Abstract
{ "background": "The operational efficiency of industrial machinery fleets is a critical determinant of productivity in developing economies, yet robust methodological frameworks for its evaluation are scarce. Existing assessments often rely on descriptive statistics, lacking causal rigour and failing to isolate the impact of systematic interventions.", "purpose and objectives": "This study aimed to develop and apply a quasi-experimental design to methodologically evaluate fleet management systems and quantify efficiency gains within an industrial context. The primary objective was to estimate the causal effect of a structured maintenance and logistics protocol on machinery availability and fuel economy.", "methodology": "A difference-in-differences design was implemented, comparing treatment and control groups across multiple industrial sites. The core statistical model, $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon_{it}$, was estimated using panel data on key performance indicators. Inference was based on cluster-robust standard errors to account for site-level heterogeneity.", "findings": "Implementation of the protocol led to a statistically significant increase in mean machinery availability of 17.3 percentage points (95% CI: 12.1, 22.5). Furthermore, a marked reduction in non-productive operational hours was observed across all treated sites, with fuel consumption per output unit decreasing by an average of 8.1%.", "conclusion": "The quasi-experimental approach provides a rigorous methodological framework for evaluating industrial engineering interventions, demonstrating that structured fleet management systems can yield substantial efficiency improvements. The findings confirm the viability of causal inference techniques in real-world operational research.", "recommendations": "Industrial enterprises should adopt formalised, data-driven fleet management protocols informed by causal evaluation methods. Policymakers and industry bodies are encouraged to promote the integration of such experimental and quasi-experimental designs into standard engineering practice for continuous improvement.", "key words": "quasi