Reducing the cost of complexity for greater farming system change. Rick Llewellyn
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Transcript of Reducing the cost of complexity for greater farming system change. Rick Llewellyn
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Reducing the cost of complexity for greater farming system change
Rick Llewellyn
CSIRO, Waite Campus
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Increasing value of convenience
• Trends in farm businesses and management
• Implications for agricultural innovation and technologies• Value of convenience • Cost of complexity
• Challenge for R&D• Shift in drivers of relative advantage• Potential for innovation-advisor synergy• Expanding research role in innovation development process
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Increasing farm sizeLess managers per hectareGreater land use intensity
More management demands
Less available labour & management attention
Farm business trends
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Management constraints affecting farm productivity
- Management constraints a major factor limiting farm productivity growth and technical efficiency
- Management constraints leading to widening gap in farm efficiency
(ABARE, 2010; Hughes et al., 2011)
Increasing research recognition of complexity and labour constraints in farming systems
(Kingwell 2011; Doole et al 2009)
Lucerne increases whole farm profitability by 3% but increases management time by 9%
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Examples from Australian crop-livestock farming
No-shear sheep
(or no sheep)
Autosteer/ GPS Guidance
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Convenience in a bag:Herbicide tolerant soybean, US
Non-pecuniary embodied benefits:
simplicity; flexibility
Piggot and Marra 2008
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Embodied innovations
Embodied innovations:
The benefits are obtained relatively simply through its direct use.
Benefits can be attributed simply and directly
(e.g. new disease resistant crop; autosteer)
Non-embodied innovations: Usually information-intensive. Ongoing decisions and management
are needed to benefit from the technology
Require higher levels of management capacity to gain full value - skills, education, advisory support
(e.g. monitoring tools; variable rate technology; soil tests)
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RR Soybean: the growing value of convenience
• Evidence that growers become accustomed to convenience
• More inelastic demand
• Willing to pay higher prices for embodied convenience
• Less willing to shift away from embodied convenience
• Shifts in farm labour allocation; IWM reluctance
Piggot and Marra 2008 +Uematsu et al 2010; Fernande z-Cornejo et al 2005.
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Llewellyn & D’Emden 2010
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% n
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Llewellyn & D’Emden 2010
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Factors influencing no-till adoption rate
Use of crop consultant Higher education
Higher participation in extension activities Years since first awareness of nearby no-till adopter
Prior year much drier than average
Perceived soil moisture conserving benefits and improved seeding timeliness
Effectiveness of pre-emergent weed control (perceived) Relative price of glyphosate herbicide Location (region/state) and average rainfall
D’ Emden et al. 2007 (SA, Vic, NSW, WA 2003) ; 82% of decisions correctly predicted – 2003 use
From Logit &
Duration analysis
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% no
-till a
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ionNo-till adoption in Australian cropping regions
Llewellyn & D’Emden (2010) ; 2008 use
Logit analysis of no-till use & extensive use (>90% crop area)
Growers without a crop consultant are less than ½ as likely to be no-till adopters.
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• No-till system has complex demands
• Information and knowledge intensive (NT groups)
• Not an embodied technology, but advisor support evolved
• Advisors have had a substantial role – ongoing
• Agronomic constraints to more extensive use (perceptions):
• Disease
Adoption of no-till systems
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Convenience, complexity and advisor support affecting peak adoption, not just rate
Time
Early majority
Late majority
Actual relative advantage
Personal characteristics; learning-related characteristics; extension; actual relative advantage
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Adoption of variable rate fertiliser in Australian grain growing regions
Region
Have yield map (%)
Varying fertiliser rates on zones
and yield map (%)
SA
Central 20 7
Lower EP 32 10
Upper EP 20 5
Western EP 8 3
Mallee 17 9
VICMallee 24 18
Wimmera 23 4
WA Central 40 9
Robertson, Llewellyn et al 2011 (2008 use)
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Adoption of variable rate fertiliser in Australian grain growing regions
Region
Have yield map (%)
Varying fertiliser rates on zones
and yield map (%)
SA
Central 20 7
Lower EP 32 10
Upper EP 20 5
Western EP 8 3
Mallee 17 9
VICMallee 24 18
Wimmera 23 4
WA Central 40 9
Robertson, Llewellyn et al 2011 (2008 use)
Consultant use 2x ***Logistic adoption model of VR
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From complexity to convenience?
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The role for research
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The R&D challenge: the case of PA
Expected profitability alone not leading to high adoption
Complexity and inconvenience
A role for research not just extension
Overcoming low ‘adoption’ by advisors
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Finally
• Role for ‘advisor-technology synergy’ • Innovation can be complex, but supported by
advisors• Research aimed at developing relative advantage for
advisors & farmers
• Management time scarcity increasingly affecting relative advantage• Cannot be ignored in full economic analyses (whole-
farm)• Increasing value of ‘convenience agriculture’
9% management attention Vs 3% profit increase?
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THANK YOU