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Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy
Open accessAbstract
There is much existing knowledge about the factors that influence adoption of new practices in agriculture but few attempts have been made to construct predictive quantitative models of adoption for use by those planning agricultural research, development, extension and policy. ADOPT (Adoption and Diffusion Outcome Prediction Tool) is the result of such an attempt, providing predictions of a practice's likely rate and peak level of adoption as well as estimating the importance of various factors influencing adoption. It employs a conceptual framework that incorporates a range of variables, including variables related to economics, risk, environmental outcomes, farmer networks, characteristics of the farm and the farmer, and the ease and convenience of the new practice. The ability to learn about the relative advantage of the practice, as influenced by characteristics of both the practice and the potential adopters, plays a central role. Users of ADOPT respond to 22 questions related to: a) characteristics of the practice that influence its relative advantage, b) characteristics of the population influencing their perceptions of the relative advantage of the practice, c) characteristics of the practice influencing the ease and speed of learning about it, and d) characteristics of the potential adopters that influence their ability to learn about the practice. ADOPT provides a prediction of the diffusion curve of the practice and sensitivity analyses of the factors influencing the speed and peak level of adoption. In this paper the model is described and its ability to predict the diffusion of agricultural practices is demonstrated using examples of new crop types, new cropping technology and grazing options. As well as providing predictions, ADOPT is designed to increase the conceptual understanding and consideration of the adoption process by those involved in agricultural research, development, extension and policy.
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“This could be due to time delays in the effect of extension participation as the herd calving rate is determined by complex practices that do not give an immediate and observable return and require more learning time (Foster and Rosenzweig, 2010;Kuehne et al., 2017;Montes de Oca Munguia and Llewellyn, 2020).”
From Extension and management pathways for enhanced farm sustainability: evidence from Irish dairy farms (2023) · cites this paper as Kuehne et al., 2017
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Metadata
- Authors
- Kuehne, G., Llewellyn, R., Pannell, D. J., Wilkinson, R., Dolling, P., Ouzman, J., & Ewing, M.
- Affiliations
- Commonwealth Scientific and Industrial Research Organisation (AU)
- The University of Western Australia (AU)
- Department of Economic Development Jobs Transport and Resources (AU)
- Department of Agriculture and Food Western Australia (AU)
- Institut des Systèmes Complexes Paris Île-de-France (FR)
- Corresponding author
- Llewellyn, Rick
- Venue
- Agricultural Systems
- Publisher
- Elsevier BV
- Published
- 2017-09
- Volume
- 156
- Pages
- 115-125
- ISSN
- 0308-521X (ISSN-L)
- OpenAlex
- W2717963309
- Cited by
- 367
- References
- 87
- Citations by year
- 2026: 38 · 2025: 39 · 2024: 45 · 2023: 44 · 2022: 51 · 2021: 55 · 2020: 41 · 2019: 36 · 2018: 17 · 2017: 1
- FWCI
- 68.39
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Agricultural Systems (publishedVersion, cc-by-nc-nd)
- UWA Profiles and Research Repository (UWA) (publishedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Grains Research and Development Corporation
- Australian Centre for International Agricultural Research
- CSIRO
- University of Western Australia
- Australian Research Council Centre of Excellence for Environmental Decisions (CE11E0083)
- Topics
- Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Agricultural Innovations and Practices
- Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
- Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Agricultural Development and Management
- Keywords
- technology adoption, agricultural practices, diffusion of innovations, ADOPT, relative advantage, risk perception, farmer networks, ease of learning, diffusion curves, agricultural extension, agricultural policy
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