Predicting technology adoption to improve research priority-setting
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...
| Autores principales: | , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2003
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/139193 |
| _version_ | 1855538834652004352 |
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| author | Batz, Franz-Jozef Janssen, Willem G. Peters, Kurt J. |
| author_browse | Batz, Franz-Jozef Janssen, Willem G. Peters, Kurt J. |
| author_facet | Batz, Franz-Jozef Janssen, Willem G. Peters, Kurt J. |
| author_sort | Batz, Franz-Jozef |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace139193 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2003 |
| publishDateRange | 2003 |
| publishDateSort | 2003 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1391932025-12-08T09:54:28Z Predicting technology adoption to improve research priority-setting Batz, Franz-Jozef Janssen, Willem G. Peters, Kurt J. prioritization agricultural research planning management innovation adoption 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. 2003 2024-02-09T19:24:23Z 2024-02-09T19:24:23Z Journal Article https://hdl.handle.net/10568/139193 en Limited Access Elsevier Batz, Franz-Jozef; Janssen, Willem G.; Peters, Kurt J. 2003. Predicting technology adoption to improve research priority-setting. Agricultural Economics 28(2): 151-164 |
| spellingShingle | prioritization agricultural research planning management innovation adoption Batz, Franz-Jozef Janssen, Willem G. Peters, Kurt J. Predicting technology adoption to improve research priority-setting |
| title | Predicting technology adoption to improve research priority-setting |
| title_full | Predicting technology adoption to improve research priority-setting |
| title_fullStr | Predicting technology adoption to improve research priority-setting |
| title_full_unstemmed | Predicting technology adoption to improve research priority-setting |
| title_short | Predicting technology adoption to improve research priority-setting |
| title_sort | predicting technology adoption to improve research priority setting |
| topic | prioritization agricultural research planning management innovation adoption |
| url | https://hdl.handle.net/10568/139193 |
| work_keys_str_mv | AT batzfranzjozef predictingtechnologyadoptiontoimproveresearchprioritysetting AT janssenwillemg predictingtechnologyadoptiontoimproveresearchprioritysetting AT peterskurtj predictingtechnologyadoptiontoimproveresearchprioritysetting |