Abstract
{ "background": "The optimisation of manufacturing systems in developing economies is critical for industrial growth, yet robust methodological frameworks for evaluating their cost-effectiveness are lacking. Existing analyses often fail to account for the hierarchical structure of plant-level data, where operational units are nested within firms, leading to potentially biased estimates.", "purpose and objectives": "This study aims to develop and apply a multilevel modelling framework to methodologically evaluate the cost-effectiveness of manufacturing systems in a West African context. The primary objective is to quantify the influence of plant-level operational factors and firm-level strategic factors on overall production costs.", "methodology": "A cross-sectional dataset from a national survey of manufacturing plants was analysed using a two-level random intercept model. The model, specified as $\\text{Log}(Cost{ij}) = \\beta{0} + \\beta{1}X{ij} + u{j} + e{ij}$, where $i$ denotes plants and $j$ firms, was estimated using restricted maximum likelihood with robust standard errors to account for heteroscedasticity.", "findings": "The multilevel analysis revealed that 32% of the variance in log production costs was attributable to firm-level heterogeneity. A one-standard-deviation increase in the automation index was associated with a 7.4% reduction in unit cost (95% CI: 4.1% to 10.6%), after controlling for firm size and capital intensity.", "conclusion": "The application of multilevel regression provides a more rigorous methodological approach for evaluating manufacturing systems, confirming that both plant-level operations and overarching firm-level strategies are significant drivers of cost-effectiveness.", "recommendations": "Manufacturing firms should prioritise investments in targeted automation. Policymakers and industry bodies are advised to adopt hierarchical modelling techniques for future industrial surveys to inform more effective sectoral support programmes.", "key words": "multilevel modelling, cost-effectiveness, manufacturing systems, industrial engineering, Senegal, regression analysis", "contribution statement": "This paper provides a novel methodological