The adoption of industrial machinery fleets systems in Tanzania is a critical area for enhancing productivity and competitiveness within the manufacturing sector. A mixed-method approach combining quantitative analysis through panel data estimation and qualitative insights from interviews was employed to assess the impact of various factors on adoption rates. Panel data revealed significant variation in adoption rates across different sectors (e. g. , textiles, food processing) with a notable trend showing higher adoption rates in urban areas compared to rural settings. The study confirmed that panel data methods are robust for measuring adoption rates and provided valuable insights into the factors affecting industrial machinery system adoptions. Policy makers should consider sector-specific strategies and targeted interventions based on findings from this research to promote wider adoption of industrial machinery systems in Tanzania. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Panga et al. (Tue,) studied this question.