Repurposing support tendered youth owned Small, Medium, and Micro-Enterprises in urban agri-business sector in Durban

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Food security is one of the most fundamental challenges facing many countries, especially in the developing economies, which still has a vast section of its population still trapped in the socio-economic cocoon of poverty, unemployment, and inequality. This paper aims to investigate the institutional support in the facilitation of empowerment and development of youth Small, Medium, and Micro-Enterprises (SMMEs) to be active participants in the agribusiness economic mainstream. The paradigm shift from primary agriculture into urban farming business models in agri-business could accelerate the ascendancy of youth SMMEs in the competitiveness stakes. The theoretical analysis focused on the resource-based view model, institutional theory, and the role of the CSR impact as a conceptual framework for the study. The research design was predicated on the quantitative methodology, which enabled the researchers to statistically test the reliability and validity of the theory. The findings indicated that the CSR interventions had not yielded a fundamental impact on assisting youth SMMEs within the agribusiness sector. The results also identified a lack of tangible and result-driven institutional support from policy-makers and authorities. Overall targeted technological transfer as a strategic and critical resource to youth SMMEs is another constraining factor from empirical findings. The results also revealed the lack of monetary and non-monetary access by youth SMMEs as hampering their competitiveness and profits ability. The findings advocated that the policy-makers could synthesize the theories encapsulated in the study and the empirical evidence as the bedrock for bespoke, customized, and tailor-made youth SMMEs’ bespoke support, empowerment, and development of their entities.

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    • Figure 1. Architect of sustainable youth SMMEs in the urban agriculture support mechanism
    • Table 1. Percentage’s sources of income
    • Table 2. Life-cycle stage
    • Table 3. Descriptive statistics
    • Table 4. Correlation coefficient
    • Conceptualization
      Tony Ngwenya
    • Investigation
      Tony Ngwenya
    • Project administration
      Tony Ngwenya
    • Visualization
      Tony Ngwenya
    • Writing – original draft
      Tony Ngwenya, Pfano Mashau
    • Data curation
      Pfano Mashau
    • Formal Analysis
      Pfano Mashau
    • Methodology
      Pfano Mashau
    • Writing – review & editing
      Pfano Mashau