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What is technology adoption? Exploring the agricultural research value chain for smallholder farmers in Lao PDR

Kim Alexander (), Garry Greenhalgh (), Magnus Moglia (), Manithaythip Thephavanh (), Phonevilay Sinavong (), Silva Larson (), Tom Jovanovic () and Peter Case ()
Additional contact information
Garry Greenhalgh: James Cook University, Townsville Campus
Magnus Moglia: Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Manithaythip Thephavanh: National Agricultural and Forestry Institute
Phonevilay Sinavong: National Agricultural and Forestry Institute
Silva Larson: James Cook University, Townsville Campus
Tom Jovanovic: James Cook University, Townsville Campus
Peter Case: James Cook University, Townsville Campus

Agriculture and Human Values, 2020, vol. 37, issue 1, No 2, 17-32

Abstract: Abstract A common and driving assumption in agricultural research is that the introduction of research trials, new practices and innovative technologies will result in technology adoption, and will subsequently generate benefits for farmers and other stakeholders. In Lao PDR, the potential benefits of introduced technologies have not been fully realised by beneficiaries. We report on an analysis of a survey of 735 smallholder farmers in Southern Lao PDR who were questioned about factors that influenced their decisions to adopt new technologies. In this study, we have constructed measures or states of adoption which identify key elements of an adoption decision-making nexus. Analysis was conducted to statistically group explanatory factors of adoption. The key explanatory factors represented attributes of the farmer, the factors considered when undertaking production decisions and elements of the agricultural value chain that present as opportunities or constraints. We describe the combination of farmer’s personal attributes, perceptions of the value chain, and the introduction of new technologies by external actors as an “agricultural research value chain”, where agricultural research activities intervene to derive greater benefits for local farmers. A generalised linear model, via Poisson (multiple) regression analysis on the identified explanatory factors, was applied to explore how they influence adoption measures and we found several significant relationships.

Keywords: Measures of adoption; Agricultural research value chain; Adoption; Lao PDR; Technologies (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10460-019-09957-8

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