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Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding

Adoption of new plant varieties has played a significant role in eradicating global hunger. Previous research has mainly focused on farmer adoption and impact of new crop varieties, although upstream adoption of technologies in plant breeding can generate substantial multiplier effects on downstream...

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Autores principales: Lenaerts, Bert, de Mey, Yann, Demont, Matty
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9292170/
https://www.ncbi.nlm.nih.gov/pubmed/35873719
http://dx.doi.org/10.1111/1477-9552.12450
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author Lenaerts, Bert
de Mey, Yann
Demont, Matty
author_facet Lenaerts, Bert
de Mey, Yann
Demont, Matty
author_sort Lenaerts, Bert
collection PubMed
description Adoption of new plant varieties has played a significant role in eradicating global hunger. Previous research has mainly focused on farmer adoption and impact of new crop varieties, although upstream adoption of technologies in plant breeding can generate substantial multiplier effects on downstream impacts. This study moves upstream in the innovation system to generate policy advice on adoption and transfer of accelerated rice breeding technologies. More specifically, we assess the determinants of global adoption of rapid generation advance (RGA) through a sample of 158 rice breeders operating in various research institutes worldwide. Moving upstream in the innovation system has important theoretical and empirical implications due to the smaller number of decision‐making units in the adoption process and the increasing role of institutional and managerial factors that may overrule individual adoption motivations. We revisit multi‐stage models and devise the most robust estimation method that can be used in this situation. To generate insights on the impact of individual versus institutional adopter characteristics on upstream technology adoption, we juxtapose the response curves of the determinants of RGA adoption in rice breeding among alternative adoption stages, levels of conditionality and model specifications. Our findings confirm the importance of institutional and managerial factors and suggest that adoption and transfer of breeding technologies require breeding institutes to provide an enabling environment in which breeders are encouraged to take risks and are given sufficient freedom to experiment with and implement new technologies.
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spelling pubmed-92921702022-07-20 Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding Lenaerts, Bert de Mey, Yann Demont, Matty J Agric Econ Original Articles Adoption of new plant varieties has played a significant role in eradicating global hunger. Previous research has mainly focused on farmer adoption and impact of new crop varieties, although upstream adoption of technologies in plant breeding can generate substantial multiplier effects on downstream impacts. This study moves upstream in the innovation system to generate policy advice on adoption and transfer of accelerated rice breeding technologies. More specifically, we assess the determinants of global adoption of rapid generation advance (RGA) through a sample of 158 rice breeders operating in various research institutes worldwide. Moving upstream in the innovation system has important theoretical and empirical implications due to the smaller number of decision‐making units in the adoption process and the increasing role of institutional and managerial factors that may overrule individual adoption motivations. We revisit multi‐stage models and devise the most robust estimation method that can be used in this situation. To generate insights on the impact of individual versus institutional adopter characteristics on upstream technology adoption, we juxtapose the response curves of the determinants of RGA adoption in rice breeding among alternative adoption stages, levels of conditionality and model specifications. Our findings confirm the importance of institutional and managerial factors and suggest that adoption and transfer of breeding technologies require breeding institutes to provide an enabling environment in which breeders are encouraged to take risks and are given sufficient freedom to experiment with and implement new technologies. John Wiley and Sons Inc. 2021-07-04 2022-02 /pmc/articles/PMC9292170/ /pubmed/35873719 http://dx.doi.org/10.1111/1477-9552.12450 Text en © 2021 The Authors. Journal of Agricultural Economics published by John Wiley & Sons Ltd on behalf of Agricultural Economics Society. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Lenaerts, Bert
de Mey, Yann
Demont, Matty
Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding
title Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding
title_full Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding
title_fullStr Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding
title_full_unstemmed Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding
title_short Revisiting multi‐stage models for upstream technology adoption: Evidence from rapid generation advance in rice breeding
title_sort revisiting multi‐stage models for upstream technology adoption: evidence from rapid generation advance in rice breeding
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9292170/
https://www.ncbi.nlm.nih.gov/pubmed/35873719
http://dx.doi.org/10.1111/1477-9552.12450
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