Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/63267
Title: | A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR |
Contributor(s): | Moglia, Magnus (author); Alexander, Kim S (author) ; Thephavanh, Manithaythip (author); Thammavong, Phomma (author); Sodahak, Viengkham (author); Khounsy, Bountom (author); Vorlasan, Sysavanh (author); Larson, Silva (author); Connell, John (author); Case, Peter (author) |
Publication Date: | 2018-07 |
Early Online Version: | 2018-04-18 |
DOI: | 10.1016/j.agsy.2018.04.004 |
Handle Link: | https://hdl.handle.net/1959.11/63267 |
Abstract: | | A Bayesian Network model has been developed that synthesizes findings from concurrent multi-disciplinary research activities. The model describes the many factors that impact on the chances of a smallholder farmer adopting a proposed change to farming practices. The model, when applied to four different proposed technologies, generated insights into the factors that have the greatest influence on adoption rates. Behavioural motivations for change are highly dependent on farmers' individual viewpoints and are also technology dependent. The model provides a boundary object that provides an opportunity to engage experts and other stakeholders in discussions about their assessment of the technology adoption process, and the opportunities, barriers and constraints faced by smallholder farmers when considering whether to adopt a technology.
Publication Type: | Journal Article |
Source of Publication: | Agricultural Systems, v.164, p. 84-94 |
Publisher: | Elsevier BV |
Place of Publication: | The Netherlands |
ISSN: | 1873-2267 0308-521X |
Fields of Research (FoR) 2020: | 3099 Other agricultural, veterinary and food sciences |
Peer Reviewed: | Yes |
HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
Appears in Collections: | Journal Article School of Humanities, Arts and Social Sciences
|
Files in This Item:
1 files
Show full item record
Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.