of
Mixed-Farming Agriculture
A livestock management service for
time pressured farmers
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Department ofPrimary Industries
KEY MESSAGESIt is possible to:
Predict a high proportion of adoption decisions for a particular practice
Identify the common factors driving adoption decisions for a particular practice – including perceptions
Target R,D & E towards factors that are influential and can be influenced to improve decision making
Identify where further information is unlikely to have any impact on the adoption decision
Consider information quality and effectivenessNovel ways to address ‘attention’ scarcity
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Acknowledgements:
GRDC, SANTFA, DAFF, Mallee Sustainable Farming
Faculty of Natural and Agricultural Sciences, University of Western Australia
CRC Australian Weed Management
CRC Future Farm Industries
Frank D’Emden, Michael Burton, Bob Lindner, David Pannell, Steve Powles, Sally Marsh, Amir Abadi, Tracey Gianatti, Bob McCown, Peter Carberry, Shahajahan Miyan, Ellen Walker, Van Nguyen,
Thank You