Handicraft small enterprises as an instrument for rural economic growth and poverty eradication

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In South Africa, exploiting economic opportunities in the handicraft sector could create livelihood and employment for ordinary citizens living in rural areas. The potential contribution of handicraft small enterprises to sustainable livelihoods and poverty alleviation is yet to be fully exploited. It is also regarded as a sector with great growth potential, but the degree of support provided to the handicraft sector is low. The study aims to evaluate the socioeconomic factors influencing the viability of handicraft small businesses operating in KwaZulu-Natal. Data collection was drawn from a stratified random sample of 196 handicraft practitioners operating in different areas of KwaZulu-Natal Province with a structured questionnaire. Data analysis was performed with the STATA statistical package. The results obtained from the study have shown that 84 enterprises (42.86%) were not viable, whereas 112 of the 196 handicraft enterprises (57.14%) were viable. The percentage of overall correct classification for this procedure was equal to 77.96%. Percentage sensitivity for the fitted logistic regression model was equal to 60.71%. Percentage specificity for the fitted logistic regression model was equal to 82.14%. The p-value obtained from Hosmer-Lemeshow goodness-of-fit test was equal to 0.0884 > 0.05. This indicates that the fitted logistic regression model is fairly well reliable. The findings from the analysis showed that two factors significantly influenced the viability of handicraft enterprises. These two factors were the belief that handicraft business could sustain the handicraft practitioner, and the level of support for handicraft businesses from non-governmental organizations is decreasing.

Acknowledgment
South Africa SarChi Chair, Nation Research Fund and Department of Science and Technology, South African, for providing funding for this research.

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    • Figure 1. The places of production of artifacts (n = 196)
    • Figure 2. Number of years in business (n = 196)
    • Figure 3. Perception of handicraft business (n = 196)
    • Table 1. Summary of gender, age, and race (n = 196)
    • Table 2. Level of formal education (n = 196)
    • Table 3. Summary of percentages of artisan attributes (n = 196)
    • Table 4. Assessment of sales turnover (n = 196)
    • Table 5. Loan applications by respondents (n = 196)
    • Table 6. Results obtained from logit analysis
    • Table 7. Summary of two research hypotheses tested as part of the study
    • Conceptualization
      Oluwayemisi A. Abisuga-Oyekunle, Mammo Muchie
    • Data curation
      Oluwayemisi A. Abisuga-Oyekunle
    • Formal Analysis
      Oluwayemisi A. Abisuga-Oyekunle
    • Investigation
      Oluwayemisi A. Abisuga-Oyekunle
    • Methodology
      Oluwayemisi A. Abisuga-Oyekunle, Mammo Muchie
    • Project administration
      Oluwayemisi A. Abisuga-Oyekunle
    • Software
      Oluwayemisi A. Abisuga-Oyekunle
    • Validation
      Oluwayemisi A. Abisuga-Oyekunle
    • Visualization
      Oluwayemisi A. Abisuga-Oyekunle
    • Writing – original draft
      Oluwayemisi A. Abisuga-Oyekunle
    • Funding acquisition
      Mammo Muchie
    • Resources
      Mammo Muchie
    • Supervision
      Mammo Muchie
    • Writing – review & editing
      Mammo Muchie