Industrial machinery fleets play a crucial role in manufacturing industries in Tanzania. A multilevel regression model was employed to analyse data on industrial machinery adoption across multiple levels, including different fleet sizes and geographical regions in Tanzania. The multilevel regression analysis revealed that the presence of skilled maintenance personnel significantly increased machinery adoption rates by about 25% compared to those without such personnel. This study provides a robust framework for understanding factors affecting industrial machinery adoption, offering insights into optimising fleet management strategies in Tanzania. Policy makers and industry stakeholders should prioritise training programmes for maintenance personnel to enhance machinery utilization rates. Industrial Machinery Adoption Rates, Multilevel Regression Analysis, Tanzanian Manufacturing Industries The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Kamile Mwinzi (Sun,) studied this question.
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