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Adopting innovations in agricultural industries

Adopting innovations in agricultural industries. Sally Marsh. ABARE Outlook 2010: Productivity session. . Why does adoption matter?. Powerful driver of productivity growth Not all new innovations taken up – affects enthusiasm for R&D funding

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Adopting innovations in agricultural industries

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  1. Adopting innovations in agricultural industries Sally Marsh ABARE Outlook 2010: Productivity session.

  2. Why does adoption matter? • Powerful driver of productivity growth • Not all new innovations taken up – affects enthusiasm for R&D funding • Recent evidence of a slow down in agricultural productivity growth in Australia • Can the adoption of agricultural innovations be improved?

  3. The adoption of innovations Often follows a typical diffusion pattern Lupins in WA(Marsh et al. 2000) No-till in Victoria(Llewellyn and D’Emden 2010)

  4. Diffusion characteristics • Diffusion to ceiling level takes time (sometimes a long time) • The ceiling level of adoption will rarely be 100% (or even close to 100%) • Rates of adoption vary between different innovations • Rates of adoption of the same innovation vary between locations • Start time of adoption can vary between locations

  5. Why do diffusion patterns vary? • They are an aggregate of individual adoption decisions • We know a lot about factors that affect individual adoption decisions – and why some innovations are not adopted

  6. Factors that affect adoption • Innovations are different • profitability, relevance, level of complexity, observability of trial results • People/industries have different resources • land, labour, capital, management skills, knowledge • People are different • personality, age, family structure, individual values, beliefs and goals • People operate within different socio-political environments • communication networks, legal constraints, access to markets, cultural factors, institutional drivers

  7. Characteristics of innovations 1 Two main elements that affect adoption: • Relative advantage • The degree to which the innovation is perceived as being superior to the practice it replaces, or available alternative practices • Trialability • The ability to trial the innovation on a small scale and learn from that trial

  8. Characteristics of innovations 2 • Relative advantage – affected by • Impact on short-term and medium-to-long term profitability • Adjustment costs • Impact on riskiness of production • Compatibility with existing technologies, practices and resources • Compatibility with beliefs and values • Innovation complexity • Trialability – affected by • Innovation divisibility • Observability of trial outcomes • Innovation complexity • Skill levels required to implement a trial

  9. Characteristics of farmers • Been the subject of a great deal of research • Findings are mixed – e.g. age, education, family structure have no consistent impact • As a general rule, changing people’s beliefs and values is difficult • But what about the ‘laggards’? – e.g. the last 20% of Australian grain farmers who haven’t adopted no-till

  10. Some evidence that ‘innovativeness’ is consistent. • So-called ‘laggard’ behaviour is not generally consistent across innovations. • More an issue of perceived/real low relative advantage, or lack of resources, capacity. Source: Rogers & Burdge 1972

  11. Encouraging adoption in agricultural industries 1 • Understand innovation characteristics which encourage adoption • High relative advantage – profitability, lack of complexity, compatibility • High trialability • Involving farmers in R,D & E builds in landholder perspectives and knowledge • Recognise that adoption decisions are multi-disciplinary • Involve economists and social scientists • At early stages of project development

  12. Encouraging adoption in agricultural industries 2 • Understand the limits of agricultural extension Source: Pannell 2008

  13. Encouraging adoption in agricultural industries 3 • Target misconceptions and identify knowledge gaps – aim to: • Direct extension towards factors that are influential in the adoption decision • Factors that can be influenced by extension • Extension has the biggest influence when the decision maker is not well informed – i.e. has high uncertainty Example – no-till non-adoption(Llewellyn & D’Emden 2010) • Non-adopters had similar perceptions as adopters about the effect of no-till on herbicide costs, herbicide resistance and fertiliser costs • Non-adopters were less likely than adopters to believe that no-till would increase water retention, yields and yield reliability.

  14. Encouraging adoption in agricultural industries 4 • Use farmer groups • Farmers learn best from other farmers and their own experience • Farmer groups turn “participative R&D” on its head • Another no-till example(Llewellyn 2010 pers. comm.) Formed 1992 in Western Australia Approx 1400 members in 1999 Formed 1998 in South Australia Approx. 1000 members in 2005

  15. Issues facing adoption in agricultural industries 1 • Adoption by small landholders • Rapid growth • ‘Lifestyle’ farmers – often lack knowledge, skills • Unlikely to have same motivations and goals • High transactions costs of engagement • Increasing technology/information complexity • Farmers face exhaustive farm management choices – e.g. possible rotations • Increasing use of consultants and knowledge brokers • Partial, stepwise adoption likely; adaptation • Promotion of “best practices” – some issues with this

  16. Issues facing adoption in agricultural industries 2 • Some innovations making large-scale operations more desirable • E.g. IT technology, no-till, GM technologies, precision agriculture, satellite technology • Could favour development of corporate farming or “farm family entrepreneurs” (already being seen) • Could lead to rapid adoption of complex agricultural technologies by specialist firms running large enterprises.

  17. Conclusions • Landholders are the decision-makers – each of them and their situation is unique • Innovations need to be as relevant and profitable as possible • Adoption is influenced by personal factors • Agricultural extension needs to become smarter • Economists and social scientists need to be involved early in agricultural R, D and E

  18. Thank you Thank you

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