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March 4, 20260 citationsOpen Access

Evaluating Cost-Effectiveness of Machinery Fleets in Ghana Through Quasi-Experimental Design

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AAAmoako AmegyioheneAAAgbeko AgudjeBBBawumia Baidarkor

Key Points

  • The study aims to evaluate the cost-effectiveness of industrial machinery fleets in Ghana.
  • Mixed-methods approach combining econometric analysis and field surveys.
  • Assess fleet utilization rates and operational costs across different sectors.
  • Analyze productivity metrics within Ghana's industrial landscape.
  • Automated machinery adoption rates are significantly higher in larger enterprises (52% vs. 30%, p < 0.01).
  • Indicates a shift towards more efficient fleet management strategies.
  • Highlights the need for sector-specific adaptations and technological upgrades in machinery fleets.

Abstract

Industrial machinery fleets play a crucial role in Ghana's economic development, yet their cost-effectiveness remains poorly understood. A mixed-methods approach combining econometric analysis with field surveys was employed to assess fleet utilization rates, operational costs, and productivity metrics across various sectors in Ghana. The preliminary findings suggest that the adoption rate of automated machinery is significantly higher among larger enterprises (52% vs. 30%, p < 0. 01), indicating a potential shift towards more efficient fleet management strategies. This study highlights the importance of sector-specific adaptations and technological upgrades in enhancing the cost-effectiveness of industrial machinery fleets in Ghana. Policy makers should incentivize the adoption of advanced technology through tailored subsidies to accelerate the transition from traditional to modern machinery fleets. Industrial Machinery Fleets, Quasi-Experimental Design, Cost-Effectiveness, Ghana The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.

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Cite This Study

Amegyiohene et al. (2006) studied this question.

synapsesocial.com/papers/69a7cd3dd48f933b5eed9653https://doi.org/10.5281/zenodo.18837170
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