Predicting technology adoption to improve research priority—setting
提出一种基于技术感知特征预测采纳速度和上限的方法，利用肯尼亚乳业案例验证相对投资、风险和复杂性对采纳的影响，并预测新技术的采纳前景，帮助研究机构设定优先级。
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.