In Ethiopia, agriculture accounts for 85% of the total employment, and the country’s export entirely relies on agricultural commodities. The country is continuously affected by chronic food shortage. In the last 40 years, the country’s population have almost tripled; and more agricultural productivity is required to support the livelihood of millions of citizens. As reported by various research, Ethiopia needs to address a number of policy and strategic priorities to improve agriculture; however, in-efficient agriculture supply chain for the supply of input is identified as one of the significant challenges to develop agricultural productivity in the country. The research problem that interest this thesis is to understand Big Data Analytics’ (BDA) potential in achieving better Agriculture Input Supply Chain in Ethiopia. Based on this, we conducted a basic qualitative study to understand the expectations of Supply Chain Management (SCM) professionals, the requirements for the potential applications of Big Data Analytics - and the implications of applying the same from the perspectives of SCM professionals in Ethiopia. The findings of the study suggest that BDA may bring operational and strategic benefit to agriculture input supply chain in Ethiopia, and the application of BDA may have positive implication to agricultural productivity and food security in the country. The findings of this study are not generalizable beyond the participants interviewed.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-97011 |
| Date | January 2020 |
| Creators | Hassen, Abdurahman, Chen, Bowen |
| Publisher | Linnéuniversitetet, Institutionen för informatik (IK), Linnéuniversitetet, Institutionen för informatik (IK), abdurahmanhassen@outlook.com |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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