Predicting technology adoption to improve research priority-setting

dc.creatorBatz, Franz-Jozef
dc.creatorJanssen, Willem G.
dc.creatorPeters, Kurt J.
dc.date2003
dc.date2024-02-09T19:24:23Z
dc.date2024-02-09T19:24:23Z
dc.date.accessioned2026-06-27T18:18:01Z
dc.descriptionThis paper presents an improved approach for predicting the speed and ceiling of technology adoption, which is a crucial information for research priority setting. In the models it is assumed that both the speed and ceiling of adoption depend on the perceived characteristics of technologies. Knowing the characteristics that have determined adoption in the past provides relevant information about the characteristics which will enable new technologies to be quickly and widely adopted in the future. Using a case study from Meru District in Kenya, it is shown that relative investment, relative risk and relative complexity significantly influenced the speed and ceiling of adoption of dairy technologies in the past. These empirical results are used to predict the speed and ceiling of adoption of potential new dairy technologies to be developed by the Dairy Cattle Research Programme (DCRP) of the Kenya Agricultural Research Institute (KARI). The approach is theoretically sound and based on empirical evidence. It clearly distinguishes promising technologies from less promising technologies and is transparent to participants in priority setting exercises. Allowing for the participation of all interest groups within the research system, the approach improves the quality of the assessment and hence the credibility of results.
dc.identifierhttps://hdl.handle.net/10568/139193
dc.identifier.urihttp://hdl.handle.net/123456789/154309
dc.languageen
dc.publisherElsevier
dc.rightsLimited Access
dc.sourceBatz, Franz-Jozef; Janssen, Willem G.; Peters, Kurt J. 2003. Predicting technology adoption to improve research priority-setting. Agricultural Economics 28(2): 151-164
dc.subjectprioritization
dc.subjectagricultural research
dc.subjectplanning
dc.subjectmanagement
dc.subjectinnovation adoption
dc.titlePredicting technology adoption to improve research priority-setting
dc.typeJournal Article

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