Methodological Evaluation and Cost-Effectiveness Analysis of Process-Control Systems in South Africa: A Quasi-Experimental Design

The adoption of automated process-control systems in industrial and civil engineering projects is increasing, yet robust methodological frameworks for evaluating their cost-effectiveness in specific regional contexts are lacking. This creates uncertainty for engineers and project managers making capital investment decisions. This study aimed to develop and apply a novel quasi-experimental methodology to empirically evaluate the cost-effectiveness of implementing advanced process-control systems within the South African engineering sector. A quasi-experimental design with matched control groups was employed across multiple construction and manufacturing sites. Cost and performance data were collected pre- and post-implementation. Cost-effectiveness was analysed using a generalised linear model: CEᵢ = β₀ + β₁ Treatmentᵢ + β₂ Scaleᵢ + εᵢ, where εᵢ represents robust standard errors clustered by site to account for heteroskedasticity. The intervention group demonstrated a statistically significant reduction in average unit production costs of 18.7% (95% CI: 15.2% to 22.1%) compared to the control group, after controlling for project scale. The benefit-cost ratio for implemented systems was 3.4, indicating high economic returns. The applied quasi-experimental design provides a rigorous methodological framework for evaluating technological interventions in engineering. Results confirm that advanced process-control systems can be highly cost-effective in the local context. Engineering firms should consider the structured methodology presented for future technology assessments. Policymakers and industry bodies are encouraged to promote standardised cost-tracking to facilitate similar evaluations. process control, cost-benefit analysis, quasi-experiment, engineering management, industrial automation This paper provides a novel methodological framework for the empirical evaluation of engineering technologies, filling a critical gap in evidence-based investment decision-making for the region.