The DOI matches its Crossref record; 81 of the 87 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
Valente, T. W. (2003) · Genetics in Medicine · doi:10.1097/01.gim.0000061743.67794.c4 · Cited by 20,559
(2008) · Cited by 6,727
Interviews – Learning the Craft of Qualitative Research Interviewing
Vaivio, J. (2012) · European Accounting Review · doi:10.1080/09638180.2012.675165 · Cited by 4,558
Hybrid Corn: An Exploration in the Economics of Technological Change
Griliches, Z. (1957) · Econometrica · doi:10.2307/1905380 · Cited by 3,363
New Product Diffusion Models in Marketing: A Review and Directions for Research
Mahajan, V., Muller, E., & Bass, F. M. (1991) · Springer eBooks · doi:10.1007/978-3-662-02700-4_6 · Cited by 2,113
Farmers’ adoption of conservation agriculture: A review and synthesis of recent research
Knowler, D., & Bradshaw, B. (2007) · Food Policy · doi:10.1016/j.foodpol.2006.01.003 · Cited by 1,839
New Product Diffusion Models in Marketing: A Review and Directions for Research
Mahajan, V., Muller, E., & Bass, F. M. (1990) · Journal of Marketing · doi:10.2307/1252170 · Cited by 1,650
Understanding and promoting adoption of conservation practices by rural landholders
Pannell, D. J., Marshall, G. R., Barr, N., Curtis, A. L., Vanclay, F. M., & Wilkinson, R. (2006) · Australian Journal of Experimental Agriculture · doi:10.1071/ea05037 · Cited by 1,467
Self-citation
Research works printed but not linked: 3
- Addison, 2015, Summary report: the cost-effectiveness protocol used to assist in the prioritisation of the second phase of Reef Trust investment
- Farquharson, 2013, Characteristics of an agricultural innovation and incentives for adoption: rhizobium in Cambodia, Int. J. Environ. Rural. Dev., 4, 44
- James, 2015, It's all about the benefits: why extension professionals adopt Web 2.0 technologies, Rural Ext. Innov. Syst. J., 11, 72
Cited by
Sorted by citations
Rethinking technological change in smallholder agriculture
Glover, D., Sumberg, J., Ton, G., Andersson, J., & Badstue, L. B. (2019) · Outlook on Agriculture · doi:10.1177/0030727019864978 · Cited by 335
Kernecker, M. L., Knierim, A., Wurbs, A., Kraus, T., & Borges, F. (2019) · Precision Agriculture · doi:10.1007/s11119-019-09651-z · Cited by 282
Big Data Analysis for Sustainable Agriculture on a Geospatial Cloud Framework
Delgado, J., Short, N. M., Roberts, D., & Vandenberg, B. (2019) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2019.00054 · Cited by 197
Shang, L., Heckelei, T., Gerullis, M. K., Börner, J., & Rasch, S. (2021) · Agricultural Systems · doi:10.1016/j.agsy.2021.103074 · Cited by 263
Gabriel, A., & Gandorfer, M. (2022) · Precision Agriculture · doi:10.1007/s11119-022-09931-1 · Cited by 184
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review