"background": "Industrial machinery fleet management is a critical operational and financial component for capital-intensive industries in developing economies. Inefficiencies in these systems lead to substantial cost overruns and project delays, yet there is a paucity of robust, quantitative frameworks for evaluating their cost-effectiveness in such contexts. ", "purpose and objectives": "This study aims to develop and apply a novel multilevel modelling framework to quantify the cost-effectiveness of industrial machinery fleet management systems, identifying key operational and organisational determinants of financial performance. ", "methodology": "A cross-sectional dataset was compiled from machinery logs, maintenance records, and financial reports across multiple industrial sites. A three-level linear mixed model was fitted to assess cost variance: ijk = \0 + u{i + vij + \₈₉₊, where i, j, and k index company, site, and individual machine, respectively. Robust standard errors were used for inference. ", "findings": "The multilevel analysis revealed that 58% of the variance in operational costs was attributable to differences between companies, highlighting the dominant role of organisational-level policies. A one-standard-deviation increase in preventive maintenance compliance was associated with a 12. 4% reduction in mean monthly operating costs (95% CI: 9. 1% to 15. 7%). ", "conclusion": "Cost-effectiveness in fleet management is predominantly influenced by strategic, company-wide practices rather than site-specific or machine-level factors. The multilevel approach provides a superior analytical lens compared to conventional single-level regression. ", "recommendations": "Industry managers should prioritise the implementation and auditing of standardised, company-wide maintenance protocols. Policymakers are advised to support initiatives that enhance data-driven, organisational-level benchmarking for industrial asset management. ", "key words": "fleet management, multilevel modelling, cost-effectiveness, maintenance, industrial machinery, developing economy", "contribution statement": "This paper provides the first application of multilevel regression
Gebre et al. (2003) studied this question.