|Author:||Elizabeth Cromwell,Batson Zambezi|
|Title:||The Performance of the Seed Sector in Malawi: An Analysis of the Influence of Organisational Structure (ODI Research Study)|
|Format:||azw doc docx lit|
|ePUB size:||1412 kb|
|FB2 size:||1396 kb|
|DJVU size:||1722 kb|
|Publisher:||Overseas Development Institute (December 1993)|
Elizabeth Cromwell and Batson Zambezi. In this, the first study of the seed sector in Malawi, the authors assess the sector's performance with respect to a range of national development functions and evaluate the operational efficiency of the major seed sector institutions, examining the extent to which current sector performance is also determined by exogenous factors. They conclude with recommendations for short-term and long-term adjustments necessary for the seed sector to fulfil its intended role in Malawi's agricultural development
The Performance of the Seed Sector in Malawi: An Analysis of the Influence of Organisational Structure. This report presents the results of a study of the performance of the seed sector in Malawi. Field work for the study was conducted by the author in Malawi in November and December 1990. The seed sector in developing countries: A framework for performance analysis. This Working Paper examines the seed sector in developing countries against a background of structural reforms initiated to correct the severe macro-economic imbalances that developed during the 1970s and 1980s. The performance of the seed sector in Zimbabwe: An analysis of the influence of organisational structure. Working and discussion papers May 1992 Esbern Friis-Hansen.
Find nearly any book by Batson Zambezi. Get the best deal by comparing prices from over 100,000 booksellers. by Elizabeth Cromwell, Batson Zambezi. ISBN 9780850032017 (978-0-85003-201-7) Softcover, Overseas Development Institute, 1993. Founded in 1997, BookFinder.
Find nearly any book by Elizabeth Cromwell. Sowing Beyond the State: NGOs and Seed Supply in Developing Countries. by Elizabeth Cromwell. ISBN 9780813322278 (978-0-8133-2227-8) Softcover, CRC Press, 1994.
In our case study, the organizational metrics when applied to data from Windows Vista were statistically significant predictors of failure-proneness. The precision and recall measures for identifying failure-prone binaries, using the organizational metrics, was significantly higher than using traditional metrics like churn, complexity, coverage, dependencies, and pre-release bug measures that have been used to date to predict failure-proneness. Our results provide empirical evidence that the organizational metrics are related to, and are effective predictors of failure-proneness.
Keywords Organizational learning, organizational structure, formative measure. to promote a greater understanding of the phenomenon. Hence, the field of. OL has been characterized by a wide diversity of definitions and conceptualizations, which have been. used to examine OL issues.
Organizational structure is important because a good structure allows efficient communication, encourages departments and groups within the company to work together, establishes a hierarchy of responsibility and allows the company to grow in a controlled manner. There are several factors that influence organizational structure. Proper training helps to encourage a healthy organizational structure
Substantial funding has been directed towards building up formal seed supply organizations in developing countries - both parastatal bodies and private companies. But it is becoming very clear that often a much more effective network of informal seed diffusion based on farmer-to-farmer seed exchange exists. Mary Mphande is just one of the farmers ODI interviewed in Malawi last year, but her story is repeated all the time throughout the developing world.
analysis explain 5. % of the variability in performance of Zimbabwean insurance. The results of factor analysis after regression are summarised in Table. In this study we identified the factors affecting the performance of insurance. companies in Zimbabwe using multiple linear regression analysis and factor.
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