"background": "The adoption of advanced manufacturing systems in developing economies is a critical driver of industrial productivity. However, rigorous, longitudinal analysis of adoption determinants within the West African context remains scarce, with methodological approaches often inconsistent and lacking robust empirical validation. ", "purpose and objectives": "This study aims to methodologically evaluate approaches for analysing manufacturing systems adoption and to apply a panel-data estimation model to quantify adoption rates and their key drivers within the Senegalese industrial sector. ", "methodology": "A comparative analysis was conducted using a novel unbalanced panel dataset from a census of registered manufacturing plants. The core analytical model is a two-way fixed effects specification: Adoption{it = \ + \1 Xit + \ + \ +, where \ and \ represent plant and time fixed effects. Robust standard errors were clustered at the plant level to ensure inference validity. ", "findings": "The methodological evaluation identified significant bias in prior cross-sectional studies. Panel estimation revealed that access to reliable three-phase electrical power had the strongest positive association with adoption (coefficient = 0. 42, 95% CI: 0. 38 to 0. 46), whereas firm size showed a non-linear relationship. ", "conclusion": "Longitudinal panel-data methods are superior for isolating causal drivers of technological adoption in this context. The findings underscore that infrastructure reliability is a more potent catalyst for adoption than previously emphasised financial incentives alone. ", "recommendations": "Industrial policy should prioritise investments in foundational industrial infrastructure, particularly power quality. Future research should integrate supply-chain linkages into adoption models and expand panel datasets to include smaller, informal enterprises. ", "key words": "manufacturing systems, technology adoption, panel data, fixed effects, industrial policy, Senegal", "contribution statement": "This study provides the first application of a plant-level panel-data model to analyse manufacturing technology adoption in Senegal, introducing a novel methodological framework for isolating infrastructure effects from firm
Ndiaye et al. (Sun,) studied this question.