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

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

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)84-94
JournalAgricultural Systems
Volume164
Early online date18 Apr 2018
DOIs
Publication statusPublished - 31 Jul 2018

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