Predicting technology adoption to improve research priority-setting
| cg.contributor.affiliation | Deutsche Gesellschaft für Technische Zusammenarbeit | en |
| cg.contributor.affiliation | International Service for National Agricultural Research | en |
| cg.contributor.affiliation | Humboldt Universitat zu Berlin | en |
| cg.howPublished | Formally Published | en |
| cg.identifier.doi | https://doi.org/10.1111/j.1574-0862.2003.tb00248.x | en |
| cg.issn | 0169-5150 | en |
| cg.issn | 1574-0862 | en |
| cg.issue | 2 | en |
| cg.journal | Agricultural Economics | en |
| cg.reviewStatus | Peer Review | en |
| cg.volume | 28 | en |
| dc.contributor.author | Batz, Franz-Jozef | en |
| dc.contributor.author | Janssen, Willem G. | en |
| dc.contributor.author | Peters, Kurt J. | en |
| dc.date.accessioned | 2024-02-09T19:24:23Z | en |
| dc.date.available | 2024-02-09T19:24:23Z | en |
| dc.identifier.uri | https://hdl.handle.net/10568/139193 | |
| dc.title | Predicting technology adoption to improve research priority-setting | en |
| dcterms.abstract | This 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. | en |
| dcterms.accessRights | Limited Access | |
| dcterms.bibliographicCitation | Batz, Franz-Jozef; Janssen, Willem G.; Peters, Kurt J. 2003. Predicting technology adoption to improve research priority-setting. Agricultural Economics 28(2): 151-164 | en |
| dcterms.extent | p. 151-164 | en |
| dcterms.issued | 2003 | en |
| dcterms.language | en | |
| dcterms.license | Copyrighted; all rights reserved | |
| dcterms.publisher | Elsevier | en |
| dcterms.subject | prioritization | en |
| dcterms.subject | agricultural research | en |
| dcterms.subject | planning | en |
| dcterms.subject | management | en |
| dcterms.subject | innovation adoption | en |
| dcterms.type | Journal Article |