"background": "The adoption of advanced manufacturing systems is critical for industrial development, yet robust methodologies for tracking and forecasting their uptake in emerging economies are lacking. Rwanda's strategic industrial policy provides a pertinent case for methodological development in this domain. ", "purpose and objectives": "This study aims to methodologically evaluate frameworks for assessing manufacturing systems and to estimate adoption rates using a panel-data model. The objective is to provide a replicable analytical tool for engineering and policy analysis. ", "methodology": "A longitudinal dataset from a census of medium and large plants was constructed. Adoption was modelled using a fixed-effects panel regression: A{it = \ + \1Tt + \2Xit +, where Ait is the adoption status for plant i at time t, \ denotes plant-specific effects, T is a time trend, and X is a vector of plant-level covariates. Inference was based on robust standard errors clustered at the plant level. ", "findings": "The methodological evaluation identified significant measurement biases in conventional survey tools. The panel estimation revealed a positive, statistically significant time trend (\1 = 0. 07, 95% CI 0. 04, 0. 10), indicating an average annual increase in adoption likelihood of 7 percentage points. Plant size and export orientation were key determinants. ", "conclusion": "The proposed panel-data methodology offers a more reliable alternative for measuring technological diffusion. The results confirm a steady, albeit moderate, uptake of modern manufacturing systems, driven by specific firm characteristics. ", "recommendations": "Industrial policy should target support towards smaller, non-exporting firms to broaden adoption. Future research should integrate the developed methodology with techno-economic feasibility assessments. ", "key words": "manufacturing systems, technology adoption, panel data, fixed effects, industrial policy, econometrics", "contribution statement": "This paper provides a novel panel-data estimation
Niyonzima et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: