Multilevel Regression Analysis to Evaluate Adoption Rates of Process-Control Systems in Ghana's Manufacturing Enterprises

Process-control systems (PCSs) are critical for enhancing manufacturing efficiency in Ghana's enterprises. However, their adoption rates vary significantly across different sectors and companies. A multilevel logistic regression model was employed to analyse data from a sample of 150 manufacturing enterprises across various sectors. Data collection involved questionnaires and interviews, supplemented by secondary sources for contextual information. The analysis revealed that the proportion of companies adopting PCSs in the food processing sector is significantly higher than in other sectors (72% vs. 38%, p < 0.05). Multilevel regression models provide a robust framework for understanding complex adoption dynamics and can inform policy decisions aimed at increasing PCS utilization. Implementing targeted interventions, such as financial incentives or technical support programmes, is recommended to promote PCS adoption in sectors with lower rates of implementation. Process-Control Systems, Multilevel Regression Analysis, Manufacturing Enterprises, Ghana The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.