African Swine Science (Agri/Animal Science) | 15 November 2004
Methodological Evaluation of Manufacturing Systems in Rwandan Farms: A Time-Series Forecasting Model for Efficiency Assessment,
R, u, g, a, m, b, a, C, h, a, r, l, e, s, ,, K, a, m, i, j, o, b, a, G, a, s, p, a, r, d
Abstract
This study evaluates manufacturing systems in Rwandan farms to enhance efficiency measurement methods. A mixed-method approach combining field surveys and secondary data analysis was employed. Time-series forecasting models were constructed using autoregressive integrated moving average (ARIMA) methodology to predict future efficiencies based on historical performance data from Rwandan farms. The ARIMA model demonstrated a significant improvement in forecast accuracy compared to previous methods, with an average error reduction of up to 15% for monthly efficiency measurements across all farms. The study confirms the effectiveness of ARIMA models in forecasting farm efficiencies and highlights their potential for policy-making and resource allocation in agricultural settings. Implementing these models can lead to more informed decision-making, particularly regarding infrastructure investment and training programmes aimed at enhancing efficiency. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.