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The study aims to evaluate industrial machinery fleet systems and quantify their impact on yield improvement in Ethiopia.

March 13, 2026Open Access

Methodological Evaluation and Multilevel Regression Analysis of Industrial Machinery Fleet Systems for Yield Improvement in Ethiopia (2000–2026)

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The study aims to evaluate industrial machinery fleet systems and quantify their impact on yield improvement in Ethiopia.
Developed a longitudinal panel dataset of fleet performance and yield data.
Applied a three-level hierarchical linear model to assess fleet effects on yield.
Used restricted maximum likelihood estimation with robust standard errors.
Model estimates show a strong positive relation between predictive maintenance and yield (coefficient 0.15).
Supply chain logistics for spare parts significantly impact fleet availability compared to machinery age.

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Longitudinal analysis shows fleet characteristics impact yield in Ethiopia, suggesting improvements in maintenance and logistics.

Abebe et al. (2011) studied this question.

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