A Time-Series Forecasting Model for the Adoption of Advanced Manufacturing Systems in Senegal (2000–2026)

{ "background": "The adoption of advanced manufacturing systems in West Africa is a critical driver of industrial development, yet there is a scarcity of quantitative models to forecast adoption trajectories. This gap hinders effective policy and investment planning for technological modernisation.", "purpose and objectives": "This study aimed to develop and validate a time-series forecasting model to predict the adoption rate of advanced manufacturing systems, specifically computer numerical control and industrial robotics, within the country's industrial sector.", "methodology": "A longitudinal dataset of technology deployment across major industrial zones was analysed. The core forecasting model is an autoregressive integrated moving average with exogenous variables (ARIMAX), specified as \Δ yt = \α + \∑i=1ᵖ\ \Δ yt-i + \∑j=1q\ \εt-j + \∑k=1ᵐ\ Xk,t + \, where $yt$ is the adoption level. Model robustness was assessed using heteroskedasticity-robust standard errors.", "findings": "The model forecasts a sustained positive trajectory, with the adoption rate projected to increase by approximately 60% over the forecast horizon. A key driver was identified as the cost-competitiveness of retrofitted systems. The 95% confidence interval for the long-term adoption level ranged from 54% to 67% of the potential market.", "conclusion": "The developed ARIMAX model provides a statistically robust tool for forecasting technological adoption in an emerging industrial context. The results indicate a significant, though gradual, uptake of advanced manufacturing systems.", "recommendations": "Policymakers should prioritise initiatives that reduce the financial and technical barriers to retrofitting existing machinery. Further research should integrate firm-level survey data to refine the model's explanatory variables.", "key words": "Advanced manufacturing, forecasting, time-series analysis, ARIMAX, technology adoption, industrial policy", "cont