Industrial machinery fleets in Ghana are a critical component of various sectors including manufacturing, construction, and agriculture. The study utilised a fixed effects model to analyse panel data from multiple industrial sectors in Ghana. The model is specified as: Y₈ₓ = eta₀ + eta₁X₈ₓ + uᵢ + e₈ₓ, where Y₈ₓ represents the operational cost of machinery fleet in sector i at time t, and X₈ₓ includes variables such as machine age, maintenance frequency, and usage patterns. Robust standard errors were applied to account for potential heteroscedasticity. The analysis revealed that a 10% increase in the frequency of machine maintenance led to an average reduction of 5% in operational costs across all sectors studied. This study provides empirical evidence on cost-effectiveness improvements through targeted interventions, offering insights for policymakers and industrial stakeholders in Ghana. Policymakers should encourage regular maintenance schedules and promote the use of energy-efficient machinery to enhance fleet performance and reduce costs.
Abena Kwadwoolu (Thu,) studied this question.