Methodological Scrutiny of Process-Control Systems in Nigeria Using Time-Series Forecasting Models

Recent studies have highlighted the importance of process-control systems in ensuring efficiency and quality in construction projects across Nigeria. However, understanding the adoption rates of these systems is crucial for policy makers and stakeholders to inform future investments. The study employs time-series forecasting techniques such as ARIMA (AutoRegressive Integrated Moving Average) model to analyse data from construction sites in Nigeria. A robustness check is conducted by cross-validating results using different model configurations and assessing their predictive accuracy through out-of-sample validation. Initial findings indicate a steady upward trend in the adoption rate of process-control systems, with an estimated increase of 15% per annum from year one to five. The ARIMA (2, 1, 0) configuration proved most accurate for forecasting future adoptions. The time-series analysis provides valuable insights into the dynamic nature of process-control systems adoption in Nigerian construction environments. Future research could explore interdependencies between technological advancements and socio-economic factors impacting adoption rates. Policy makers should consider investing in capacity-building programmes for practitioners to enhance their understanding and implementation of advanced process-control systems, thereby improving project outcomes and efficiency. Process-Control Systems, Nigeria, Time-Series Forecasting, ARIMA Model, Adoption Rates The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.