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Adaptation of spatial development framework methods for agricultural value chain development.

Marete, Emmanuel Mutwiri (2020) Adaptation of spatial development framework methods for agricultural value chain development.

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Abstract:Developing economies in sub-Saharan Africa (SSA) aim to break into global markets, by shifting from low productivity to high productivity and creating more jobs. They have had lessons from both policy successes and failures, as evidenced by the previous continental and regional economic strategies since independence. In the contemporary literature, various research advocates for adapting successful strategies applied in other fast developing economies, e.g. in East Asia, to facilitate the shift. However, to avoid duplicating externally designed strategies that lack endogenous characteristics, which have previously proven unsuccessful, development is to be guided by comparative advantages. Agriculture employs majority of SSAs working population, thus it offers a strength to the shift and job creation, through diversification of activities around it. Hence, national development strategies and plans need to integrate agricultural development initiatives. To coordinate these strategies necessitates use of strategic planning tools at both national and local levels. The SDF methodology as used in Rwanda, facilitated a territorial understanding of regional development and complementarity of settlements within regions. It was also used to coordinate the allocation of interventions from national and local development strategies into regions, based on the territorial understanding. To further this research, this study adapted this methodology to prioritize industrial locations, by coordinating industrial and agricultural policy objectives. An agricultural commodity value-chain was analysed to identify relevant factors that complemented policy guidelines, to prioritize activities in special economic zones (SEZ). To handle the variety of complex factors, spatial multi-criteria evaluation (SMCE) was used evaluate the suitability of the SEZs relative to the identified factors. This revealed that the selection of location factors was not exhaustive to select SEZ sites, and in addition identified the performance of SEZs based on agro-processing activities related to the analysed value chain. To simplify future site selection processes and activity allocation, a decision support model was developed in Scenario 360, an interactive GIS platform, using the factors from the SMCE to facilitate prioritization of activities in the SEZs. In conclusion, the developed model could be adopted to facilitate allocation of other activities in the SEZs, which in turn would facilitate prioritization of infrastructure investments. Moreover, as a recommendation, improved data availability and management would be beneficial for such a model to be more useful in strategic spatial planning.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/85184
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