Panel data analysis uncovers efficiency gains in industrial machinery fleets, suggesting targeted interventions for improvement.
Industrial machinery fleets play a crucial role in South Africa's manufacturing sector, yet their operational efficiency varies significantly. The study employs a two-stage least squares (2SLS) regression model for estimating efficiency gains, accounting for potential endogeneity issues. The robustness of the findings is evaluated with Monte Carlo simulations to assess uncertainty. The estimated efficiency score for machinery fleets in South Africa ranges between 65% and 70%, indicating substantial room for improvement through targeted interventions. Our analysis provides a structured framework for policymakers and industry practitioners to optimise the use of industrial machinery fleets, leading to reduced operational costs and enhanced productivity. Based on our findings, we recommend the implementation of preventive maintenance programmes and continuous training for operators to improve fleet efficiency. Industrial Machinery Fleets, Panel Data Analysis, Two-Stage Least Squares (2SLS), Efficiency Gains The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.
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Gupafoa et al. (2005) studied this question.
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