A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR
Date
2018
Authors
Moglia, M.
Alexander, K.S.
Thephavanh, M.
Thammavong, P.
Sodahak, V.
Khounsy, B.
Vorlasan, S.
Larson, S.
Connell, J.
Case, P.
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Journal article
Citation
Agricultural Systems, 2018; 164(C):84-94
Statement of Responsibility
RMagnus Moglia, Kim S. Alexander, Manithaythip Thephavanh, Phomma Thammavong, Viengkham Sodahak, Bountom Khounsy, Sysavanh Vorlasan, Silva Larson, John Connell, Peter Case
Conference Name
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.
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© 2018 Published by Elsevier Ltd. All rights reserved.