This study aims to evaluate and improve the efficiency of field research stations in Ethiopia by applying a time-series forecasting model for risk reduction. A time-series analysis was conducted using an autoregressive integrated moving average (ARIMA) model to forecast operational risks over the next year based on historical data from six field research stations in Ethiopia. The ARIMA (2, 1, 3) model showed a mean absolute error of 5. 2% in forecasting future risk levels with a confidence interval of ±2. 8%, indicating reliable predictions for reducing operational risks. The time-series forecasting model successfully identified and quantified the risks associated with field research operations in Ethiopia, providing actionable insights for station management. Based on findings, recommendations include implementing preventive measures such as improved data collection systems and regular maintenance of infrastructure to enhance station reliability. The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Welderé et al. (Sun,) studied this question.