Abstract
{ "background": "The management of industrial machinery fleets is critical for infrastructure development, yet robust empirical evidence on the cost-effectiveness of systematic fleet management in developing economies is scarce. Existing evaluations often lack rigorous counterfactual analysis.", "purpose and objectives": "This study aims to methodologically evaluate the impact of implementing structured fleet management systems on operational costs and to assess their cost-effectiveness within the Nigerian construction and industrial sectors.", "methodology": "A quasi-experimental difference-in-differences (DiD) design was employed, analysing panel data from firms with and without formalised systems. The core model is $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon_{it}$, where $\\delta$ captures the causal effect. Inference is based on cluster-robust standard errors at the firm level.", "findings": "The DiD estimator revealed that firms adopting structured fleet systems achieved a statistically significant reduction in average monthly maintenance costs of 18.7% (95% CI: -22.3%, -15.1%) relative to the control group. The benefit-cost ratio for implementation was estimated at 3.2 over the study period.", "conclusion": "Formalised fleet management systems are a cost-effective intervention for industrial machinery operations, leading to substantial and significant reductions in operational expenditures.", "recommendations": "Industry stakeholders should prioritise investment in integrated fleet management systems. Policymakers are encouraged to develop frameworks and incentives to support their adoption across the sector.", "key words": "fleet management, difference-in-differences, cost-effectiveness, industrial machinery, maintenance, Nigeria", "contribution statement": "This paper provides the first application of a quasi-experimental DiD framework to isolate the causal effect of fleet management systems on costs in this context, introducing a robust methodological approach for