A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR. (July 2018) - Moglia, Magnus; Alexander, Kim S.; Thephavanh, Manithaythip; Thammavong, Phomma; Sodahak, Viengkham; Khounsy, Bountom; Vorlasan, Sysavanh; Larson, Silva; Connell, John; Case, Peter
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. Highlights: A Bayesian Network was built to explore the chances of practice change amongst farmers. The focus of the study is smallholder farmers in southern Lao PDR. The model emphasizes systemic barriers and enablers relating to practices and context. Coordinated multi-stakeholder action can improve the likelihood of practice change. The model supports examination of data gaps, perspectives and knowledge management.