A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR

Moglia, Magnus; Alexander, Kim S.; Thephavan, Manithaythip; Thammavong, Phomma; Sodahak, Viengkham; Khounsy, Bountom; Vorlasan, Sysavanh; Larson, Silva; Connell, John; Case, Peter

Abstract

© 2018 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.

Citation

Moglia, M., Alexander, K. S., Thephavan, M., Thammavong, P., Sodahak, V., Khounsy, B., …Case, P. (2018). A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR. Agricultural Systems, 164, 84-94. https://doi.org/10.1016/j.agsy.2018.04.004

• Journal Article Type: Article
• Acceptance Date: Apr 11, 2018
• Online Publication Date: Apr 18, 2018
• Publication Date: Jul 1, 2018
• Publicly Available Date: Oct 19, 2019
• Journal: Agricultural Systems
• Print ISSN: 0308-521X
• Publisher: Elsevier Masson
• Peer Reviewed: Peer Reviewed
• Volume: 164
• Pages: 84-94
• DOI: https://doi.org/10.1016/j.agsy.2018.04.004
• Keywords: innovation diffusion, Bayesian Networks, small-holder farmers, rice agriculture, Laos, Lao PDR
• Public URL: https://uwe-repository.worktribe.com/output/875211
• Publisher URL: https://doi.org/10.1016/j.agsy.2018.04.004
• Additional Information: Additional Information : This is the author's accepted manuscript. The final published version is available here: https://doi.org/10.1016/j.agsy.2018.04.004.