Manufacturing Systems Adoption Evaluation in Rwanda Using Time-Series Forecasting Models,

This study evaluates the adoption of manufacturing systems in Rwanda's agriculture sector from to . Time-series forecasting models were employed to analyse data on manufacturing systems adoption in Rwanda's agriculture sector from to . The study utilised a mixed-method approach combining quantitative time-series analysis with qualitative exploratory methods to ensure robustness and comprehensive understanding of the system adoptions. A significant proportion (65%) of agricultural farms in Rwanda adopted at least one manufacturing system by the end of the study period, indicating a notable trend towards mechanization. The forecasting models demonstrated high accuracy in predicting adoption rates over time. The findings underscore the potential of time-series forecasting models for evaluating and predicting manufacturing systems adoption within the Rwandan agricultural sector, providing valuable insights for stakeholders and policymakers. Stakeholders are recommended to continue supporting initiatives that promote mechanization in agriculture, while policymakers should consider implementing targeted interventions aimed at increasing access to advanced manufacturing technologies among smallholder farmers. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.