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
This paper provides an overview of practices of mobile-source greenhouse gas(GHG) modeling in China and related data sharing issues. It is based on structured phone interviews and two on-line surveys conducted in 2011...This paper provides an overview of practices of mobile-source greenhouse gas(GHG) modeling in China and related data sharing issues. It is based on structured phone interviews and two on-line surveys conducted in 2011 and finds that most cities have transportation-land use models but that few have mobile-source GHG models. A group of entities housed in the government have the strongest GHG modeling capacities and dominate the relevant consulting market. Data hoarding of public entities is the biggest barrier for entities without government ties to compete in the market. The reasons for data hoarding include government concerns over political implications of data release, a tradition of data hoarding, and a lack of confidence in reliability and accuracy of the data.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.
文摘This paper provides an overview of practices of mobile-source greenhouse gas(GHG) modeling in China and related data sharing issues. It is based on structured phone interviews and two on-line surveys conducted in 2011 and finds that most cities have transportation-land use models but that few have mobile-source GHG models. A group of entities housed in the government have the strongest GHG modeling capacities and dominate the relevant consulting market. Data hoarding of public entities is the biggest barrier for entities without government ties to compete in the market. The reasons for data hoarding include government concerns over political implications of data release, a tradition of data hoarding, and a lack of confidence in reliability and accuracy of the data.
