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

Bert Lenaerts, Yann de Mey*, Matty Demont

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)277-300
JournalJournal of Agricultural Economics
Volume73
Issue number1
Early online date4 Jul 2021
DOIs
Publication statusPublished - 2022

Keywords

  • accelerated breeding
  • innovation system
  • rice
  • selection model
  • triple-hurdle

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