A combination of factors, including inadequate interactive influence of professional human resource needs, contributes to low adoption of forest innovations. This study was conducted to assess the influence of quantit...A combination of factors, including inadequate interactive influence of professional human resource needs, contributes to low adoption of forest innovations. This study was conducted to assess the influence of quantity of professional human resource needs on adoption of forest innovations across relevant institutions in Kenya. The study considered 51 main institutions involved in, or support conservation activities, of which 33 were public, 14 non-governmental, and 4 private. Purposive sampling was used due to the heterogeneity of the institutions involved in conservation. Primary data were collected using a structured questionnaire. A quartile graph-based quantitative model was used to establish the differences in capacity variation expressed as expected variation region or the common cause and the unexpected variation region or the special cause. The latter should be investigated and acted upon. Statistical analysis involved Levene’s Test of Equality of Variances. Embracing both approaches confirmed the model as an appropriate quantitative analytical framework for assessing and articulating elements of institutional capacity, and that quantity of professional human capital (P < 0.05) is key to influencing adoption of forest innovations in Kenya. The study reiterates that to overcome professional capacity gaps and respond to conservation paradigm shift, quantity was relevant and was an imperative policy issue.展开更多
文摘A combination of factors, including inadequate interactive influence of professional human resource needs, contributes to low adoption of forest innovations. This study was conducted to assess the influence of quantity of professional human resource needs on adoption of forest innovations across relevant institutions in Kenya. The study considered 51 main institutions involved in, or support conservation activities, of which 33 were public, 14 non-governmental, and 4 private. Purposive sampling was used due to the heterogeneity of the institutions involved in conservation. Primary data were collected using a structured questionnaire. A quartile graph-based quantitative model was used to establish the differences in capacity variation expressed as expected variation region or the common cause and the unexpected variation region or the special cause. The latter should be investigated and acted upon. Statistical analysis involved Levene’s Test of Equality of Variances. Embracing both approaches confirmed the model as an appropriate quantitative analytical framework for assessing and articulating elements of institutional capacity, and that quantity of professional human capital (P < 0.05) is key to influencing adoption of forest innovations in Kenya. The study reiterates that to overcome professional capacity gaps and respond to conservation paradigm shift, quantity was relevant and was an imperative policy issue.
