Predictive Analytics for SA Land Reform | AcademicJobs
South African researchers from TUT, UNISA, UFS, and NMU propose a predictive analytics model to balance equity and productivity in land reform, addressing high failure rates with ML and GST.
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Dr Siphe Zantsi is an agricultural economist affiliated with the Department of Agriculture and Animal Health at the University of South Africa. He holds a PhD in Agricultural Economics from Stellenbosch University. Dr Zantsi serves as an Agricultural Economist at the Agricultural Research Council in Pretoria. He previously worked as a researcher at Agroscope in Switzerland during his doctoral studies and as a post-doctoral research fellow at the University of Johannesburg and the University of Fort Hare.
His research focuses on rural development, agrarian and land reform, food economics, and smallholder commercialization in South Africa. Dr Zantsi has contributed to studies employing agent-based modeling to assess land redistribution policies and has published extensively on topics including beneficiary selection for land reform, the degree of smallholder commercialization, and rangeland conditions on land reform farms. His work appears in peer-reviewed journals such as Development in Practice, Agrekon, and Frontiers in Sustainable Food Systems, with over 550 citations recorded on Google Scholar. Dr Zantsi has also examined the role of cooperatives in agri-food value chains and the impacts of land reform initiatives.
South African researchers from TUT, UNISA, UFS, and NMU propose a predictive analytics model to balance equity and productivity in land reform, addressing high failure rates with ML and GST.
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